While hyperscalers race to build data centers and GPU manufacturers struggle to meet demand, a different story is unfolding inside enterprise IT organizations. The Forrester Wave: Microsoft Business Applications Services, Q1 2026 reveals a measured — even cautious — approach to Copilot adoption that contrasts sharply with the AI infrastructure stampede dominating headlines.

This supply vs. demand gap matters: Billions are flowing into AI supply-side capacity while enterprise demand remains disciplined, governed, and conditional. After speaking with dozens of CIOs and CDOs implementing Copilot across Dynamics 365, Power Platform, and Microsoft 365, we identified six patterns that define successful adoption and explain why most organizations are still piloting rather than scaling:

  • Most enterprises remain in pilot mode. Organizations are testing Copilot in targeted scenarios — such as sales enablement, customer service, and analytics — before committing to broader rollout. A mid-tier Australian bank ran pilots with a few hundred licenses to assess adoption, data readiness, and cost impact. A North American government organization restricted Copilot to internal teams to evaluate regulatory and process fit. These pilots help establish ROI, data readiness, and user experience baselines. Providers that support phased adoption — with clear success criteria, adoption metrics, and cost transparency — align better with enterprise buying behavior than those pushing rapid enterprisewide deployment.
  • AI capabilities are table stakes, but outcomes remain unproven. Every MBAS provider now offers Copilot integration, but presence doesn’t equal impact. A North American retailer deployed Copilot in Dynamics 365 Customer Service to summarize case histories and recommend next actions for agents, reducing average handling time in high-volume queues. An EMEA bank piloted Copilot for relationship managers to summarize client interactions and draft follow-ups but only expanded licenses after seeing measurable improvements in response quality and cycle time. CIOs are demanding outcome-led use cases upfront, not generic productivity claims.
  • Industry depth accelerates value realization. Providers with deep sector expertise tailor AI solutions to specific business contexts, improving adoption and time to value. An EMEA insurer saw stronger uptake when Copilot was tuned to underwriting workflows and regulatory language rather than generic prompts. A North American manufacturer benefited from a provider that understood merchandising and supply chain processes, enabling Copilot to surface insights aligned with actual decision-making patterns. CIOs should prioritize partners with proven transformation frameworks and sector-specific capabilities.
  • Governance determines who scales and who stalls. Governance defines where Copilot can be used, how data is accessed, who approves new use cases, and how low-code development is controlled at scale. A European public-sector agency restricted Copilot to a small internal group while IT defined data boundaries, security controls, and approval workflows. An Australian insurer established a Power Platform and Copilot center of excellence to govern citizen development, ensuring new copilots aligned with underwriting and compliance requirements. Providers that embed governance models, enablement frameworks, and architectural guardrails early help clients avoid stalled pilots and costly rework.
  • Copilot integration depth varies dramatically across providers. Some providers embed Copilot directly into delivery, operations, and business workflows; others position it as an add-on. A North American manufacturer worked with a provider that integrated Copilot into development and testing workflows, reducing effort for documentation and code review. In contrast, an EMEA telecom noted their partner could demonstrate Copilot features but lacked accelerators or repeatable patterns to integrate it into live sales and service processes. CIOs should assess not just availability, but operational depth.
  • Roadmap alignment reduces integration risk. Providers closely aligned with Microsoft’s AI strategy deliver future-ready solutions and reduce rework. A large European energy company valued partners who could translate Microsoft’s rapid Copilot updates into practical guidance on when to adopt new capabilities vs. when to wait. A North American retailer reduced rework by ensuring Copilot integrations stayed within supported Dynamics and Power Platform patterns. Strategic alignment matters for long-term relevance.

The AI Shift In Microsoft Business Applications Is Real… 

… but enterprise adoption follows a different timeline than infrastructure investment cycles suggest. Success is no longer defined by deployment speed alone. Organizations that lead with the right use cases, embed governance early, and demand measurable outcomes are making steady progress. Most, however, remain 12–18 months away from scaled deployment.

The Gap Between AI Supply And Enterprise Demand Won’t Close On Its Own

Service providers hold the key to accelerating this timeline. Those that move beyond feature demonstrations to deliver governance frameworks, outcome-based use cases, and industry-specific accelerators will compress the vision-to-value cycle. The providers that succeed will translate Microsoft’s roadmap into business value — not simply resell licenses. For CIOs, choosing the right partner means finding one that can bridge what’s technically possible with what’s organizationally ready.

To identify the right partner for your digital transformation, read the full Forrester Wave: Microsoft Business Applications Services, Q1 2026. The report provides detailed comparison of the 14 most significant providers and their capabilities across strategy, offering, and customer feedback. Set up a guidance session to discuss how these insights apply to your organization.