The Situation

 

The IT organization of a large, regulated-industry enterprise brought me in to help the company’s legal and compliance function become more AI-native, moving from scattered experimentation to deliberate, organization-wide adoption. My role was to bridge IT’s enterprise AI strategy and vision with the legal and compliance team’s business priorities, ways of working and people realities. The timing was complicated. The organization was in the midst of significant organizational change, including a reshaped leadership team, and a corporate pilot of Microsoft Copilot was already underway. Legal and compliance work is document-heavy and precision-critical. Leaders were enthusiastic about AI’s potential and equally firm that people must remain accountable for the output.

The Challenge

 

Enthusiasm was running ahead of the enablement, guidance and guardrails needed to turn it into consistent, responsible use. Leaders were being asked to drive AI adoption while navigating a major transition, and employees were absorbing both at once. The organization needed an approach that treated AI adoption as a leadership and change challenge, not a tool rollout, and that could build momentum without getting ahead of its people.

The Approach

 

Listening first. I led listening sessions with nearly the entire senior and mid-level leadership team. I then surveyed every leader, manager and employee in the legal and compliance group about their perceptions of AI, experience to date, barriers to adoption, and the support they needed. The survey revealed a clear readiness gap: 70% of managers and 56% of employees felt more positive about AI, yet 30% of managers and 34% of employees had never used it at work. Access and time were the leading barriers for both groups.

 

Leadership alignment. A leadership alignment workshop brought the newly formed legal and compliance leadership team together to create a shared vision and agree on how they will lead the organization through the transition. A hands-on AI session followed, in which leaders worked on real problems with real-time coaching. The survey reinforced the need for this support: only 11% of managers felt fully equipped to answer their teams’ AI questions, and just 9% said they regularly modeled their own AI use. Nearly one-third wanted to model it more but rarely or never did.

 

A strategy built on what we heard. In close partnership with IT, I translated the enterprise AI vision into an adoption strategy grounded in the legal and compliance team’s priorities and capacity for change. The strategy runs people readiness and tooling decisions in parallel, with each informing the other rather than waiting on it.

 

Use cases drawn directly from the listening. From the listening sessions, I identified more than 40 AI use cases across legal and compliance and prioritized them by value and effort. They fall into three groups: a handful of high-value pilots, roughly 20 self-serve wins employees can pursue with tools they already have, and a set of foundational enablers such as governance and data readiness.

 

A portfolio approach to tools. Rather than betting on a single vendor, the strategy pairs Microsoft Copilot as the baseline with a broad but legal-specialized AI platform for high-value work, adding niche tools only for corner cases. A pilot of the specialized platform is planned this fall spanning five use cases.

 

Six workstreams to sustain adoption over time. I partnered with the operations function to stand up six workstreams as a lasting support system inside the organization: governance and guardrails, manager enablement, communications, training, change champions, and listening and metrics. They are designed to support continuous adoption and growth as AI tools and capabilities keep evolving, not a one-time rollout. I design and coach, while internal leads own and run each workstream, so the capability stays and grows in the organization.

Where Things Stand

 

• Executive sponsors are aligned on an AI vision and success criteria: near-term wins, measurable adoption, leader role-modeling, and a team working AI-natively.

• Nearly all licensed Copilot users are active, and two teams have sustained 100% weekly use over the past month.

• Governance approval for the specialized platform pilot is nearly final, and the pilot is set to kick off imminently.

• The engagement has expanded to include a dedicated AI program manager, one-on-one executive coaching, and broader support for the organizational transition.

Key Learnings

 

• Frame AI as how the organization meets a real capacity problem, not as a headcount play, and say so early and plainly.

• Managers are a key hinge point. Adoption accelerates or stalls at the manager level, so enablement has to reach them early.

• Change capacity sets the pace. Meet the organization where it is and sequence AI adoption around its capacity to absorb change, especially when a significant restructuring is already competing for leaders’ and employees’ attention.

• Building internal owners’ capability takes longer than handing them finished work, but it is what makes adoption durable.

What’s Next

 

Pilot results and business cases, scaling the self-serve use cases, measuring AI fluency, and supporting leaders through the broader organizational change.

If you’re leading AI adoption in a precision-critical function, let’s talk.

 

Book a 30-minute conversation →

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