New Resource: Getting Started with Custom Analysis in Viva Insights and Copilot Analytics
Last month, we introduced an exciting new resource to help organizations unlock deeper insights with Microsoft 365 Copilot: the “Getting Started with Custom Analysis in Copilot Analytics” playbook. This guide is now publicly available as part of the Copilot Success Kit under the User Enablement section. Why This Playbook Matters As more organizations adopt and utilize Microsoft 365 Copilot, many are asking:How do we measure success? How can we go beyond the default dashboards and Power BI reports to answer deeper questions? And how do we go about planning and setting up a measurement program? This playbook was created in response to feedback from customers and partners who wanted practical guidance on the deployment and strategy side of Copilot Analytics. It complements the previously released Advanced Examples playbook, which focuses on interpreting analytics once a program is in place. The new guide takes a step back to help you build a custom analysis strategy from the ground up. What You’ll Learn The playbook offers a structured, step-by-step approach for analytics leaders, change management teams, and Copilot champions. Key topics include: Planning a Copilot Analytics measurement program aligned to your organization's goals Evaluating out-of-the-box tools Setting up Viva Insights for custom analysis, including role assignments and data preparation Running queries and building an analysis plan Analyzing results using R or Python Whether you’re just starting your Copilot journey or looking to scale your analytics capabilities, this resource provides the tools and methodology to measure adoption impact, identify barriers, and drive success. Explore the Playbook Access the playbook here: 👉 https://adoption.microsoft.com/files/copilot/GettingStartedWithCustomAnalysisInCopilotAnalytics.pptx What’s Next To help you get the most out of this resource, we’ll be rolling out: A series of blog posts and webinars showcasing how to use the playbook effectively Real-world success stories and advanced analysis techniques Additional materials such as analysis templates, code examples, and visualization guides to support data scientists and analysts Start your custom analysis journey today and take your Copilot Analytics strategy to the next level.Empowerment Unlocked: Key Conditions for Thriving Teams
In the second blog of Microsoft People Science team’s People Success Series, we shared the importance of employee trust in leadership. This 3 rd edition “flips the script” and examines the importance of leadership trust in employees: a cultural foundation to empowerment. With rapid technological changes, increased pressures to reskill, shifting workplace policies, and staff restructuring, certainty about how and where one does their job can be a challenge for many employees. Recent research found that job insecurity and workplace uncertainty significantly impact workers’ stress levels, emotional exhaustion, and motivation. Workers affected by constant, overlapping changes reported higher levels of disorientation and confusion, which correlated with reduced performance and engagement 1 . But at the same time, today’s fast-changing business landscape requires organizations to respond quickly to challenges and opportunities and employees to be agile and resilient. So how can people be more empowered to take risks and make decisions in a work environment that feels less certain and more stressful? In 2023, our research on the PS Elements found 9 critical needs associated with Empowerment, such as Decision Transparency, Risk-Taking, and Work Ownership. Our recent research on employee engagement and attrition drivers between 2024-2025 2 revealed five empowerment items with the strongest associations with engagement and attrition. Empowerment Top Five Drivers of Engagement and Attrition Empowerment Item Item Text Attrition Multiplier * Pearson r (correlation) value ** eSat Recommend Job Resources I have the resources I need to do my job well 1.94 .76 .76 Barriers to Execution At <COMPANY_NAME> we do a good job removing barriers that slow down our work 2.28 .71 .70 Continuous Improvement <COMPANY_NAME> continually improves the way work gets done 2.12 .74 .76 Job Empowerment I feel empowered to make decisions regarding my work 2.79 .65 .63 Initiative I am encouraged to find new and better ways to get things done 2.67 .81 .78 * from the 2025 attrition multiplier analysis: figures represent how many times more likely employees are to stay if these conditions are met 2 . ** from the 2025 engagement key driver analysis: displaying the Pearson r correlation value between the empowerment item and engagement outcomes 2 . Today, we’ll take a deeper look into each of these empowerment factors and provide data-backed recommendations on how to improve the conditions for empowerment. Job resources: critical to meeting today’s work demands We define Job Resources as “resources (time, people, tools, information, knowledge) available when people need them to get their work done.” Our research shows there’s a strong (with Pearson r values = .76) correlation between having the resources to succeed and eSat: (How happy are you working at <COMPANY_NAME>?) and Recommend (I would recommend <COMPANY_NAME> as a great place to work) 2 . With the many changes happening in today’s work world, employees are under pressure to keep up. Providing sufficient time and resources helps to mitigate feelings of stress. And if not provided adequate resources, our data shows people are twice as likely to leave than those who are 2 . Calls to action: Encourage managers to read employee survey comments and have conversations with direct reports about what they need and why. Do they have access to networking opportunities? Do they have access to technology and the training to use it? Do they have sufficient time to adjust to changes? Take an expansive perspective on overall work demands and resources to make sure that employees feel the full support of the organization. This, in turn, will help employees develop psychological capital and trust in leadership. Help employees use Copilot prompts and develop job-specific agents that speed up routine tasks. Barriers to execution: when slow processes get in the way of timely performance A critical component of empowerment is the ability to “carry out one’s duties and responsibilities without running into roadblocks and with minimal delays.” People expect to see company actions to remove barriers and install efficiencies that make it easier to execute the work. Employees who see their management removing obstacles are more than 2 times as likely to stay with the company than those who don’t 2 . Our data shows a dramatic increase (more than 15% in Pearson r value YoY) in the correlation between removing barriers and engagement outcomes (eSat and Recommend) 2 . This signals an increasing need for task efficiency and predictability in an environment where work processes and roles are quickly evolving. Calls to action: While some process roadblocks are systemic and require company support to fix, many barriers to action are entirely addressable by individual workers and small teams (e.g., testing small improvements in their workflow before asking for changes). Give employees the resources and authority to safely mitigate problems at their job level and within their scope without asking for permission. Open up feedback channels so that employees can easily report obstacles that get in their way. Then involve them in developing solutions and making changes to streamline and improve workflows. Continuous improvement: a mindset for lasting success We recognize continuous improvement when companies put effort and resources into ongoing improvements that help people successfully get their work done and produce better quality outcomes. It is an attitude and approach where individuals, teams, and organizations are committed to consistently seeking ways to improve processes, products, skills, and outcomes over time. The continuous improvement mindset is rooted in the belief that there’s always room for growth and optimization, no matter how well things are currently working. Our stats show that continuous improvement is a strong driver of eSat and Recommend (with Pearson r values of .74 and .76 respectively) 2 . Changes in technology (e.g., AI), office location (e.g., hybrid/remote workplace), and work policies (e.g., asynchronous “always on” work) are swiftly transforming the way work gets done, but without proper process reengineering, these changes can feel disruptive and create frustration among workers. Both barriers to execution and continuous improvement call for streamlining work to reduce friction and are highly associated with people feeling well-supported by the company. Calls to action: Organizations can better support their managers to help their teams operate more efficiently and successfully by providing them with more decision-making authority and/or better tools to make improvements upon local team feedback. Help teams surface improvement ideas through connections to other departments across the organization. Managers can guide their teams on how to grow their informal networks and use them for sharing learnings, innovation, and improvement. When individual contributors face inefficiency at work, encourage them to bring the issues to their manager so it can be escalated. Leaders may not always have insight into the day-to-day challenges, so it’s up to employees to share their experiences to drive improvement. Job empowerment: a matter of trust from leadership Beyond efficiently getting the job done, empowerment also means being trusted to approach one’s work with ownership, flexibility, and autonomy. This is where leadership trust in employees will make or break feelings of empowerment. Employees want an optimal level of autonomy and involvement in decision making to perform their work without having to check in first – and without a lot of monitoring. In fact, employees are willing to leave if they experience too much micromanagement. Our research found that employees who have job empowerment decision making authority are 2.8 times less likely to leave than those who don’t 2 . Post-pandemic, hybrid workers have mostly proven they can be productive with less direct supervision, which has fundamentally reshaped their expectations around control and trust. Yet some leaders still don't agree, and continue to enforce strict mandates that harm retention, especially of the most vulnerable and marginalized groups (women, people with disabilities, those who cannot afford the commute and time away from caregiving responsibilities). In fact, employees from underrepresented groups are 22% more likely to consider leaving if flexibility is withdrawn 3 . And caregiving employees (73% of U.S. workforce) are 30% more likely to quit if their ability to manage care is compromised by return to office directives 4 . Calls to action: When managers micromanage (continuously checking up on employee progress), or worse yet, monitoring activities (e.g., tracking keyboard or camera actions), it can feel as though they lack trust which can lead to an environment of fear that hinders innovation and growth. Instead, encourage managers to check in on the status of the work tasks and use those moments as an opportunity to provide feedback and clarity which provide the necessary context for the team to plan and direct their own performance. Empowerment thrives when employees know they won’t be punished for thoughtful risks. Help managers foster a team environment that normalizes learning from mistakes where people discuss what worked and what didn’t without blame. Use language like “experiments” or “pilots” to frame decisions as opportunities for learning. Back employees publicly when they make decisions in good faith. Initiative: a path to fearless innovation People want the self-determination to be creative, take risks, and try new ways of approaching their tasks that bring joy to their work, improve their outcomes… and get the job done. In fact, taking Initiative scores highest among empowerment items as a very strong driver (with Pearson r values greater than .78) of eSat and Recommend 2 . Correlation values have risen 15% YoY indicating an increasing importance of the autonomy, space, and time to experiment with new work practices 2 . Today, workers welcome new technologies (like AI) that reduce repetitiveness and allow time for more complex strategic activities, leading them to seek greater control over their new, redefined roles 5 . Embracing new tools and processes requires a curious mindset that is open to experimentation and to discovering better ways of working. This mindset is fostered when people can experiment without the fear of negative consequences for failure. Taking risks requires a climate of psychological safety to challenge the status quo. Calls to action: Managers can encourage professional growth and risk taking by decreasing the weight assigned to goals based on expected outcomes and increasing the weight assigned to goals that encompass risk taking and learning. Encourage direct reports to challenge themselves by seeking responsibilities and learning opportunities that will take them in new directions. Recognize those who take risks and make independent decisions. Managers can model risk taking for their teams by sharing examples from their own work that demonstrate the value of creative approaches and innovative ideas. Share successes as well as misses, demonstrating that it is safe to fail. Managers can create a climate where it's safe to take risks by interacting with employees in ways that encourage alternative perspectives and approaches. Be sure to convey respect and consideration in verbal and nonverbal responses to innovative ideas. Ask questions designed to reveal and develop divergent thinking. Show an openness to new ideas that come from across departmental lines. Conclusion With today’s rapid workplace changes, empowering employees is essential for boosting engagement and retention. Empowerment grows with trust from leadership which enables employees to take risks and make decisions more confidently. When organizations provide job support and resources and actively promote self-determination, employees feel valued and motivated to contribute their best, benefiting both themselves and the company. Is employee empowerment where it needs to be for your organization to thrive? Think about which of the following survey questions is most critical for your organization's goals and consider including them on your next survey. References 1 American Psychological Association. (2025). Work in America™ Survey. Majority of U.S. workers say job insecurity has significant impact on their stress. 2 The 2025 engagement and attrition key driver refresh and longitudinal analysis determined the top predictors of engagement and voluntary attrition (across 235 customers) based on LinkedIn Glint survey scores in 2022, 2023, and 2025 representing 6.8 million employee survey responses. Engagement: As these data variables are continuous, Pearson's r was used to measure the correlation strength of the linear relationship between People Success “critical needs” (25 survey items that measure employee experiences aligned with the six People Success Elements) and the six engagement outcome items (eSat, Recommend, Manager, Belonging, Retention and Intent to Stay). The r values for each item were aggregated and averaged across all customers for each year reported. To calculate meaningful change from year to year, we examined the delta in r value for each item-outcome pair over the 3-year period. Then, we calculated the correlation percentile splits to determine the top 33 percent (r value YoY deltas from .10 up to .25) and bottom 33% (r value YoY deltas below .05). We comment here only on those items and their outcomes with r value deltas in the top third, noted as “top predictors” or “strong drivers” of the outcome(s) and whether the change is trending up or down. Attrition: Only survey item responses from at least 15 LinkedIn Glint customers who’ve had at least 80 voluntary terminations between survey administrations were included in this study. “Attrition Multipliers” were formed by comparing favorable vs. unfavorable survey responses scores from those voluntary termed employees for each of the People Success “critical needs” items. Aggregate analysis involved averaging the attrition multipliers per item at a customer level, filtered by n size for each of the three years in this longitudinal study. 3 The Hill. (Aug, 2024). Employers used return-to-office to make workers quit. Then this happened. 4 Upwards. (Nov, 2024). The Hidden Key to Successful RTO: Supporting Your Caregiving Employees. 5 Stanford Report. (2025, July 7). What workers really want from AI.Rebuilding Trust in the Workplace Before It’s Too Late
In this second blog in the People Success Elements series, we continue to dive deeper into the modern work experience and let survey responses from over 6.8M employees across more than 235 companies from 2022 – 2025 reveal why worker trust has waned and – importantly – how leaders can earn it back. In today’s workplace, even amid strong financials, many companies are navigating difficult decisions like layoffs and policy shifts—often without clear communication. The challenges faced by company leadership today are daunting , and stakeholder confidence in executive teams’ ability to handle them is reportedly at an all-time low 1 . Only 24% of employees say they trust senior leadership 1 . The Disconnect Between Words and Actions The most perplexing part of current trust challenges? It’s unfolding during a time of economic growth. Traditionally, trust dips during recessions or scandals. But today, the stock market has hit all-time highs, and there’s a labor shortage, yet workers still face layoffs and abrupt policy shifts 2 . That contradiction can significantly strain employee trust and morale. Across nearly all industries, the layoffs haven’t spared any sector 2 . When people perceive their employer is not being fully transparent, they are left confused and anxious, which only deepens mistrust. Return-to-office policy shifts, especially when implemented without employee input, have become a flashpoint for internal tension—highlighting the importance of inclusive decision-making. Nearly 75% of executives admit these mandates have caused internal conflict 2 . Moments like this break what’s called the “psychological contract,” an implicit understanding that employees have about what they owe the company and what the company owes them. Psychological contracts are tacit, not just unspoken but unconscious, and not clearly articulated in people’s minds until the moment they are broken 3 . Breaches can be driven by organizational factors such as low initial trust, employer reneging, value misalignment between employee and organization, organizational change, lack of support or fairness, and internal politics. Positive organizational practices can reduce breach perceptions, while negative actions increase them 3 . To cultivate a healthy relationship, today’s workforce requires a human-centric approach which fosters a deeper understanding of personal needs such that people care enough about their job and company to put in extra effort, thought, and creativity; to be proactive; to engage in extra-role behaviors 4 . The Perception of Leadership Recent research found that people across the board – from boards of directors to frontline employees – doubt that executive teams can juggle today’s disruptions and still put the enterprise’s interests above all else 1 . Employees may perceive leadership as disconnected or overwhelmed by today’s challenges. And to be fair, leaders have been dealing with “precedent-setting” disruptions lately, from global crises to rapid tech changes, which means they’re often trekking through uncharted territory 1 . Having confidence is key to trust. People need to believe their leaders have the experience and capability to handle challenges and keep the company on track. Further, Confidence in Leadership and Company Prospects (I am excited about <COMPANY_NAME>'s future) have a very strong correlation (with Pearson r values > .84) 5 , meaning that when employee confidence in leadership is low, so is their excitement, further eroding their loyalty to the company. No doubt, the past few years have been challenging with pandemics, social and political upheaval, AI acceleration, and more. Even strong leaders are flying without a playbook. But employees aren’t looking for perfection. They’re looking for humane treatment, honesty, and respect 1 . When decisions appear inconsistent and messaging feels out of touch, employee confidence in leadership’s priorities and alignment begins to erode. And here’s where leadership’s opportunity begins. Rebuilding Trust: How Leaders Can Get It Back So, how do you rebuild something as fragile and essential as trust? Here are four research-backed strategies that start at the top and ripple throughout the organization: Radical Transparency People don’t expect you to have all the answers, but they do expect the truth through honest, two-way communication. That means holding regular town halls, offering open Q&A sessions, and addressing hard questions head-on—especially around layoffs and restructuring, big policy changes or tech rollouts. Our recent data highlights the importance of transparency. Trust in Decision Making (Overall, I am satisfied with how decisions are made at <COMPANY_NAME>) is the strongest correlate (with a Pearson r of .91) of Confidence in Leadership 5 . In other words, lack of clear explanations has a strong, negative effect on trust in leadership. Think of transparency like internal “forward guidance.” Just like companies signal forecasts to investors, leadership can communicate potential changes early, honestly, and with context. Being upfront with upsetting news is rarely easy or comfortable, but people appreciate being told rather than being surprised. Visible Accountability and Fairness Nothing erodes trust like “rules for thee, not for me.” To rebuild trust, leaders must hold themselves accountable just as they do others. One bold idea emerging is pay transparency at the top, making executive compensation public and clearly linked to performance 2 . Employees aren’t naïve; they notice when a company is belt-tightening for everyone except the C-suite. Disparities in compensation during times of cost-cutting can impact perceptions of fairness and trust 2 . Our 2025 findings show that the correlation between Compensation Rewards (I am fairly compensated for the work that I do) and eSat has grown substantially (from a Pearson r of .68 in 2022 to .83 in 2025) 5 . Job security concerns may be making fair pay a more crucial factor for engagement. Fairness is often best demonstrated when leadership strives to hold itself accountable to the same values that are expected from staff. If “people first” is a core value, maintaining consistency in programs that advance equity and inclusion is essential. Quietly scaling back such efforts can create misalignment between mission and execution, undermining credibility. Recent findings show that Diversity Commitment (Top leaders demonstrate a visible commitment to diversity) has seen an strong uptick (from a Pearson r of .58 in 2022 to .72 in 2025) in strength as a driver of eSat 5 . People expect to be treated fairly, and this becomes increasingly essential in an ever more diverse work world. Believing there are Equal Opportunities (Regardless of background, everyone at <COMPANY_NAME> has an equal opportunity to succeed) also had a strong increase (from a Pearson r of .58 in 2022 to .72 in 2025) as a predictor of eSat 5 . When employees feel the playing field is level, they’re far more likely to trust leadership’s intentions 6 . Co-Creation Over Command-and-Control Here’s one of the most underutilized tools for restoring trust: involvement. Employees have great ideas, and high motivation to participate in decisions that affect them especially around hot-button issues like remote work, wellness benefits, and tech tools. Our data shows that when people have Job Empowerment (I feel empowered to make decisions regarding my work) they are 2.8x less likely to leave than those who don’t 5 . So why not ask? The return-to-office transition has shown how top-down decisions, even when well-intentioned, can create unintended challenges when employee perspectives aren’t fully considered. Nearly three-quarters of executives admit strict mandates have created internal conflict 2 . RTO is a prime opportunity to build trust by valuing employee input. Whether it’s surveys, cross-functional advisory panels, or policy pilots with built-in feedback loops, employee involvement fosters buy-in. Consistency and Unified Messaging This one’s deceptively simple but mission-critical: say what you mean and do what you say. When employees hear an executive saying one thing, and another contradicts it, or see decisions being reversed soon after they’re announced, the back-and-forth can chip away at credibility. The fix? Align messaging across leadership. Push back when mixed signals arise. Advocate for sticking to decisions unless new input justifies a change—and when that happens, explain why. Our data shows that Communication Flow (There is a good flow of communication between leadership, departments, and teams) is a strong driver of Confidence in Leadership (with a Pearson r of .74) and eSat (with a Pearson r of .69) 5 . Key messages should be transparent and reliable through every level of management and across the organization. Of course, there’s a balance between communicating decisions early even if they might change versus waiting until decisions are final. But there are no trade-offs for aligning communication across the organization. Consistency over time builds trust. Don’t Underestimate Empathy and Humility While powerful, these four strategies may fall flat without the right tone. To be successful each of these strategies must be carefully planned and executed with compassion, humility and authenticity. Preserving the psychological contract comes down to showing that you truly care. Our data show that Care (At work, I feel cared about as a person) has been a steady driver since 2022 of eSat and Recommend (with Pearson r values of .83 and .78 respectively) 5 . Showing you care starts with empathy, and empathy starts with listening. We found that people who have Inclusive Leaders (Leaders at <COMPANY_NAME> value different perspectives) are 2.8x less likely to leave than those who don’t 5 . When employees raise concerns about workplace changes, like Return-to-Office mandates or AI adoption, don’t just “acknowledge” them, find ways to address concerns. Empathy is saying, “I hear you, and here’s what we’re doing with your feedback.” Feeling well supported by leadership, Company Support (I feel well supported by <COMPANY_NAME> at this time) has a meaningful relationship with Confidence in Leadership (with a Pearson r value of .86) and eSat (with a Pearson r value of .87) 5 . It goes beyond feeling heard – it’s about seeing action. And humility? That’s admitting when leadership gets it wrong, by owning past missteps and using them as learning moments, e.g., “We tried X and it didn’t work—here’s what we’re doing differently.” Employees don’t expect flawless leaders in turbulent times, but they do expect honest ones 1 . The Long Game: Why Trust Matters Now More Than Ever The truth is, once trust is broken, it doesn’t bounce back overnight. But it can be rebuilt—deliberately, consistently, and humanely. So, whether you’re navigating reorgs and layoffs, launching AI, reworking hybrid policies, or redefining values, remember this: Trust isn’t restored through a memo. It’s rebuilt one conversation, one decision, one act of empathy at a time. And in a world that’s changing faster than ever, trusted leadership is a necessity. References 1 Harvard Business Review. (April 28, 2025). Executive Teams Are Losing Stakeholders’ Confidence. Here’s How to Get It Back. 2 Forbes. (April 18, 2025). The Trust Crisis: Why Employees No Longer Believe Their Leaders (And How To Rebuild It. 3 Annual Review of Organizational Psychology and Organizational Behavior. (Volume 6, 2019). Psychological Contracts: Past, Present, and Future. 4 Harvard Business Review. (May 6, 2025). The Workplace Psychological Contract Is Broken. Here’s How to Fix It. 5 The 2025 engagement and attrition key driver refresh and longitudinal analysis determined the top predictors of engagement (across 235 customers) and voluntary attrition based on LinkedIn Glint survey scores in 2022, 2023, and 2025 representing 6.8 million employee survey responses. Engagement: As these data variables are continuous, Pearson's r was used to measure the correlation strength of the linear relationship between People Success “critical needs” (25 survey items that measure employee experiences aligned with the six People Success Elements) and the six engagement outcome items (eSat, Recommend, Manager, Belonging, Retention and Intent to Stay). The r values for each item were aggregated and averaged across all customers for each year reported. To calculate meaningful change from year to year, we examined the delta in r value for each item-outcome pair over the 3-year period. Then, we calculated the correlation percentile splits to determine the top 33 percent (r value YoY deltas from .10 up to .25) and bottom 33% (r value YoY deltas below .05). We comment here only on those items and their outcomes with r value deltas in the top third, noted as “top predictors” or “strong drivers” of the outcome(s) and whether the change is trending up or down. Attrition: Only survey item responses from at least 15 LinkedIn Glint customers who’ve had at least 80 voluntary terminations between survey administrations were included in this study. “Attrition Multipliers” were formed by comparing favorable vs. unfavorable survey responses scores from those voluntary termed employees for each of the People Success “critical needs” items. Aggregate analysis involved averaging the attrition multipliers per item at a customer level, filtered by n size for each of the three years in this longitudinal study. 6 Harvard Business Review. (March 21, 2025). Employees Won’t Trust AI If They Don’t Trust Their Leaders.Insights from our Tech Industry Cohort Kickoff
The tech industry is at a crossroads, facing challenges that demand bold leadership and strategic action. Our Tech Industry Cohort, launched last month, created a space for innovators to tackle these issues head-on and explore the opportunities hidden within the turbulence. Here's what we uncovered in our time together: 🔹 Facing the Pressures Head-On The ripple effects of layoffs continue to test employee trust and morale, leaving organizations striving to rebuild confidence. Geopolitical tensions and trade issues compound this uncertainty, forcing leaders to adapt while navigating rising costs. 🔹 The AI Balancing Act AI adoption represents the industry's greatest opportunity—and challenge. While skill shortages and job disruptions demand immediate attention, the concerns around data ethics underscore the need for thoughtful, transparent implementation. AI is not just a tool; it’s a partnership. Getting it right is how organizations unlock its immense potential while empowering employees to embrace change. 🔹 Seizing Opportunities Through Training Employees are eager to upskill, especially in AI, and organizations that embrace enterprise-wide training programs reap the rewards of better innovation, stronger retention, and increased revenue. Addressing barriers like lack of time, leadership buy-in, and employee confidence is key to creating a culture of growth and resilience. 🔹 Fueling Transformation Through Collaboration HR and IT must work hand-in-hand to drive successful AI integration—open communication, tailored learning programs, and a focus on data protection are critical. Strategies such as AI collaboration groups and appointing AI ambassadors enable employees to lead the charge in adoption. 🔹 Boosting Engagement with AI Agents Recognition matters, and Copilot AI Agents are already helping organizations make it easier for employees to feel valued. Automated recognition systems ensure appreciation is timely and frequent, boosting morale and driving motivation across teams. 🔹 Proving AI’s Worth Demonstrating ROI to leadership isn’t always straightforward, but trusted advisors and clear evidence of outcomes are helping organizations make a compelling case for AI investment. The insights shared in this cohort were a powerful reminder: the tech industry’s challenges are deeply human. Prioritizing transparency, engagement, and empowerment allows organizations to not only adapt but thrive in the face of change. Now Is Your Time Leadership in the tech industry isn’t just about navigating the present—it’s about shaping the future. The Tech Industry Cohort is an invitation to join forces with other trailblazers, dive into actionable strategies, and drive innovation that sets the standard for our field. Don’t miss the chance to be part of this journey, and register for our next session on August 12 th . Let’s innovate, collaborate, and lead the way forward—together!Think like a People Scientist: Leading AI Change with Employee Sentiment
In our latest ‘Think like a People Scientist’ webinar, I was joined by Ryan Lebow, Principal People Scientist, Microsoft, to talk about the topic of measuring employee sentiment with Viva Glint and Viva Pulse during AI transformation. This webinar shared valuable strategies and tools to help organizations navigate the complexities of AI adoption through employee sentiment. Key Takeaways Understanding Change and Sentiment: Ryan kicked off the session with a historical perspective on technological advancements, highlighting the fear and uncertainty that often accompany significant changes. From the invention of the telegraph to the rise of personal computers, these examples underscore the importance of addressing employee sentiment during times of transformation. AI in the Workplace: The discussion then shifted to the present, focusing on AI's impact on the workplace. Ryan shared statistics showing that 75% of employees are already using AI at work, with many bringing their own AI tools. This highlights the urgency for organizations to develop clear strategies for AI implementation and measurement. Measuring AI Sentiment: Ryan emphasized the importance of measuring both the business impact and employee experience of AI. Tools like Viva Glint and Viva Pulse can help organizations gather valuable feedback and insights. These tools enable leaders to understand how AI is affecting productivity, engagement, and overall sentiment. Practical Steps for HR and IT Leaders: The session also provided practical steps for HR leaders to collaborate with IT teams, including scheduling regular meetings, identifying key metrics, and creating collaborative working groups. These strategies are essential for ensuring successful AI implementation and addressing any challenges that arise. To further support your AI measurement journey, we recommend exploring the following resources: Read our ‘Top Ten Tips for Measuring AI Transformation’ Leverage the Playbook for Measuring Copilot Implementation and Impact with Viva Access the slides from the webinar below and share with your colleagues and AI leaders Visit our ‘Think like a People Scientist’ Adoption page for all past and upcoming webinars in this series Thank you for being part of our ‘Think like a People Scientist’ series. We look forward to seeing you at our next event!Research Drop: Unlocking AI Potential for Frontline Workers
Research Drop in Brief: Information workers (IW) and frontline workers (FLW) experience AI transformation at work differently. Though in our sample access to tools is the same, adoption metrics reveal a gap. FLWs face unique challenges in AI adoption, such as ineffective training and uncertainty about how to properly integrate AI into their workflow. Addressing these barriers can unlock the potential of AI to improve working conditions, efficiency, and communication for FLWs. On average, IWs workers are more likely to report optimistic AI sentiment, see the value proposition for organizational investment, and realize the personal benefit of using AI at work. In some industries and departments, this sentiment gap between IWs and FLWs reaches 22%. As we continue to see more and more AI integration in our daily workflows, our ability to recognize its impact on individuals grows. AI use cases are emerging in all job types, and industries and change leaders are focused on optimizing AI investments across the board. Much of the research we see about AI adoption and transformation centers around the Information Worker (IW), typically a salaried employee whose primary responsibilities are conducted sitting at a desk. But what about Frontline Workers (FLW), who are more likely to be deskless and paid hourly? Are FLWs having the same experiences with AI as their IW counterpart? How is their AI journey similar or unique to their deskbound peers? This month’s Research Drop explores the differences between full-time employees who self-report as paid an “annual salary” or an “hourly wage.” For the sake of this blog, we use these classifications as a proxy for IWs and FLWs. We acknowledge this proxy may not be perfect but aim to provide some directional insight into how these groups experience AI at work and what we may have overlooked as stewards of AI transformation. Usage differences exist despite AI access parity One of the first things we look for when comparing two employee groups is their access to AI – are there disparities in what tools and technologies certain employees are provided? Interestingly, we found a less than 1% difference between salaried employees and hourly employees regarding AI access – 61% of salaried employees and 60% of hourly employees report high access to organization-sponsored AI tools. This suggests that from a rollout perspective, both IWs and our FLWs are included as user groups for pilot programs, license rotations, and full-scale implementations. However, we start to see some differences when we look at usage metrics. 61% of salaried employees are high or moderate frequency AI users (use AI at work at least once a week), while only 51% of hourly employees fall into high/moderate use categories. This is our first indicator that there may be some underlying differences in these groups’ AI experiences. A multi-level pattern of falling behind emerges for FLWs At multiple levels of AI transformation (for example, greater workforce impact, organizational impact, and individual impact), we uncovered a pattern. FLWs’ AI sentiments are lower than their IW counterparts. This raises the alarm that current AI transformation strategies are not as effective within the FLW population. Uncertainty at the macro level We found a 10-percentage point difference between hourly and salaried employees on our AI Optimism scale, which includes items such as believing that AI transforms work for the better and that AI is built to benefit employees. When employees are not excited and hopeful for an AI-future, these worries will negatively impact their experience with AI and reduce the likelihood of successful AI integration. Where everyone is using AI at work and is inspired by success stories and innovative use cases, IWs are more likely to agree with positive, future-forward sentiments about AI. While still optimistic (the favorability score for the AI Optimism scale for hourly employees was 59%), these FLWs may be slightly more apprehensive when it comes to AI at work. In some industries where AI transformation is more aligned with automation than augmentation, FLWs might have concerns about the long-term vision for their roles. From a macroeconomic perspective, however, while some people may think that AI automation is replacing FLW jobs, we actually see that FLW jobs are growing in number. The World Economic Forum reported that frontline jobs are set to increase significantly in the coming years. Roles in industries like farming, delivery, and construction are expected to grow the most, along with positions in healthcare and education. This trend highlights the ongoing demand for these essential roles, even as technology evolves 1 . Whereas IWs may be more inclined to see AI as a tool that enhances productivity and opens doors to innovation, FLWs may need more direct support in mitigating concerns around job replacement to feel optimistic. When connecting the dots gets blurry We found an 8-percentage point difference between hourly and salaried employees on our Organizational Value of AI scale. This includes items such as believing AI is critical for organizational success and is worth the investment. Again, FLWs are behind IWs in seeing the full vision for enterprise-wide AI and the impact it could have. The gap is slightly smaller in this instance, suggesting that FLWs are slightly more likely to see the benefit for their organization than they are to see AI being beneficial for themselves. Employees’ understanding of the organizational benefits of AI may be impacted by how well their organization translates the enterprise-wide transformational strategy. Internal communication for FLWs regarding strategy and vision is challenging to ensure, as their work is often shift-based or dispersed; consistent access to technology is limited. Organizations need to be intentional in how and when they share company-wide communications, making sure that the goals and benefits of technology rollouts meet their people where they are in their workday and workplace. Additionally, empowering FLWs to co-build the vision of AI transformation may help them translate their experience being on the frontline directly to the goals and desired benefits of AI for both their organization and themselves. Challenges in capturing personal impact We found a 10-percentage point difference between hourly and salaried employees on our Realized Individual Value of AI (RIVA) scale. This includes items such as reducing work-related stress and speeding up task completion. Even beyond seeing the vision for company strategy, seeing the vision for personal productivity and impact is critical to adoption. Change leaders seek to justify the ROI of AI investments, and enthusiastic employee voices are vital to achieving this goal – but FLWs in our sample are not yet reaping the benefits that IWs are. The more benefits one sees of making a behavioral change at work (for instance, using AI), the more likely they are to continue that behavior. Not seeing as many benefits as IWs puts FLWs at risk to have lower adoption levels. Microsoft internal research shows that AI mastery requires time and practice, where employees see 20-30% higher sentiment related to learning, thriving, and productivity when Copilot usage is 6 months, compared to 3 months 2 . FLWs may need extra support to ramp up to the sustained use necessary to build AI proficiency that results in strong value. It can be helpful to surface high value scenarios for this employee group to capitalize on AI value immediately, as their time is limited and dedicated time for upskilling is scarce. The moment to capitalize on frontline AI-human collaboration is now Research shows that when AI for FLWs is done right, it acts as a critical resource for these employees 3 . AI has the potential to impact frontline work by improving working conditions, accelerating efficiency, and supporting on-the-move tasks that require high levels of operational coordination. AI can improve internal content generation and distribution for company-wide communication by getting to “the right people at the right time via the right channel” 3 . Consider how to be more intentional with the expectations for FLWs’ AI experience. It is unlikely that the goal for FLWs is to become “super users” – but rather to support their workload and augment their experience. Knowing when to integrate AI tools and how to optimize what’s available is a challenge for FLWs. The top barriers for their AI adoption are lack of time to understand the tools, ineffective training, and uncertainty around when to use the tools 4 . This results in scattered usage and value add. More than half of FLWs have had to quickly adapt to using digital tools without any prior training or preparation 5 . To truly unlock the potential of AI for frontline workers, it's crucial to tackle challenges like training gaps and tool accessibility with focus and care. Practical steps to engage and equip your frontline workers for AI transformation As we think about how to shore up the gaps that exist between information workers and frontline workers in terms of their AI experience, it’s important to remember that we consistently see that AI adoption is not one-size-fits-all. Various external and internal factors influence each employee's likelihood of adopting and recognizing value from integrating AI into their workflow. At a high level, based on varied tasks and goals, each industry and department will likely differ in how it approaches AI transformation. Industries and departments with larger FLW populations need to be strategic in how they invest and roll out their AI technologies to both employee groups. Bring FLWs into the process early and seek their feedback to better understand the needs of FLWs. What pain points are they having? Where can AI be best deployed to alleviate barriers and expedite processes? Bringing them into the transformation process can also help crystallize the impact AI can have on the business, as FLWs are likely a direct channel to customer needs and opportunities. Create opportunities where FLWs can provide feedback, such as deploying surveys via mobile devices, ensuring all shift schedules are represented, setting up kiosks and QR codes in common areas, or setting aside time during weekly huddles to seek feedback. Empower FLWs to be a critical part of the evolution of their roles/teams. By soliciting their input, changes can be made that scale to similar roles across the organization. Encourage FLWs to upskill on the components of AI that excite them and which directly improves their day-to-day, whether through AI taking a larger share of the logistic load or through an AI-powered communication system. To make the most of AI for FLWs, companies need to tackle issues like training gaps and tool accessibility, while figuring out tailored ways to roll out AI solutions. By getting employees involved early on and focusing on their specific needs, businesses can create smarter workflows and an improved work experience for everyone. Stay tuned for our June Research Drop to keep up with what the Microsoft People Science team is learning! This month’s Research Drop analyzed 1,800 global employees (1,022 salaried employees, 778 hourly employees) from the Microsoft People Science AI Readiness Survey from April 2024. Note: participants were asked to respond to questions around “generative artificial intelligence” which has been shortened to “AI” for the sake of this blog. 1 World Economic Forum. (January 2025). Future of Jobs Report 2025. 2 Analysis conducted by Microsoft HR Business Insights team on internal Microsoft Copilot users. 3 Forbes. (April 25, 2025). AI: The Frontline Jobs Revolution You Didn't See Coming. 4 BCG. (June 26, 2024). AI at Work 2024: Friend and Foe. 5 Microsoft WorkLab. (January 12, 2022). Technology Can Help Unlock a New Future for Frontline Workers. 6 Accenture. (March 10, 2025). Gen AI amplified: Scaling productivity for healthcare providers. 7 McKinsey and Company. (January 28, 2025). Superagency in the workplace: Empowering people to unlock AI's full potential. 8 Gartner. (March 5, 2025). Gartner Predicts Agentic AI Will Autonomously Resolve 80% of Common Customer Service Issues Without Human Intervention by 2029. 9 Salesforce. (January 7, 2025). AI Education: How to Reskill Your Team for the Future of Customer Experience.How important is belonging to your organization?
Microsoft People Science provides customers with the latest research on the modern workplace, helping them navigate changes that may impact the workforce such as technological advancements, economic instability, and societal shifts. For many organizations, DEI (diversity, equity, and inclusion) is a key focus area. Research shows that fostering a sense of belonging and good treatment at work significantly impacts employee engagement and financial success. Evidence-based decision-making is a good way to guide any programmatic adjustments to DEI practices that affect employees. Start by collecting and acting on employee feedback and let facts be your guide. Staying up with the changes With technological advancements like AI transforming work, economic instability reshaping markets and impacting labor and growth, demographic shifts challenging workforce stability, and work models and expectations constantly evolving, organizations often struggle to figure out how to adapt while keeping employee engagement and productivity at the forefront. The Microsoft People Science team strives to address the big questions and concerns our customers face by providing straightforward, researched-backed information to help them navigate turbulence and make informed decisions. With 85% of companies reporting having dedicated DEI budgets 1 , deciding how to move forward with DEI is a business decision many companies face. The Microsoft People Science team has been researching modern workplace practices (like DEI) for over a decade and has data that can help guide customers. Based on over 350 million data points (collected between 2020 and 2023) and extensive research on psychology and workplace behavior, we examined how employees stay motivated at work, despite the tumultuous changes during that time period. This study resulted in the People Success Elements 5 , a model for understanding what contributes most significantly to employee happiness and success. This framework helps Microsoft Viva Glint offer out-of-the-box employee surveys focused on what matters most to people to be their best and do their best at work. Three of these elements in particular – Empowerment, Connection, and Wellbeing – are based on trust, and call out for a positive work environment that is open and welcoming, where workers feel valued, respected, appreciated, and treated with fairness and care. This kind of environment is more prevalent in companies that place an emphasis on people-centric policies, management practices, and employee programs. People Science Insights In 2023, we noticed a market shift among our customers towards a focus on achieving high performance, resulting in our High Performance Organization (HPO) eBook 6 . Our customers were certainly still concerned with creating an “engaged” workforce, but many of them wanted to establish a culture that would drive individual productivity and team performance as well. To help determine the workplace conditions that predicted financial performance (as measured by 35 financial success indicators), we studied various workplace factors across 220 customers that best differentiated company performance 7 . This study resulted in the following Top 15 list: Significantly, employees’ sense of belonging is the top predictor of financial success. It predicts five out of six top financial indicators 7 . And our latest engagement driver analysis showed that across all 400+ engagement survey topics, belonging has the strongest correlation with happiness at work. No wonder the belonging question is so popular – it is used by over 70% of Glint customers 8 . Fostering a culture where people feel a strong sense of belonging helps organizations achieve higher levels of employee engagement, commitment, and greater financial success. A more committed and dedicated workforce increases retention, thus paving the way to greater efficiency as measured by net income over workforce size. Belonging is a huge win-win for the employee and the business. A sense of belonging is only possible if people feel well-treated at work. In the Top 15 table we see several other related top drivers of business success that describe important treatment factors like feeling free to speak one’s mind, being a valued member of the team, and being able to be oneself at work. In a recent study on survey question utilization trends across Glint customers 10 , the Speak My Mind item (currently used by 23% of Glint customers) was identified as a key opportunity to increase engagement and performance because it gets at a component of psychological safety, which has a positive impact on turnover, stress, and productivity (For more, view our recent webinar on Building Psychological Safety 11 ). In sum, this data shows how someone is treated at work in terms of feeling they belong, feeling valued and respected for who they are, and being able to speak freely about what concerns them is critically important to employee happiness and success and company performance. Let the evidence decide your next steps Here are some Microsoft People Science best practice methods you can use to examine your own workforce attitudes and opinions about DEI: Align: As with all changes that impact your workforce, reconnecting to your organizational strategy and checking in with employees can help teams chart the best course forward. A great way to do that is through seeking and acting on survey feedback. Collect: Leverage existing surveys and listening channels to involve employees during times of change. The goal is to understand how your employees feel about their work environment and treatment. Listen: Consider hosting live focus groups and dialogue sessions to allow people to share their ideas and concerns. Acknowledge what you’ve heard and any plans to follow up. Assess: Based on the feedback you’ve gathered, assess how similar or divergent attitudes are across your workforce and how they align with your company stance or position on the change’s topic(s). This insight may help you think through your next steps. The Microsoft Viva measurement apps (Glint, Pulse, and Insights) are an ideal way to assess the impact of large-scale changes to your organizational strategy and what helps employees perform at their best. Glint and Pulse provide out-of-the-box surveys and questions that assess how people feel they are being treated and the extent to which that treatment is impacting their sense of belonging, happiness, productivity, and success at work. Collecting and acting on employee feedback is crucial for guiding programmatic adjustments that affect your workplace. Our research shows that fostering a sense of belonging and good treatment at work significantly impacts employee engagement and commitment. Companies that prioritize people-centric policies and create a positive work environment see higher levels of productivity, retention, and financial success. Microsoft People Science Microsoft People Science is a research-backed and people-centric approach to the study and practice of happiness and success at work. People Science prides itself on providing customers with the latest research and findings about the modern workplace. We serve customers across a wide spectrum of industries, geographies, and company cultures, and remain open to all customer orientations on any given topic, current event, or public discourse that may be impacting their strategies and choices. References 1 Workday. (February 6, 2024). Workday DEI Landscape Report: Business Leaders Remain Committed in 2024. 2 MIT Sloan. (November 7, 2024). How Integrating DEI Into Strategy Lifts Performance. 3 Harvard Business Review. (December 13, 2024). Continuing the Work of DEI, No Matter What Your Company Calls It. 4 Pew Research Center. (November 19, 2024). Views of DEI have become slightly more negative among U.S. workers. 5 Viva Glint Blog. (April 20, 2023). The Elements of People Success. Six Microsoft People Science. (2023). Redefining High Performance in the New Era of Work. 7 This research draws from employee survey responses from 220+ customers, collected from the year prior to October 1, 2023. 132 survey questions covering the entire ranges of People Success factors were utilized in various tests (e.g., multiple regression) to validate their impact on talent outcomes (engagement, attrition, performance) and business outcomes (35 financial metrics, e.g., stock return, market cap per employee, etc.) 8 This analysis examined LinkedIn Glint customer item utilization between September 2023 to August 2024 (n = 728 customers). 9 American Psychological Association. (2023). 2023 Work in America Survey: Workplaces as engines of psychological health and well-being. 10 Viva Glint Blog. (December 18, 2024). Research Drop: What Organizations Ask in Employee Surveys (Plus Three Untapped Opportunities for 2025). 11 Microsoft Viva Blog. (November 15, 2024). 3 Steps to Build Psychological Safety on Your Team.Research Drop: Investing in Training Opportunities to Close the AI Skills Gap
Research Drop in Brief: 39% of workers' existing skillsets will become transformed or outdated over the next five years, emphasizing the need for organizations to keep up with skill demands. Despite the rise in AI use, 70% of organizations report struggling to equip their workforces with the necessary AI skills, and 62% of leaders believe their organization has an AI literacy skill gap. When employees feel adequately trained in AI, they are 1.9x as likely to report realizing the value of AI, such as improved decision making. To close the gap, organizations need to focus on providing equitable access to training opportunities and helping their employees dedicate time for upskilling and continuous learning. With rapid workplace changes, 39% of workers’ existing skillsets will become transformed or outdated over the next five years 1 , making it imperative for organizations to keep up with the demands of this revolutionary workforce change. One of the significant macrotrends impacting work is the introduction of generative AI to the workplace, such as Microsoft Copilot. The integration of AI tools and technologies continues to grow across industries and roles, directly altering the way employees across the planet execute their daily tasks. Three in four organizations (77%) are planning to reskill/upskill their workforce in the next five years in order to better work alongside AI 1 . Leaders acknowledge that equipping employees with the skills they need to fully optimize AI at work can be tricky – 31% of leaders report a main barrier to reskilling/upskilling their workforce is not knowing where to start with data and AI training 2 , which can cause lag in scaled organizational development. And we see consistently that employees’ excitement for AI at work outpaces the ability for their organizations to roll out organization-sponsored AI tools 3 , which can lead to inconsistent adoption and misaligned AI usage. For this reason, now is the time for organizations to invest in enterprise-wide AI training and learning opportunities. This month’s research drop explores the current AI skill gap, the impact of AI-specific training, and strategies for organizations to better equip their employees to succeed in the era of AI. The reality of the AI skill gap The AI skills gap is increasingly prevalent – 70% of organizations report struggling to equip their workforces with the skills they need for future success 4 , 62% of leaders report their organization has an AI literacy skill gap 2 , and 39% of CEOs report low levels of confidence about their employees having the right skills to fully maximize AI benefits 5 . The demands of leading through AI transformation can feel overwhelming, involving high-effort experimentation and comprehensive organizational strategies for deployment. The pace of change in the current workplace continues to be faster than ever, with employees simultaneously feeling the challenge of keeping up and excitedly leaning in to experiment with AI before their organization officially adopts. Leaders are in a difficult situation of needing to support employees encompassing a wide variety of stages in their AI journey. And employees are craving more opportunities to learn. Nearly half of employees feel they are receiving moderate or less support for AI capacity building at their organization 6 , which can directly impact their ability to dedicate time for learning and upskilling. A strong organizational investment in training and learning opportunities is needed to help bridge the gap. Differentiating value of AI-specific training 48% of employees rank training as the most important factor for AI adoption 6 . And for good reason – at organizations with enterprise-wide data and AI literacy programs, the results are striking. Within these organizations, 90% report faster decision-making, 81% report increased revenue, and 81% report better employee retention 2 . Training is a key input to the adoption and usage of AI. We found that while 43% of employees who feel adequately trained are high frequency users of AI (at least once per day), less than 1% of employees who don’t feel adequately trained are high frequency users of AI. This means nearly no one fully adopts what they don’t feel equipped to use, and employees missing that foundational training may not be trying or leveraging AI at all. We’ve seen in previous research that upskilling can improve confidence, encourages play and experimentation, and drives behavior changes, further underscoring that adequate training is a key ingredient in driving AI use, adoption, and ultimately, transformation. Training also impacts employees’ conviction in their future in an AI-first organization. Employees who feel adequately trained in AI are more likely to agree that they have irreplaceable skills (79%), compared to employees who don’t feel adequately trained (68%). When employees are confident and comfortable with AI technology, they better see the vision for how they can collaborate with AI, rather than compete with it. And once employees are trained and leveraging AI, they also become more likely to realize the benefits of using AI at work. In our data, we see that employees who feel adequately trained in AI are 1.9x as likely to report realized individual value of AI (RIVA) outcomes. Our RIVA scale includes positive AI outcomes such as employees reporting reduced stress, better decision making, and higher quality work output. These outcomes are critical to not only fully maximizing and seeing the ROI of AI at work, but also to reinforce the utilization of AI to complete daily work tasks. The lagging state of organization-wide AI-specific training programs Unfortunately, although we see the benefits training can bring, training opportunities can be hard to come by. One report shows that only 49% of employees have received training in AI and that 57% of employees report feeling “behind” in keeping up with AI 7 . Employees worry that this might negatively impact their organization’s future – 1 in 3 employees report that a lack of AI-specific training is the biggest barrier to their workforce being prepared to leverage AI 4 . So, what’s going on? In our dataset, two main obstacles to training confidence emerged: accessibility of training and capacity to engage in training. Accessibility of training As many organizations are still in the planning and early implementation stages of AI, their training programs are as well. Many employees report that training feels exclusive to certain organizational groups. Only 16% of employees report that their organization offers enterprise-wide AI training, while 77% report that their organization either offers no training or only offers it to a selective group of employees 4 . Some of this may be aligned with pilot programs in the early stages of AI transformation, where training might be limited to those with early access licenses. These trainings may also be limited to groups the organization have selected due to their outspoken excitement, hand raising, or opt-in processes. When organizations take a proactive approach to providing AI tools to their employees, employees are far more likely to feel equipped to use them. We found 80% of employees with high access to company-provided AI tools agree that they are adequately trained in AI, compared to just 60% of those with low access to company-provided AI tools who are left to navigate AI on their own – a 20-percentage point difference. The groups most likely to be given access are those teams that are more likely to be closely involved in the AI transformation initiatives. In our dataset, the departments with the highest access were Product Development and IT. While it is important that those directly involved in the transformation strategy have tool and training access, the rest of the organization may feel left out and fall behind, resulting in a lack of cross-functional use cases and deepened skills gaps throughout your organization. Capacity to engage in training It’s not only the accessibility of training that impacts whether an employee feels skilled in AI, however. There are individual restrictions that may hinder upskilling opportunities. A key blocker can be that training takes time. For an employee to engage in training, they need to have the capacity to dedicate work hours to participate, to expend focus time on learning, and to commit to experimentation to practice the learnings. When an employee’s workload is too high, or their leader doesn’t support dedicated learning time, they may not benefit from available training. We also find that employee burnout had a direct impact on training confidence. When burnout is high, training confidence plummets. While 83% of employees with no burnout indicators feel adequately trained, that number drops to 55% for employees that have three or more burnout indicators – an almost 30-percentage point difference. Burnout indicators include overwhelming workload, little or no support from managers/peers, and unclear job responsibilities. Employee burnout is a sign that something needs to be addressed in the workplace to best set employees up to be happy and successful. Employees who feel burnt out have a hard time feeling prepared and trained to integrate AI into their work. If you know your organization already struggles with burnout or dedicating time for learning, consider how you can work AI training into role or function-specific time. When leveraged properly, AI can reduce burnout by reducing time spent on tasks or by helping employees make informed decisions. If an employee is already burned out, they don’t have the capacity to attend training or to learn and that generates a negative feedback loop. Therefore, it’s important for organizations to understand that it’s not only about providing training opportunities that lead to upskilling/reskilling but also supporting employees who want to invest their time and capacity to engage in the training. Strategies for organization-driven AI upskilling/reskilling Employees are craving training opportunities to help them close the AI skills gap, so how can organizations be better equipped to meet this need? Our research shows that organizations can help employees “future-proof” themselves by ensuring equitable access to training and by helping employees invest in training opportunities. If the goal of your organization is enterprise-wide AI adoption, then training also needs to be scaled throughout the organization, whether through network-based sharing or democratized access to training resources. Consider where you may have gaps in developmental opportunities or accessibility of learning. Are there departments who haven’t been provided with training yet? Some employees may even be unaware of what opportunities are open to them. Focus on clear company communications that share the location and availability of training, learning paths, and skill-building sessions. While some employees may proactively look for these opportunities, others may need more direct instructions on how to upskill themselves. It's also helpful to brainstorm scalable strategies for training. For example, can you leverage AI champs to conduct training? Perhaps they can help create a “training-in-a box” kit which can be adapted by function or region to leverage the learning communities that already exist in your organizational network. AI-specific training should slot into your continuous learning strategies, where an emphasis on cross-team sharing, learning, and experimentation helps your workforce keep up with the pace of change. Employees also need leadership and managerial support to engage in training. Workloads can be high and bandwidths tight, so employees may not feel as though they have the capacity to focus on learning. Consider a monthly calendar hold for your team to dedicate the time to engage in learning. Include training or structured L&D programming as a team-wide goal to measure for the quarter, raising its importance to that of other team outputs. Employees need to feel safe and supported to prioritize their development and are likely to look to their leaders to model this behavior. This can also be a key moment where leaders can help connect the dots between individual roles and organizational strategy, further helping employees to invest in the vision and future of AI at your organization. To conclude, organizations should deeply invest in AI training opportunities and support employees in dedicating time to upskill. By promoting continuous learning and addressing factors such as burnout, companies can prepare their workforce for the future. A well-trained and supported team is essential for successful AI transformation. Stay tuned for our May Research Drop to keep up with what the Microsoft People Science team is learning! This month’s research drop analyzed 1,800 global employees from the Microsoft People Science AI Readiness Survey from April 2024. Note: participants were asked to respond to questions around “generative artificial intelligence” which has been shortened to “AI” for the sake of this blog. 1 World Economic Forum. (January 2025). Future of Jobs Report 2025. 2 Datacamp. (2024). The State of Data & AI Literary Report 2024. 3 Microsoft People Science. (April 2024). The State of AI Change Readiness. 4 i4cp. (2025). Workforce Readiness in the Era of AI. 5 ADP. (2025). Unveiling the Next Anything: Navigating new frontiers in talent, compliance and technology. 6 McKinsey & Company. (January 28, 2025). Superagency in the workplace: Empowering people to unlick AI's full potential. 7 American Management Association. (March 19, 2025). Organizations Make Progress Adopting AI, but Many Employees Feel Left Behind.Think like a People Scientist: Bridging HR & IT for AI Success
“IT brings the tech, HR brings the people.” This was a memorable takeaway from last month’s Research Drop on HR & IT collaboration in driving successful AI transformation. In our most recent ‘Think like a People Scientist’ webinar, we dove deeper into this idea and explored how, and why, HR and IT teams should be working closely together when it comes to driving AI transformation. In this webinar, Dr. Julie Morris, Program Manager in the People Science R&D team was joined by Dr. Megan Benzing, Senior People Scientist at Microsoft, and Craig Foster, Director of HR Digital Transformation at Microsoft. To kick of the session, we asked the audience which team(s) are currently leading the AI strategy in their organizations. Not surprisingly, over 50% reported that it was their IT team but 35% also felt that HR was one team that should be involved from across the organization. Some of the reasons given for this more collaborative approach included people-centricity, enhancing adoption and promotion of AI, and change management integration. Despite the general awareness that HR has a key role to play in AI transformation, our research uncovered some of the challenges that are facing HR when it comes to AI. During the webinar Dr. Megan talked about the lack of access to AI for HR teams and the impact that this can have on realized value, not only from HR employees but leaders too. You can read more about this research here. To bring a real-world example to the audience, Craig Foster shared insights from Microsoft's own journey in building the Employee Self-Service agent and digital transformation. He discussed how HR and IT teams at Microsoft have worked together to create a seamless experience for employees, leveraging AI to enhance productivity and engagement. Here are some key learnings from Craig’s experience: Integration of HR and IT: Successful implementation of the Employee Self Service (ESS) tool requires close collaboration between HR and IT teams to ensure both technical and human-centric aspects are addressed. Employee Experience: Focusing on enhancing the employee experience is crucial. This involves creating seamless and intuitive self-service tools that empower employees and improve productivity. Data Security: Ensuring the security and privacy of employee data is a top priority. This involves implementing robust security measures and addressing employee concerns about data protection. Change Management: Effective change management strategies are essential to facilitate the adoption of new technologies and processes. This includes providing training and support to employees to help them adapt to the changes. Continuous Improvement: The ESS journey is ongoing, with continuous improvements and iterations based on employee feedback and evolving needs. To further explore insights from this webinar and learn how to navigate AI transformation in your organization, we invite you to: Read our Research Drop: Investing in HR & IT Collaboration to Drive Successful AI Transformation Access the slides from the webinar below and share with your colleagues and AI leaders Join our next ‘Think like a People Scientist’ webinar on May 6 where we will discuss how you can lead AI change with employee sentiment Thank you for being part of our ‘Think like a People Scientist’ series. We look forward to seeing you at our next event!
People Science Researchers Reflect on SIOP 2025 Learnings
Last week several of our team members attended the 2025 Society for Industrial and Organizational Psychology (SIOP) annual conference in Denver, Colorado. This marquee event in our field brings together industry leaders, practitioners, and academic professionals to discuss, learn, and share on the most important topics. This year we heard a lot about building AI with “humans in the loop,” agents disrupting employee experience workflows such as hiring and skills-based learning, and the future of employee listening. The Microsoft People Science led several sessions and participated in panels on topics related to agents at work, the future of nudge interventions, and manager action taking. Our sessions were packed with attendees, and we also hosted a customer networking event focused on how to measure AI’s impact on the employee experience. We had an energizing and productive time at the conference, and we look forward to applying many of the ideas into our work. Our team is buzzing about all that they learned: Building AI with a human in the loop AI will reinvent the workplace, and we should welcome it rather than run from it so that we can develop it with proper guardrails and ensure it enhances engagement and productivity, fosters innovation, and maintains ethical standards. By embracing AI and establishing ourselves as the “human in the loop”, we can leverage AI’s potential to streamline processes, improve decision-making, and create a more dynamic and efficient work environment. Being the "human in the loop" means taking an active role in leveraging AI to enhance the workplace. It involves thoughtfully considering how AI can assist in hiring the right candidates, fostering career development, and helping individuals find meaningful and fulfilling work. Additionally, it includes identifying areas where AI can be applied to tasks that are rule-based, routine, and repeatable, while pushing the boundaries for what the future may entail, ensuring that these processes are optimized to reduce bias and improve reliability. This plays to our strengths as People Scientists. Jaime Gonzales, Principal People Science Manager AI coaching will help scale support at work, but empathy remains uniquely human Using AI for employee coaching is likely to significantly scale (and in many cases enhance) coaching experiences globally, particularly for employees who do not normally have access to great coaching on-the-job (e.g., front-line employees, deployed soldiers). Aspects of coaching like career plan development, performance appraisal, feedback, and collaborative ideation are all likely to benefit from the development of AI solutions in the coaching space. Further, AI can help managers identify skill gaps on their teams, suggest relevant training programs, and offer tailored career advice, better fostering employee growth and development and actually enriching the leadership of a manager. One aspect of coaching that the consensus suggested would remain uniquely human is the support that managers provide employees in moments of great need, vulnerability, and struggle. In these moments, the perception is that AI is likely to lack the nuanced understanding required in situations that demand empathy and direct human connection (those moments when an employee needs to know that their manager is standing beside them). The thinking goes that even if AI developed an improved capacity to understand and act with empathy, that the current workforce would not feel as supported and satisfied if the desired support were not coming from another person. Thus, while AI will likely augment several managerial tasks, it cannot (yet) substitute the profound importance of human empathy in some high-need and emotional work situations. Eric Knudsen, Principal Manager, People Science Analytics The data sources are expanding, but action continues to be the ‘why’ While there were more sessions than ever about different types of data collection methods and the use of passive data + AI analysis, the problem we are trying to solve has largely stayed the same: driving action. The growing interest in passive data collection methods and non-sentiment data are driven by better access than in years past and a desire from leaders to lighten the load on employees needing to provide their input via traditional surveys. These expanded approaches offer valuable insights, but it is crucial to remember that they are most valuable when they help leaders and managers make better, more informed decisions about how to best serve their people. While passive data may be held closer to HR and other groups who may own the data, those most insightful data points need to be shared back to the people within the organization (leaders, managers, and individual contributors!), ensuring that the insights lead to tangible improvements in their experiences and performance. Carolyn Kalafut, Principal People Scientist In uncertain times, we lean on psychological safety to help us adapt and be resilient When everything around us is changing rapidly, psychological safety becomes increasingly critical. Among all the varied session topics at SIOP (e.g., AI, skilling, listening), psychological safety was present throughout. It truly underscored that speaking up, asking questions, and being authentic are key to navigating the spectrum of workplace changes we are currently navigating. When our leaders and cultures create safe environments, it demonstrates a commitment to people-centric change and acts as a lighthouse to guide us through. Presenters discussed creating spaces where training can thrive through vulnerability, where employees are comfortable with providing honest feedback, and where experimenting with AI and agents is celebrated. By leading with psychological safety, we ensure that change is not just about adapting but also about thriving, resilience, and meaning. Megan Benzing, Senior People Scientist At a Turning Point: AI, Work, and the Role We Must Play At this year’s SIOP conference, the conversation around AI took a meaningful step forward, and the momentum is only growing. Rather than chasing trends, discussions focused on how AI is reshaping work and the role we must play in that transformation. The message was clear: our responsibility is not just to analyze this transformation, but to help build it. Three key themes emerged for me across the sessions I attended. First, grounding efforts in familiar frameworks and well-established paradigms such as the Technology Acceptance Model or principles of social learning can help bring clarity and structure to adoption strategies. It doesn't have to feel like you are starting from scratch. Second, start small, and start now. Use AI in everyday workflows, identify a couple of use cases, test, and iterate. We heard great examples from job analysis to item creation and automated dashboards, by starting with breadth rather than depth you can help identify where deeper investments will have the most impact. Third, we need to evolve our skillsets. That means understanding how AI systems work, collaborating more closely with IT, product and design, and developing solutions that scale. We have a critical role to play in shaping AI at work, so it is ethical, effective, and truly human-centered. Caribay Garcia, Principal People Science Manager
