When AI Ambition Meets Federal Reality (Part 2): Operationalizing Responsible AI Through Enterprise Change Management

In Part 1 of this series, we argued that AI implementation is first and foremost an organizational change challenge. In this blog, we shift from that big picture to a more practical change management question: what does it take to make AI stick in day-to-day work?

Across the Federal government, interest in AI is high. But that interest has not yet translated into widespread use. Early 2026 data showed that just 12% of civilian agencies and 2% of defense agencies report that adoption is fully in place. This gap between enthusiasm and actual use points to an issue of adoption. AI implementation does not happen with a single push, and it cannot be measured at just one point in time.

Because of this, agencies need to move beyond one-time readiness checks or post-implementation surveys, which are common in many change efforts. Instead, they should treat change management as something ongoing. Adoption, workforce confidence, and leadership alignment are not milestones to check off. They are conditions that need steady attention throughout the life of the effort.

In practice, that means creating a consistent rhythm that supports change over time. Agencies can do this by focusing on four disciplines that stay active throughout implementation: continuous readiness assessment, regular pulse checks, adoption tracking, and reinforcement, including clear actions for leaders and managers.

Drifting Away from Strategy

Federal agencies are moving quickly to adopt AI, with new policies, pilots, and training underway. But adoption is still uneven. Leaders are seeing confusion among managers and hesitation from employees, and guidance is not always showing up in day-to-day work. Part of the challenge is readiness. Employees need clear guidance, practical examples, and training to build confidence before the introduction of something new.

At the same time, the message can get lost as it moves through the organization. As guidance passes from leaders to managers to employees, it can become inconsistent. That increases risk, especially with AI, where employees are making real-time decisions about data and outputs.

Without a clear way of working, agencies feel pulled in two directions. They need to move fast but also maintain trust. Clear guardrails and ongoing support help employees make good decisions. What is missing is not more policy or tools, but a consistent way to manage change as AI becomes part of everyday work.

A Practical Model for Managing AI as Organizational Change

A consistent model helps close this gap by translating high-level intent into clear, actionable guidance for how work gets done. One FMP approach centers on SHAPE (Shaping the Human and Performance Environment), which focuses on leadership behavior, the workplace environment, and clear communication as the foundation for change. Applied in this way, SHAPE provides a structured path for managing AI as an organizational shift, not just a technology rollout.

SHAPE sits at the center of our enterprise-wide organizational change model (Figure 1) to help the Federal government stay ahead of emerging risks by continuously assessing results and outcomes. This model incorporates components from a variety of change management frameworks, tailoring the approach to organizational needs.

The SHAPE model incorporates the following concepts:

• Sense workforce management & climate, continuously
  • Use quick pulse surveys or short manager check-ins to see where people are confident and where they are stuck.
• Harmonize leadership signals and communications
  • Provide leaders and managers with talking points so messaging is consistent, aligned, and continually reinforced.
• Act early on weak signals and risks
  • Problems often start small. Address them early to avoid bigger disruptions later.
• Prepare managers to lead change at the point of execution
  • Managers guide how work actually gets done. Give them clear expectations, tools, and guidance so they can answer questions and lead with confidence without feeling overwhelmed by what is on their plate.
• Embed accountability into governance
  • Treat AI the same as cost, schedule, and performance. Track it, discuss it, and manage it as part of normal operations or status update meetings.

Instead of reacting after issues surface, this model helps leaders identify and monitor early signals, align actions and messages, and intervene before risks have time to surface as issues.

What this approach solves:

• Leaders see risks and adoption gaps earlier
• Managers reinforce expectations more easily in daily work
• Governance shows up in real workflows, not just at approval stages
• Employees understand how to use AI responsibly in their roles

Over time, teams build more confidence and fluency because there is a clear way to raise issues, learn, and adjust.

Why AI Requires an Enterprise Change Management Approach

AI is different from other technology changes because it moves decision-making closer to the work itself, rather than embedding it primarily in systems, workflows, or approval layers. In past technological shifts, tools often guided users through defined steps with clearer boundaries for judgment. AI changes that dynamic by enabling employees to interpret information, generate content, and shape outputs in real time without a fixed path. While employees have always applied judgment in their roles, AI increases both the frequency and impact of those decisions, making everyday actions like prompting, refining outputs, and determining appropriate use more consequential for quality, risk, and consistency. As a result, AI starts to influence how work gets done, how roles evolve, and how teams coordinate and review outputs. At the same time, the pace of change is much faster. New capabilities and expectations are emerging continuously, requiring organizations and employees to adapt in real time rather than through more structured, time-bound implementation cycles.

AI adoption will not succeed through policy alone. It requires a clear way of working, consistent leadership signals, and ongoing support so agencies can align goals with daily work, empower managers, spot risks early, and build oversight into everyday operations.

In our next blog, we will address the challenge of ongoing change and transition. What happens when employees and organizations face change fatigue?  We will explore what it takes to move beyond one‑off change management campaigns and build an organization that is ready for change as a normal, if not expected, way of operating.

If you’re in the process of introducing AI to your workforce, or even just going through a major change, check out these other blogs for further insights:

• Navigating Change: A Practical Guide
• When AI Ambition Meets Federal Reality (Part 1)
• AI Adoption is Really About People, Not Tech
• Thriving Through Technology Transitions
• Systems Don’t Make Change, People Do

Jessica Waymouth joined FMP in 2014. She is a Managing Consultant helping organizations drive lasting change by aligning people, processes, and systems. She co-leads FMP’s Strategic Communication Community of Practice (CoP) and brings a thoughtful, results-driven approach to organizational transformation. She has a particular passion for mission-driven impact, designing environments that empower individuals and organizations to grow. Outside of work, she’s a mom of two, curious traveler, and loves a good book.  

Jacob Flinck is a Managing Consultant at FMP and co-lead of the firm’s Strategic Communications Community of Practice (CoP), where he helps organizations make sense of complex change and communicate with clarity during moments of transition. His work sits at the intersection of organizational change, strategic communications, and emerging technology, with a particular focus on helping leaders responsibly integrate AI into everyday work. Jacob partners with teams to ensure technology transitions, especially AI-enabled ones, are grounded in people, purpose, and sustained adoption, not just tools. Outside of work, he finds inspiration in travel and creativity in the kitchen through cooking and baking.