AI was showing up across The Gunter Group in small, disconnected pockets. Individual consultants were experimenting on their own, but there was no shared approach, no governance, and no mechanism for turning what was working for one person into something the whole firm could use. Competitive pressure was building, and the tooling was evolving faster than informal adoption could absorb. The problem wasn't interest. It was structure. What was missing was a repeatable model for identifying, testing, and embedding AI capability across a workforce with a wide range of starting points.
Case Study
Turning AI experimentation into a firm-wide capability in under six months.
When every consultant was trying something different and nothing was sticking, we built the system that changed that. A structured adoption program, a champion network, and a governance model that made AI practical across the entire firm.
Engagement at-a-glance
Industry:
Consulting & Professional Services
Organization size:
50-100 employees
Services:
AI & Data Strategy
Training & Adoption
Program & Project Delivery
Training & Adoption
Program & Project Delivery
The Challenge
Fragmented usage. No framework. No way to scale it.
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No structure behind the experimentation.
Consultants were exploring AI tools independently, but there was no prioritization process, no shared methodology, and no way to distinguish what was worth scaling. The activity was real. The results stayed with individuals.
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Governance wasn't keeping pace with usage.
As AI crept into daily work, the firm had no guardrails in place around ethics, data handling, or appropriate use. The gap between what people were doing informally and what the firm had formally thought through was widening.
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The tooling was moving faster than the workforce.
Keeping up with a rapidly shifting AI landscape required dedicated structure the firm didn't yet have. Without a repeatable model for evaluating and adopting new tools, each cycle of change meant starting from scratch.
Our Approach
Building a repeatable system, not a one-time rollout.
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1
Meet people where they are
The team assessed baseline AI usage across the firm and identified who had early interest or momentum. Rather than designing a program for an idealized user, they built it around the actual range of experience already in the building.
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2
Establish the governance before scaling the usage
Before accelerating adoption, the team built the guardrails. Training on generative AI fundamentals, ethics, and appropriate use went out firm wide, alongside a governance framework that gave consultants clear boundaries and the confidence to work within them.
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3
Prioritize real problems, not hypothetical ones
Working with consultants and operations staff, the team built a use case backlog grounded in actual firm challenges. Problems were prioritized by impact and feasibility, keeping the work connected to outcomes rather than novelty.
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4
Build, enable, and sustain through a dual-track model
Two parallel tracks ran simultaneously: an investment track for higher effort use cases and a sprint track for rapid prototyping. AI Champions embedded across the firm drove adoption from the inside, supported by monthly learning labs and firm wide tool rollouts that kept the program improving after initial deployment.
Value Delivered
A firm that knows how to adopt AI, not just use it.
A repeatable adoption methodology
The Gunter Group now has a structured model for identifying, prioritizing, and deploying AI capabilities, one built from real problems inside the firm and ready to scale to client engagements.
Governance that matches the pace of change
The firm now has documented guardrails for AI use, including ethics guidance, data handling standards, and clear expectations for appropriate use. Consultants know what's in bounds and why.
An embedded champion network
Fifteen to twenty AI Champions distributed across the firm give the program staying power. Adoption isn't dependent on a central push; it's sustained by people embedded in each practice area.
A foundation for client-facing AI work
The internal program produced the methodology, tools, and demonstrated results that The Gunter Group can now bring to clients as a structured AI workforce readiness offering.
Results that reflect the work behind them.
60-70%
Firm-wide AI adoption rate among consultants
50-60%
Share of staff actively identifying and developing AI use cases
30%
Share of staff involved in building and testing AI tools
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