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 1,000+ customers, collected from January 1, 2022, to December 31, 2022. Eleven outcome items (including Belonging) were utilized in various tests (e.g., multiple regression) to validate their impact on talent outcomes (e.g., attrition, performance) and business outcomes (e.g., stock return, market cap per employee) 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 ManagerBring stakeholders together with the Communications Track at the Microsoft 365 Community Conference
The Microsoft 365 Community Conference is the ultimate Microsoft 365 community event—and the perfect place to expand your skills and knowledge in Microsoft 365 and AI. You’ll learn directly from over 160 Microsoft product leaders, and gain access to more than 200 sessions, including keynotes, workshops, breakouts, and hands-on demos. This year we’re bringing you all-new content and sessions to help you transform the way you work—and maximize your impact with the tools you use every day. Communications sessions Discover new ways to modernize communications, engage employees, and foster a strong organizational culture with Microsoft tools. Gain practical guidance, inspiration from experts, and real-world examples from peers across industries. Speakers John Cirone | Senior Director, Global Employee and Executive Communications Murali Sitaram | Corporate Vice President, Viva Engage Dan Holme | Principal Group Product Manager, Viva Engage Amy Morris | Director, Global Employee and Executive Communications Sessions What's New and What’s Next for Microsoft Viva Communications and Communities with Murali Sitaram, Kripal Kavi, and Jason Mayans GEEC Out Part 1: Insights and Strategies for Global Executive and Employee Communications at Microsoft with John Cirone and Amy Morris GEEC Out Part 2: An Insider’s View of Communications, Change, and Culture at Microsoft with Amy Morris and John Cirone Reimagining Communications and Employee Engagement in the Age of AI with Michael Holste, Venkat Ayyadevara, and Jason Mayans Closing the Loop: Acting Effectively on Employee Feedback with Mark Straetmans and Alisa Liddle Viva Communications and Communities Administration, Moderation, Security, and Compliance with Sandra Martinez Vargas Viva Connections: Building an Employee App for Your Organization with SharePoint and Viva with Tejas Mehta and DC Padur Unlocking Enterprise Knowledge with AI and Copilot with Christina Ferancik Learn more See all Communications Track sessions.6 Insights from the Microsoft & Josh Bersin Webinar: Employee Experience in the AI Era
Our recent webinar hosted by Microsoft and Josh Bersin, ”The Employee Experience Platform Evolves in the Era of AI,” brought together industry experts including Josh Bersin, CEO and Global Industry Analyst from The Josh Bersin Company; Kathi Enderes, SVP and Global Industry Analyst from The Josh Bersin Company; and Prerna Ajmera, GM of HR Digital Strategy and Innovation from Microsoft. With business leaders seeking to enhance productivity, engagement, and well-being, AI-powered solutions are reshaping how organizations support their workforce. Here are six key insights from the event that highlight the evolving landscape of employee experience in the AI era. Watch the Microsoft & Josh Bersin Webinar: The Employee Experience Platform Evolves in the Era of AI 1. The Super Worker Effect One of the most compelling insights from the event that the Bersin team shared was the concept of the "Super Worker Effect. This idea emphasizes that the most significant factor in AI adoption is not the technology itself but workforce readiness. AI has the potential to transform employees into "super workers" by amplifying their capabilities, enhancing productivity, and enabling more meaningful work. Organizations must focus on preparing their workforce to leverage AI effectively, ensuring that employees can harness the full potential of these advanced tools. 2. The Role of the Employee Experience Platform The employee experience platform (EXP) plays a crucial role in the AI transformation journey. With the advent of generative AI, the role of EXPs like Microsoft Viva is evolving. The Bersin team shared that these platforms are becoming more personalized, streamlined, and impactful, interfacing with employees, contractors, and managers in natural language. This personalization enhances communication, skill-building, and overall employee engagement, making the EXP an indispensable tool in the modern workplace. 3. Change Agility in AI Transformation Traditional change management approaches are no longer sufficient in the rapidly evolving AI landscape. As Kathi Enderes from the Josh Bersin Company emphasized, there’s a need for "change agility," a dynamic approach to managing change that focuses on continuous adaptation and growth. Unlike static change management, change agility involves iterative processes, bottom-up transformation, and a growth mindset. The EXP can support this by facilitating communication, tracking goals, and providing ongoing training and support. 4. HR's Leadership Role in AI Transformation HR departments have a pivotal role in leading AI transformation within organizations. Drawing on real-world insights from Prerna Ajmera and Microsoft’s own journey, as AI reshapes the workforce, HR must take on a leadership role in ensuring workforce readiness, driving change agility, and fostering a culture of continuous learning. HR professionals need to work collaboratively across the enterprise, partnering with IT, legal, and operations to implement AI tools and redesign job practices. This leadership is essential for creating a supportive environment where employees can thrive in the AI era. 5. Personalized Learning and Development (L&D) Effective communication and personalization are key to successful AI transformation. Prerna Ajmera suggests that using EXPs to tailor communication and create personalized employee journeys is crucial. By leveraging AI, organizations can deliver the right information to the right people at the right time, enhancing engagement and satisfaction. Additionally, fostering a culture of experimentation and sharing success stories can build positive momentum for AI adoption. Ajmera also highlighted how AI is revolutionizing learning and development strategies by analyzing skills, recommending tailored courses, and creating individualized development paths, aligning employee growth with organizational objectives. 6. Microsoft’s Approach to Building AI-Enabled HR Experiences Microsoft's approach to building AI-enabled HR experiences is comprehensive and multifaceted. The company focuses on responsible AI principles, connecting solutions with M365 and Viva, and leveraging AI-enabled tools like Employee Self-Service Agent to enhance employee experience and improve HR processes. Microsoft's strategy involves breaking down silos within HR, fostering a culture of continuous learning, and ensuring that AI tools are accessible and beneficial to all employees. Conclusion Microsoft & Josh Bersin provided valuable insights into how AI is not just a technological update-it is transforming how organizations engage, develop, and support their people. By leveraging AI-driven EX platforms, companies can foster a more agile, skilled, and satisfied workforce, positioning themselves for success in the evolving world of work. For more insights: Access the full report by HR technology leader Josh Bersin, in collaboration with Microsoft: “The Employee Experience Platform Evolves in the Era of AI.” Read our blog on how we’re using the Employee Self-Service Agent Join us for our April webinar in the Viva Community: Think Like a People Scientist: Bridge HR and IT for AI SuccessThink like a People Scientist: Influencing action without authority
On April 23rd, the Viva People Science team hosted the third webinar in the 'Think like a People Scientist' series. The topic was how to influence internal stakeholders without formal authority, including executives, HR colleagues, managers, and employees.
Microsoft Viva + Copilot newsletter: March 2025
Welcome to the March 2025 edition of our Microsoft Viva newsletter, now with an exciting new focus as we continue to evolve and enhance our suite of tools to help organizations with employee experience and AI transformation. (Not familiar with Microsoft 365 Copilot? Sign up for a free trial here!) This newsletter will be delivered several times per year and will include customer success stories, invitations to upcoming events, tips and tricks related to prompting, the latest thought leadership, and more! Customer Success Story: Campari Group Campari Group enhances collaboration and creativity with Microsoft 365 Copilot and Microsoft Viva Campari Group is revolutionizing its workplace with Microsoft 365 Copilot and Microsoft Viva in order to drive collaboration, productivity, and innovation. The company has leveraged Copilot and Viva together to empower employees and increase effective collaboration. Notably, early adopters report saving two hours weekly, with 81% seeing productivity gains and 73% experiencing less mental strain. Read more here. Upcoming Events Microsoft AI Skills Fest Learning Bliz | April 8 50 days of AI discovery and learning, starting with our learning blitz on April 8. Registration is now open! Registration officially opens for Microsoft AI Skills Fest—our exciting global event dedicated to boosting AI fluency, one skill at a time, for our customers, partners, and learners everywhere. Register here Ask the Experts series Using additional languages in Viva Glint | April 8 Learn about common topics and best practices when using additional languages in Viva Glint. Register here Think Like A People Scientist series Bridging HR and IT for AI Success | April 9 Hear about the critical need for HR and IT collaboration to achieve true business transformation in the era of AI. We will be joined by speakers from Microsoft HR. Register here Psychological Safety series Building Psychological Safety | April 10 This session aims to help managers learn how to identify psychological safety and what practical actions they can take to help move teams in the right direction (and get a sneak-peak on how Copilot can help!). Register here Building Psychological Safety Amidst Change | April 22 Similar to our standard webinar, but focuses on unique strategies needed for helping employees navigate change. Register here Customer cohorts People-centric AI transformation cohort | April 16 Based on your feedback, we are launching our first topic-based cohort, the people-centric AI transformation cohort. This is open to all customers who are interested in employee experience and AI transformation (HR, IT, etc.)! Register here Technology cohort | April 22 Also based on your feedback, we are excited to announce our fourth industry-based cohort: technology. Register here In case you missed it... Microsoft & Josh Bersin: The Employee Experience Platform Evolves in the Era of AI Panelists discussed the evolution of the Employee Experience Platform (EXP), the Change Agility Imperative, leveraging EXP as a change agility tool, and the pivotal role of HR leadership. First Fridays: Comms Conversations - Applying AI in Communications Industry experts discussed the transformative impact of AI on communications, providing valuable insights and practical applications for attendees. How to Prepare for Employee Self-Service Agent Implementation A step-by-step guide on how to prepare your organization for a smooth and successful rollout. Learn the key actions to take before implementation and best practices for readiness.. Research Drop: Investing in HR & IT Collaboration to Drive Successful AI Transformation As we continue to see massive growth in AI adoption across industries, the importance of collaboration between HR and IT departments has become a critical component for successful AI integration. This month’s research drop explores how HR & IT can better align to drive a more holistic AI transformation. Read our full report here. Tips from the Team: Copilot Prompting Spotlight from Julie Morris, People Science Program Manager Recently, a team member reached out to me after receiving a difficult email from a colleague. She wanted to know if her response sounded kind and professional. I suggested that she have Copilot take a look at it first. She was shocked at what a wonderful sounding board Copilot was and said it offered several suggestions for adjusting her tone resulting in a more productive outcome. Here's a prompt you can try for this kind of scenario: Copilot, can you read this email and give me feedback on clarity, professionalism, and tone? Happy prompting! How are we doing? Did this newsletter increase your knowledge of Copilot? Yes No Enjoying this newsletter and want to share or get it straight to your inbox? Sign up using this link.Research Drop: Diving into AI Transformation Profiles to Understand Unique Needs Across Employee Personas
Research Drop in Brief: We discovered five AI transformation profiles: Multipliers, Advocates, Persuadables, AI Skeptics, and Change Pessimists. These AI transformation profiles highlight key differences in how employees approach AI at work, shaped by their engagement levels, experiences with change, and attitudes. AI transformation needs and expectations are not one-size-fits all; this is illustrated by statistically significant differences in AI usage frequency and perceived value of AI between profiles. We provide a recommendation on how to craft a nuanced AI transformation strategy that is inclusive of all employee profiles’ needs, bolstering the likelihood of success in your own AI transformation. As AI technology continues to evolve at a rapid pace, we are witnessing a profound transformation in the workforce that aims to enable people to be more efficient, productive, and creative than ever. To better understand this experience from the employee perspective, the Microsoft Viva People Science team published The 2024 State of AI Change Readiness eBook, which outlines findings from our recent external panel study on AI Transformation and provides practical guidance for leaders and HR on how to best support people through this change. Involved in our analysis this external panel data for this eBook was a closer look at the employee profiles you may uncover during an AI transformation, deepening our ability to understand and empower employees to adopt AI by meeting them where they are on their AI journey. To do this, we conducted a latent profile analysis (LPA) of our data, which groups respondents by similar response patterns to items on the survey, allowing us to identify profiles. The advantage of LPAs is that they allow you to use data to discover invisible clusters of respondents who share similar beliefs or feelings, removing the potential for assumptions or biases to influence groupings. Specifically, we examined respondents’: Engagement: Their current employee engagement levels Change Experience*: Individual-level experiences with past change initiatives at their organization AI Sentiment: How optimistic and ready they are for AI at work *Assessed at three dimensions: vision (i.e., feeling ownership and clarity over the change vision), communication (i.e., seeking and sharing information on the change), and competence (i.e., proactively upskilling and advocating for the change). Our findings: The five employee AI transformation profiles Within our data sample, we found five AI transformation profiles: Multipliers, Advocates, Persuadables, AI Skeptics, and Change Pessimists. At a high-level, the distribution of these profiles is encouraging – more than 70% of the employees in our study fell into the Multiplier or Advocate profiles! These employees are engaged, have had positive change experiences, and are excited and ready for AI at work. Every organization and employee base will be different based on their unique culture and experiences, but discovering these five profiles in our dataset helped to ground us in an understanding that employees will be at all ends of the spectrum in their personal change and AI journey. Acknowledging the differences helps us to not only describe the potential AI user base, but also hypothesize what key needs exist for each profile to support them through this workforce transformation. These profiles are specific to the study sample and were generated based on the sentiment data available within that study. Therefore, it's important to consider what additional aspects of the employee experience would be relevant when thinking about the profiles that might exist in your organization. Consider your organization and AI transformation: What other considerations (e.g., leadership support of AI, culture of innovation, job security concerns) will you include when thinking about different experiences that employees may have within your organization? How are you considering multiple profiles in your change initiatives? When thinking about employee profiles in your organization, what unique experiences do they bring to the table? What change barriers might exist in your organization and what do you have in place that may help employees overcome those barriers? How might those change enabler efforts differ across your employee profiles? Adoption looks different across AI transformation profiles Looking at employee adoption behaviors across your organization can provide early indicators of how successful various change initiatives are and for whom. At the beginning of your transformation when you are still iterating and refining your long-term vision and goals, it can be helpful to examine usage metrics to see how often the AI tools are being used. In our study we asked respondents how often they use AI at work and sorted responses into four groups: High frequency (at least once a day) Moderate frequency (at least once a week) Low frequency (a few times a month or less) Never From this we found a large and meaningful relationship between AI transformation profiles and AI usage frequency. We can see that employees who are the most likely to engage with AI tools are the Multipliers – highly engaged employees who have had positive previous change experiences and have positive AI sentiments. Usage frequency follows a consistent downward pattern for the profiles, with the highest usage group for Advocates being Moderate Frequency, the highest usage group for Persuadables being Low Frequency, and the highest usage group for AI Skeptics and Change Pessimists being Never. What we learned from this was that change initiatives will not necessarily have the same impact on all employees. Seeing how each profile leverages AI to a different extent provides a key insight into how we can better target those groups. For example, reaching those AI Skeptics and Change Pessimists who never use AI might look different. For AI Skeptics, they are likely unsure about the technology in general, whereas Change Pessimists may not be using AI because they are overwhelmed by the associated business and workplace changes. Uncovering these profiles and knowing how they are adopting AI can better inform your AI transformation strategy. Certain profiles realize differentiated value from AI Further, it’s not just usage that will help you evaluate your change initiatives – how employees feel about using AI at work also provides a deeper level of context that helps change leaders provide a holistic transformation experience. In our study we explored a set out outcomes we call RIVA, or Realized Individual Value of AI. RIVA captures a myriad of ways that employees might see a direct impact of AI use on their day-to-day. Looking at RIVA enables us to see not just that people are using AI at work, but also that they actively recognize positive results from using AI. When comparing AI transformation profiles for RIVA scores overall (only for respondents who use AI at least at a low frequency), we found meaningful differences in RIVA between AI transformation profiles. In other words, how much value people were seeing from their AI use differed across the AI transformation profiles. The graph below outlines the six survey items that make up RIVA and presents percent favorable (Agree + Strongly Agree) scores for each profile. Our Multiplier and Advocate groups reported the highest RIVA of all the profiles, followed by the Persuadables. Only a small subset of AI Skeptics (25%) and Change Pessimists (43%) use AI and were therefore included in this analysis. Interestingly, of these employees, Change Pessimists reported higher RIVA than AI Skeptics, likely because AI Skeptics have the most negative sentiments toward AI. Even with the small number of AI Skeptics and Change Pessimists who do use AI, it’s interesting to see where they are more likely to see value in AI. Around half of AI Skeptics, Change Pessimists, and Persuadables agree that AI allows them to complete tasks faster – an often described “quick win scenario” of leveraging AI. However, when the value becomes less tangible, such as reducing stress or improving decision-making, then we start to see a drop off in favorability. This suggests that change leaders may need to provide additional support and use cases to translate the more “transformational” benefits of AI usage to all employee profiles. This can be done by sharing tactics for leveraging AI that aligns with key business needs specific to the users’ role. Consider the examples in the Microsoft Copilot Scenario Library which provides a variety of AI use-cases across functional areas. We also see nuances in what value AI Skeptics and Change Pessimists see in AI at work. Where AI Skeptics more often report that AI simplifies their complex tasks, Change Pessimists more often report that AI helps them be more productive and make better decisions. This distinction is important because it shows that even though both profiles are hesitant about AI, their reasons for hesitation and the value they see in AI are not the same. Putting all of this into context, it becomes clear that our AI transformation initiatives should be mindful that while AI adoption might feel like flipping a switch for some employees, with certain profiles jumping right into AI transformation, for other groups, it will be more gradual. Better understanding the profiles of those groups can indicate where additional, nuanced support may be required. Change the context, not the person Where an employee may currently fall in a particular AI transformation profile is not static – meaning that as an employee’s environment and experiences change, so will their sentiments around engagement, change, and AI, causing shifts between profiles. Therefore, if you want to increase the likelihood that employees will use AI and see value, AI transformations must embody the basics of change best practices and address the unique needs for employees across the profiles. Each of the AI transformation profiles brings a unique set of strengths and needs to your organization’s AI transformation and change initiatives – supporting the need for targeted approaches that meet employees where they are. While these actions will look different for the employee profiles in your organization, the critical takeaway is that all types of profiles can be an asset to your AI transformation. For example, your Multipliers may have higher Daily Active Usage, but your Change Pessimists may help you create a training program that works for all skill and interest levels. Our takeaway from this AI transformation profile deep dive is further underscoring that everyone has different feelings and perspectives that shape their AI adoption journey and how immediately they will be ready to for your company’s AI transformation. Organizations who succeed in bringing their employees along, through clear communication and ongoing employee feedback, are likely to craft a change strategy that meets their people where they are without judgement. We learned that it’s not solely interest in AI that drives adoption, but also current engagement and previous experience with organizational change. Focusing on critical EX moments and relying on strong change management fundamentals remain critical during this transformation to ensure that no employee groups get left behind. As we continue to navigate the developing landscape of AI, we will continue to learn what our employees need to feel empowered as their skills expand, their tasks evolve, and their work transforms. By seeking to understand the unique employee profiles in your organization, you can better tailor your support to meet their specific needs, fostering a more inclusive and effective AI transformation. Stay tuned for our December Research Drop to keep up with what the Viva People Science team is learning!
