Understanding AI Maturity: Part 3 – Stage 2: Localized Projects

Last week in Part 2, we explored the Ad Hoc phase of generative AI maturity, where curiosity sparks experimentation, but shadow IT and security risks begin to surface. We saw how individual tinkering with tools like ChatGPT and Claude can reveal powerful use cases, even as it challenges organizational norms. Leaders in Stage 1 recognize the need to listen, observe, and gently guide grassroots innovation toward shared learning.

This week, we move into Stage 2: Localized Projects, where GenAI begins to shift from scattered exploration to team-level pilots and proof-of-concepts. It’s a stage characterized by creativity, momentum, and the emergence of internal champions, yet also shaped by fragile workflows and inconsistent evaluation, as teams navigate early pilots without formal governance or shared metrics, often relying on intuition rather than standardized measures of success.

What Localized Projects Look Like

In Stage 2, small groups or departments begin building use-case-specific tools:

• A marketing team might deploy a GenAI-powered content summarizer.
• An IT group might experiment with a triage agent for help desk tickets.
• HR might pilot a Q&A bot for PTO policies.

These efforts are often led by citizen developers, domain experts, or embedded data scientists using tools like LangChain, CrewAI, or OpenAI’s function-calling APIs. Agentic AI starts to appear in mono-agent deployments—simple, tightly scoped systems that perform one task well but operate in isolation, without connection to wider processes. Evaluation remains informal. Teams may compare productivity before and after adoption or collect anecdotal feedback, but formal metrics are rare. And while local success can be exciting, it doesn’t always scale.

Risks and Leadership Challenges

Stage 2 is fertile ground—but it’s also fragile. Risks include:

• Overgeneralizing from local wins
• Embedding immature workflows into production systems
• Replicating fragile pilots without governance

Leaders must begin tracking what’s being built, what tools are gaining traction, and where agent handoffs or breakdowns occur. This is the time to start cataloging toolchains, documenting agent behaviors, and gently introducing structure without stifling innovation.

One powerful strategy is the hybrid model:

• Encourage open-ended exploration (pitch your coolest GenAI idea)
• Pair it with targeted problem-solving (build strategic solutions in high-ROI domains)

This approach balances imaginative thinking with strategic focus which opens the innovation funnel while directing energy toward measurable returns.

Building Internal Champions

Stage 2 is also when internal champions begin to emerge. These are the employees who see GenAI not just as a tool, but as a capability. They prototype, iterate, and generate excitement that helps drive adoption. Leaders should support them with visibility, resources, and opportunities to share learnings across teams.

Documenting these early wins, and the lessons learned when things go sideways, lays the groundwork for scale. It also helps build trust, which is essential as GenAI moves from isolated pilots to cross-functional programs.

What’s Next: Programmatic Use

Next week, we’ll explore Stage 3: Programmatic Use, where GenAI adoption becomes coordinated across departments. This is the phase where governance frameworks emerge, strategic portfolios take shape, and agentic systems begin to collaborate across workflows.

We’ll look at how organizations like Adobe and Salesforce have navigated this transition—and what leadership practices are needed to sustain momentum without losing agility.

Until then, we’d love to hear from you:

What localized GenAI projects have you seen in your organization?

What worked, what didn’t, and what surprised you?

Let’s keep learning together.

This post is part of a series. View the full series Understanding AI Maturity.

This article was created in collaboration with GenAI and shaped by intentional human insight.

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Amie Harpe Founder and Principal Consultant

Amie Harpe is a strategic consultant, IT leader, and founder of Sakara Digital, with 20+ years of experience delivering global quality, compliance, and digital transformation initiatives across pharma, biotech, medical device, and consumer health. She specializes in GxP compliance, AI governance and adoption, document management systems (including Veeva QMS), program management, and operational optimization — with a proven track record of leading complex, high-impact initiatives (often with budgets exceeding $40M) and managing cross-functional, multicultural teams. Through Sakara Digital, Amie helps organizations navigate digital transformation with clarity, flexibility, and purpose, delivering senior-level fractional consulting directly to clients and through strategic partnerships with consulting firms and software providers. She currently serves as Strategic Partner to IntuitionLabs on GxP compliance and AI-enabled transformation for pharmaceutical and life sciences clients. Amie is also the founder of Peacefully Proven (peacefullyproven.com), a wellness brand focused on intentional, peaceful living.

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