Partner Blog | Time to market wins: Building the Frontier partner practice
Customers are clear about what they want from AI now. They want to move from ideas to outcomes faster, and at enterprise scale. The experimentation phase is giving way to production expectations, and time to market is becoming a competitive advantage in how organizations transform. That shift creates opportunity for AI practice leaders in services partner organizations. Partners who can repeatedly take agentic solutions from concept to production, while addressing governance and security considerations, can earn a bigger role in customers’ most critical transformation work. Earlier this spring, Nicole Dezen shared the direction for our partner ecosystem, including our framework for Frontier Transformation and updates to the Microsoft AI Cloud Partner Program, such as the Frontier Partner specialization. This blog is the follow-up, with clear guidance on how to build the partner business behind Frontier Transformation and how to position your practice to win on time to market. Move confidently from pilots to production AI has moved from experimentation to real-world impact. Customers are transforming business processes, products, and employee experiences with AI, and they expect solutions that operate reliably in the real world. That means production-grade delivery, governance, and the ability to scale. continue reading hereEVENT | Drive Frontier Transformation: Attend the engineer summit and work toward your badge
Accelerate your capabilities delivering Frontier Transformation with two exciting opportunities: the Frontier Transformation Engineer badge and the Frontier Transformation Engineer Summit. The Frontier Transformation Engineer badge validates your expertise in building AI agents across the Frontier stack, which includes Microsoft Foundry, Microsoft Copilot Studio, Microsoft 365 Copilot, GitHub Copilot, Microsoft Fabric, and Agent 365. This applied skilling journey equips solution engineers and architects to design, build, and operate production-ready agentic AI solutions—so you can lead customers from AI experimentation to secure, real-world agentic implementation. Earn the badge through certifications, project-ready execution, and advanced training. As you work toward the badge, join us for the Frontier Transformation Engineer Summit on June 9, a live, expert-led skilling experience designed to fast-track badge completion. Gain insights on how to use Microsoft Agent Factory at scale, building individual expertise, showcasing organizational readiness, and leading Frontier Transformation for your customers. These are exciting opportunities to drive Frontier Transformation—both for your organization and for customers who are looking to adopt agentic AI at scale. And as we get ready to enter FY27, the year of Frontier Transformation, we strongly encourage you to join us at MCAPS Start for Partners on July 22. You'll get insights from Microsoft leaders on where we’re investing, our shared priorities, and how to activate AI-led opportunities to drive growth this year.
Scaling Seller Impact with ASPX Insights: From Data Access to AI-Driven Execution
ASPX Insights in Partner Center Most sellers are not constrained by opportunity; they are constrained by time and signal. With up to 70% of effort spent on administrative work, portfolio coverage continues to expand while insight quality declines. Sellers are forced to manually interpret fragmented telemetry across multiple systems, slowing decision-making and reducing precision in where they focus. The result is missed revenue signals, delayed interventions, and inconsistent execution at scale. Productivity is not just about efficiency, it is about enabling every seller to consistently identify and act on the highest-value opportunity, in real time. To drive consistent, data-led growth across Security and AI Business Solutions, partners should connect to ASPX Insights within Partner Center. This provides direct access to adoption propensity models, customer telemetry, and actionable account-level insights across Microsoft 365 Copilot, E7, and Agent 365 scenarios. Access to ASPX Insights is only the starting point. The real value comes from how you operationalise that data and surface it directly to sellers in the flow of work. The most effective pattern is to build a lightweight “opportunity agent” that connects to ASPX data via API and translates telemetry into clear actions. This ensures your sales teams have the right conversation with the right customer at the right time - Conversations that are backed by intelligent insights to help guide your customer's on their AI and security journey. The Architecture ASPX Insights is powered by Partner Center data and exposes rich telemetry and propensity signals that can be accessed programmatically. This allows partners to move beyond dashboards and embed insights directly into seller workflows. As demonstrated in internal adoption patterns, partners can connect to ASPX via API and pull Customer-level adoption and usage telemetry Copilot, Security, and Agent usage signals Propensity scores for expansion, adoption, and conversion Licensing, whitespace, and engagement indicators The M365 Partner API – AI Business Solutions & Security Insights allows partners to ground an agent in real, actionable data rather than static pipeline assumptions. By pulling live telemetry and seat-level signals directly into the agent, the solution continuously reflects actual customer usage patterns - who is adopting, who is stalled, and where there is untapped potential. This means opportunity identification is no longer based on periodic reporting or manual interpretation, but on near real-time behavioural insight. As a result, account prioritisation, upsell motions, and intervention strategies are driven by evidence rather than instinct, enabling account teams to act with precision and focus on the highest-impact opportunities across their portfolio. The agent should act as a translation layer between raw telemetry and seller action. The goal is not to expose more data, but to remove ambiguity and tell the seller exactly where to focus. A simple architecture looks like this: Data layer Ingest ASPX Insights data via API on a daily or scheduled basis. Optionally store monthly snapshots to track trends and smooth out variability. This creates both real-time signal and historical context. With the data layer you have a couple of options. You can integrate directly into Partner Centre ASPX Insights by using the API. This is technically complex and may have a longer lead time to see results. Alternatively, to see results with less complexity, you can simply download snapshots of the data monthly from ASPX Insights in Partner Centre. This is manual but easy to achieve and offers a shorter time to value for your agent. Scoring layer Use ASPX propensity outputs directly or combine them with your own logic to rank accounts across a small set of opportunity lenses Expansion ready (Copilot scale) Conversion ready (free to paid) At risk (low adoption vs paid licenses) Transformation ready (Agent 365 and advanced AI scenarios) These align directly with the machine learning models and signals already surfaced in ASPX. Action layer Translate scores into next best actions Who to engage Why now What motion to run (sell, enable, expand, govern) This is where agents create value. Sellers should not see raw dashboards. They should see prioritised accounts and recommended actions. Internal Adoption Path The key design principle is simple: bring insight into the tools sellers already use. CRM integration Push ranked accounts and recommendations directly into CRM as opportunities, tasks, or account insights. This ensures data becomes part of pipeline management, not a separate activity. Copilot / Agent interface Expose the agent through Microsoft 365 Copilot or a custom chat interface where sellers can ask Which customers should I prioritise this week Which accounts are ready for Copilot or E7 expansion Where are my adoption risks The agent queries the ASPX-backed dataset and returns structured recommendations in seconds. Proactive notifications Trigger alerts based on signal changes Spikes in Copilot usage Drops in adoption for paid tenants New high-propensity accounts entering threshold This shifts sellers from reactive to proactive engagement. Portfolio dashboards (secondary) Maintain dashboards for leadership and planning, but not as the primary interaction model for sellers. Dashboards support strategy, agents drive execution. Extending into E7 and Agent 365 scenarios Once the agent is connected to ASPX, partners can extend the same model across broader solution plays E7 opportunities Use signals such as usage depth, licensing posture, and workload adoption to identify customers progressing toward advanced security and compliance requirements. The agent can flag these accounts as ready for E7-led conversations. Agent 365 opportunities Combine Copilot maturity with agent usage signals to identify customers moving beyond productivity into process automation. These are high-value transformation plays where partners should proactively engage. This ensures sellers are not operating in silos but are guided toward the next logical workload based on real behavior, not assumptions. Where to Next If you lead a partner sales team, connect to ASPX Insights and see how these insights can empower your sales teams to achieve more. Check out our ready made ASPX Insights agent in Github.Now generally available: Microsoft 365 E7 and Agent 365
We're excited to announce the general availability of Microsoft 365 E7 and Agent 365! Microsoft 365 E7 is the Frontier Suite powered by Work IQ, designed for a human-led, agent-operated enterprise—turning human intent into AI action that functions securely and at scale. Microsoft 365 E7 bundles Microsoft 365 E5, Copilot, Agent 365, and more into a single integrated offer built for customers’ Frontier Transformation. Designed for organizations to move from AI experimentation to scale, it includes Microsoft Entra Suite and advanced Defender, Intune, and Purview capabilities, delivering comprehensive security across agents and employees. Agent 365 is the control plane for customers to observe, govern, and secure both Microsoft and third-party AI agents, grounded in shared intelligence and built with trust to protect the organization. This marks a clear path for customers to upgrade to Microsoft 365 E7, unlocking access to Agent 365 for a setup built for secure agentic operations. Get more detailsPartner Blog | Frontier Transformation starts here: Save the date for MCAPS Start for Partners
Customers are moving toward Frontier Transformation, and they are looking to Microsoft partners to turn AI from isolated experimentation into a repeatable operating capability embedded into how work gets done. Value does not scale automatically, but complexity does. Partners who win in FY27 will be the ones who can operationalize AI with intelligence grounded in real work and trust built in from day one, including security, governance, and responsible AI. MCAPS Start for Partners is built to give you early clarity on what Microsoft will prioritize in FY27 so you can translate strategy into execution. It is the annual moment to align with Microsoft priorities at the start of the fiscal year so that you begin on the same page around investments and go-to-market motions that will shape customer conversations throughout the year. Save the date to join us virtually on Wednesday, July 22, 2026, to align on what is changing, what is net-new, and where Microsoft will focus. You will hear directly from Microsoft leaders and leave with practical next steps you can activate with your teams in the first weeks of FY27 across co-sell engagement, Microsoft Marketplace motions, incentives, and skilling. Registration opens in May. Download the calendar invite now to save the date for the event. The shift partners are observing: Frontier Transformation moves from pilots to operating capability Across industries, customers are pushing for outcomes, not pilots. They want solutions that can be operationalized, governed, and scaled across business units. Expectations are also rising around security, compliance, and responsible AI as AI moves closer to core business processes. For partners, this is a clear signal. Differentiation increasingly comes from repeatable delivery models, strong governance, and responsible AI practices built into your approach from day one. Customers want confidence that AI is not just deployed but is also managed, secured, and monitored in ways that stand up to real-world use. Starting FY27 aligned to Microsoft priorities can sharpen your focus, guide where you invest, and accelerate your ability to engage customers with a clear execution model. Continue reading herePartner Blog | Introducing Microsoft 365 E7: The Frontier Suite
Frontier Firms—those who adopt an AI-first approach as a core part of their business strategy—are shaping the future of work, which is increasingly fueled by agentic AI. As customers move toward Frontier Transformation, you can help them seize the agentic moment with the premium Microsoft 365 E7 plan, generally available on May 1, 2026. Microsoft 365 E7 is the Frontier Suite, designed for a human-led, agent-operated enterprise, turning human intent into AI action that functions securely and at scale. To accomplish this, Microsoft 365 E7 includes access to Microsoft Agent 365—the control plane to govern and scale agents. Microsoft 365 E7 bundles Microsoft 365 E5, Microsoft 365 Copilot, Entra Suite, and Agent 365 to serve customers who are ready to scale AI with governance and security. This means your customers will have AI-powered productivity apps with advanced security and AI capabilities, grounded in intelligence and trust. You can help your customers make the most of the agentic AI opportunity and unlock new monetization streams with the premium Microsoft 365 E7 plan. Starting on April 1, 2026, to accelerate Microsoft 365 E5 to Microsoft 365 E7 upsell and Agent 365 adoption, Copilot + Power Accelerate will include Agent 365 across Immersion Briefings, Envisioning and proof of concept (PoC) engagements, and Deployment Accelerators. Microsoft 365 E7 and Agent 365 will also be included as eligible workloads for core tier one strategic product accelerators and growth levers in Cloud Solution Provider (CSP) incentives. The AI future is here. Encourage your customers to upgrade to Microsoft 365 E7 so they can move faster and deploy AI with confidence. Read more in our blog post
Spotlight On... AI Transformation & the Frontier Firm Playbook
Introduction AI transformation is not a single launch – it’s a multi‑phase journey that blends strategy, change management, and measurable business outcomes. The Frontier Firm Playbook captures how leading organizations move from AI pilots to pervasive impact by aligning use cases to business value, scaling responsibly, and building momentum with the right metrics. This article shares how to apply that playbook in practice – and how Viva Glint and Viva Pulse together serve as the employee listening and insights backbone of the transformation, capturing signals of readiness, trust, adoption, and impact that usage telemetry alone cannot reveal. Pulse enables rapid, scenario‑specific feedback early and often, while Glint provides the enterprise‑grade analytics, benchmarking, and trend analysis required to govern and scale AI transformation. Why Follow the Frontier Firm Playbook? Frontier Firms are those that consistently turn AI’s potential into a durable competitive advantage. What sets them apart is how they manage the transformation: Intentional sequencing: They sequence initiatives from foundational readiness to pilot-scenario quick wins, to scaled adoption. Measuring what matters: They go beyond raw deployment counts – tracking usage, behavior change, and business outcomes together. Building trust & capability: They invest in upskilling, clear communication, and responsible AI guardrails to foster confidence and competence. Continuous feedback loops: They continuously listen to employees (and customers), using feedback to refine the program as it evolves. Crucially, Frontier Firms treat AI adoption as an organization-wide people transformation, not just a tech rollout. HR: Co-Owner of the Journey In successful AI transformations, HR is a named co‑owner of the Frontier Firm journey alongside IT and business leadership. That’s because lasting AI-powered change depends on new behaviors, skills, and cultural shifts at scale – domains where HR excels: Workforce transformation: AI adoption reshapes roles, skills, incentives, manager routines, and culture. HR functions as the strategic enabler for these workforce changes, ensuring people are prepared and supported. Skills and enablement: HR drives role-based training, upskilling, and change communications, so employees feel confident and know why and how to use AI. Employee listening & trust: HR uses Viva Glint and Pulse to gauge sentiment, trust, and pain points, giving leaders evidence to steer the change effectively. Bottom line: AI transformation is as much about people as technology. Empowering HR to co-lead – backed by robust employee insights – greatly increases the odds of success. Viva Glint & Pulse: A Layered Listening Model Frontier Firms use a layered listening approach. Viva Pulse captures fast, situational feedback during early rollout and experimentation, while Viva Glint consolidates sentiment, comments, and outcomes into a durable insight layer that leaders use to steer, govern, and scale AI adoption. Different data sets answer different questions: Telemetry (e.g., Copilot usage stats and license dispersion) shows what is happening – who is using AI, how often, in which apps. Business outcomes (KPIs like productivity or quality metrics) show what changed as a result of AI. Glint and Pulse measure why those results are happening in a way to guide direct action to address the feedback – revealing human factors like confidence, trust, friction points, and enablement gaps. Simply put, Glint and Pulse track workforce sentiment and adoption motivators throughout the AI journey, allowing organizations to continuously check in with employees and to leverage advanced analytics to uncover key insights. This real-time input highlights challenges or wins that metrics alone can't provide—such as identifying whether low usage stems from inadequate training, apprehension about AI, or workflow mismatch. By using Glint and Pulse, HR and leaders gain a trusted, central gauge of organizational readiness and sentiment. This allows them to address issues (e.g., low confidence or ethical concerns) proactively and to celebrate successes (e.g., improved productivity and morale) with credible data. The Frontier Firm Phases & What to Measure Successful AI transformation follows a deliberate, phased path. Frontier Firms progress through three stages: Foundation, Expansion, and Frontier. Across all phases, Frontier Firms follow a consistent measurement journey: early readiness feedback (Pulse), deep sentiment and trend analysis (Glint), and usage/outcome correlation (Viva Insights + Copilot reports). Phase 1: Foundation Goal: Ensure the organization is prepared — strategically and culturally — to adopt AI. Frontier Firms start by aligning AI scenarios to business priorities and establishing clear guardrails. Just as importantly, they assess whether employees understand why AI matters and feel confident using it. What to measure: Employee confidence and trust in AI Enterprise cultural readiness Awareness of priority AI scenarios and enablement coverage Awareness of strategic mission aligned to AI investments Early signals of hesitation, risk, or uneven preparedness HR’s role: HR co‑owns this phase by shaping the change narrative, segmenting the workforce for targeted enablement, and ensuring managers are equipped to lead adoption. Phase 2: Expansion Goal: Prove value quickly in a small number of high‑impact scenarios. In this phase, Frontier Firms focus on 2–4 pilot scenarios that demonstrate tangible benefits and build confidence across the organization. What to measure: Copilot usage depth and repeat use in pilot groups Self‑reported time savings and quality improvements Employee feedback on usefulness, accuracy, and friction HR’s role: HR partners with business leaders to reinforce new habits through role‑based learning, manager routines, and peer sharing. Phase 3: Frontier Goal: Embed AI into everyday work and sustain momentum responsibly. Once value is proven, Frontier Firms scale adoption with consistent enablement, governance, and continuous listening. What to measure: Adoption patterns by role, team, and region Links between AI usage, employee experience, and strategic business outcomes Ongoing trust, confidence, and enablement effectiveness HR’s role: HR helps embed AI into role expectations, capability models, and performance conversations, ensuring adoption is sustainable and inclusive. Why this matters Across all three phases, telemetry shows what's happening — but employee sentiment explains why. By pairing usage and outcome data with workforce sentiment, Frontier Firms reduce transformation risk, accelerate value realization, and scale AI with confidence. Your AI Transformation Measurement Stack To manage an AI transformation, you will draw on multiple sources of data and insights. Viva Glint and Pulse sit at the center of this measurement strategy, complemented by usage analytics and workplace analytics across Viva. The table below summarizes how each tool or signal contributes: Measurement Tool / Signal Role in AI Transformation (What It Captures) Viva Glint and Pulse – Copilot Survey Templates Employee sentiment and readiness. Pulse is typically used for early and recurring checks tied to specific Copilot/AI Transformation moments, while Glint is used to aggregate, analyze, and correlate sentiment with usage and outcomes over time. Purpose-built surveys templates for Readiness, Adoption, Impact can be deployed in Viva Glint or Pulse designed to capture baseline and ongoing sentiment on AI: e.g., awareness, confidence, trust, perceived usefulness, and enablement effectiveness. Reveals why people are or are not adopting. M365 Copilot usage & adoption analytics Usage telemetry. Dashboard and admin reports showing who is using Copilot, how often, and in which scenarios (when available). Key metrics include active users, active days per user, and usage trends by team or role. Shows what AI usage looks like across the org. Viva Glint + Insights – Workplace Patterns report Work pattern changes. Analyzes how work habits are shifting as AI is adopted: meeting hours, focus time, after-hours workload, cross-collaboration patterns, etc. Compare teams using Copilot vs. those not using it to see if work is getting streamlined (e.g., fewer meetings, more focus time). Viva Glint + Copilot – Employee Experience Outcomes report Experience vs. adoption link. Combines the above data to see if higher AI adoption correlates with improved employee experience. For example, do people who use Copilot feel they “can do my best work” more often? Is workload perception changing? Understanding sentiment with Copilot also helps us uncover: -high adoption but low satisfaction signaling, e.g., the need for more enablement -low usage/low satisfaction signaling, e.g., the need to explore deeper barriers and root causes Viva Glint + Engage - Ambient Signals report (in development) Integrated telemetry + outcomes + sentiment. In development: advanced analytics to link behavioral data with outcomes and sentiment in real time. This can pinpoint moments that matter – e.g., correlating a spike in AI usage with a boost in productivity or identifying where low trust feedback coincides with low adoption. Viva Glint - Employee Feedback agent (in development) Continuous listening at scale. In development: an on-demand, conversational feedback tool enabling quick pulse checks on specific topics. For instance, a manager could ask their team about a new Copilot feature, and an AI-driven summary of responses would feed into the program's next steps. Together, these tools provide a 360° view of your AI initiative. But it is the voice of your employees, the qualitative “why” layer as measured by Glint and Pulse, that gives context to the quantitative numbers. It ensures you do not misinterpret raw data and helps HR and leaders make informed adjustments (whether that's more training, tweaking a use case, or communicating success stories to build confidence). Example 90‑Day Plan To illustrate how all these pieces come together, here is an example of a 90-day rollout plan that can be piloted with a subset of the employee population before rolling out function –specific or enterprise-wide initiatives for kicking off the Frontier Firm journey: Weeks 0–4: Awareness & Readiness Deploy short readiness and expectation surveys using Viva Pulse to capture early sentiment on AI confidence, trust, and perceived value. Use Viva Insights to establish baseline Copilot usage and adoption patterns. Segment early adopters to inform a targeted pilot rollout strategy. Set clear adoption and experience success metrics and develop enablement materials. Weeks 5-8: Pilot, Learn, and Adjust Launch pilots with defined scenarios and success criteria. Continue Pulse check‑ins to monitor usefulness, friction, and enablement gaps. Analyze sentiment heatmaps and early resistance signals to refine the pilot approach. Begin correlating early sentiment with usage using Copilot Employee Experience Outcomes data where available. Weeks 9-12: Scale with Confidence Conduct Viva Glint engagement or Copilot Impact surveys to measure sustained confidence, trust, and enablement. Correlate Glint sentiment insights with usage and Workplace Patterns data to identify what is driving (or blocking) adoption. Identify success stories and positive adoption signals to amplify across the organization. Establish a recurring measurement rhythm using Glint and Pulse as the systems of record for ongoing governance. Throughout these 90 days, the insights from Glint, Pulse and other analytics are crucial – they ensure you’re not just checking technical metrics but truly understanding how employees are experiencing the change. Early feedback helps you iterate the program for greater success in subsequent waves. “What Good Looks Like”: Key Success Signals How will you know if your AI transformation is on track? Here are some leading indicators that Frontier Firms watch for: Adoption: ~60–70% of target users actively using AI at least weekly by the second month, with the average frequency of use per user rising steadily. This shows not only broad uptake but deeper habitual use. Employee Experience: Improvement in employee survey ratings on items like “I can do my best work” or “I have the tools and support I need,” indicating that people feel more effective and supported with AI. Productivity Gains: Measurable time savings in key workflows – for example, a 10–20% reduction in routine meeting time for pilot teams, faster completion of tasks like document preparation or case notes, etc. Quality Improvements: Signs of higher quality output in pilot areas, such as fewer revision cycles required or fewer escalations and errors in AI-assisted processes. Confidence & Trust: Increasing user-reported accuracy ratings and confidence in AI recommendations over time, reflecting growing trust as the technology proves its value. Sustainability: A growing and active community of champions, an expanding library of shared best-practice prompts, and a visible improvement backlog for the AI program. These all indicate that the initiative is building self-sustaining momentum beyond the initial push. These metrics should be interpreted in combination. For instance, a jump in usage is encouraging – but if experience or trust scores drop, it flags a risk (perhaps people feel pressure to use AI without support). That's why Glint’s qualitative insights are so vital to pair with quantitative metrics. Frontier Firms watch both, ensuring increased AI adoption also means employees feel more effective and empowered, not frustrated or threatened. Common Pitfalls (and How to Avoid Them) Even with a solid plan, there are missteps to guard against. Here are a few common pitfalls in AI transformation – and how Frontier Firms avoid them: Staying vigilant about these pitfalls will help ensure your AI initiative delivers sustained results. In particular, never underestimate the people side – unaddressed fears or lack of support can derail even the best technology. By measuring and responding to the human signals, you mitigate transformation risks (e.g., catching early signs of fatigue or compliance concerns) and strengthen your case for scaling AI responsibly. Resources Embarking on the Frontier Firm journey requires both strategic vision and tactical execution. Here are some resources to help you move forward: Frontier Firm Playbook – Detailed guidance on AI transformation patterns, example scenarios, and maturity stages (Microsoft’s playbook) Frontier Firm Scenarios – A library of industry-specific AI use cases to spark ideas By following the Frontier Firm Playbook – and leveraging Glint and Pulse to keep a finger on the pulse of your organization – you can turn AI from a promising experiment into a sustainable, enterprise-wide capability. The result is not just successful AI adoption, but a more engaged, empowered workforce ready to innovate continuously. Good luck on your journey to becoming a Frontier Firm!Partner Blog | Lead SMBs into the AI frontier with Microsoft 365 Copilot Business
In today’s fast-changing digital landscape, the Microsoft partner ecosystem is the catalyst for building Frontier Firms that lead with AI, embrace innovation, and deliver transformative outcomes for enterprise customers. To illustrate this, the Enterprise Partner Solutions (EPS) Asia Regional Leadership Team (RLT) has launched a new series called Frontier Forward: Asia Edition focused on how partners are creating impactful solutions across Asia. About the Frontier Forward series By interviewing executives from key partner organizations, we spotlight successful joint initiatives and tangible results that matter to enterprise customers. Follow along to learn how partners have developed strategies that accelerate transformation and create customer value. Continue reading here
