AI Center of Excellence

An AI Center of Excellence (AI CoE) is a centralized function within an organization that defines, drives, and scales the company’s AI strategy and implementation.

At Rekap, we believe an AI CoE isn’t just about centralizing knowledge, it’s about operationalizing AI in a way that creates real, measurable business value. It’s the connective tissue between experimentation and execution, turning AI from an innovation lab novelty into a cross-functional engine for performance.

Core Functions of an AI CoE

Establish guardrails and frameworks for how AI is evaluated, implemented, and monitored. This includes:

• Data governance and ethical use guidelines
• Model selection, versioning, and lifecycle management
• Risk assessment frameworks to ensure responsible AI use
• Compliance with internal and external regulatory standards

Not every AI project is worth doing. The CoE identifies and validates high-impact opportunities by:

• Partnering with domain leaders to understand business pain points
• Evaluating feasibility, ROI, and integration complexity
• Building a living backlog of vetted, prioritized use cases
• Creating shared criteria for what “valuable” means across departments

AI adoption only scales when teams know how to use it. A CoE:

• Creates and curates playbooks for repeatable AI workflows
• Develops internal certification or onboarding programs
• Hosts regular enablement sessions, office hours, and roadshows
• Translates technical concepts into business language and vice versa

Without clear metrics, AI success is anecdotal. The CoE puts numbers behind the work by:

• Tracking adoption, usage patterns, and satisfaction scores
• Connecting AI projects to business outcomes (e.g. efficiency gains, risk reduction, revenue growth)
• Creating dashboards for visibility and accountability
• Regularly reviewing and deprecating underperforming initiatives

oo often, AI initiatives get stuck in experimentation mode or fragmented across teams. What separates a high-functioning CoE is its ability to turn AI into an operating system for the business. That means:

• Bridging strategy and execution: The CoE doesn’t just advise—it executes. It embeds AI into real workflows, closes loops with stakeholders, and ensures AI tools aren’t just shiny objects, but drivers of process change.
• Creating shared context: An effective CoE brings together ops, HR, GTM, finance, and leadership to speak a common language about AI—what it is, where it fits, and how to scale it.
• Building trust: By being transparent about where data comes from, how models are trained, and what success looks like, the CoE earns stakeholder buy-in and keeps projects aligned with company values.

Rekap gives AI Centers of Excellence superpowers. We eliminate guesswork by showing how work actually happens across your organization. With Rekap, your CoE isn’t relying on surveys or theory—it’s grounded in real data, real behavior, and real outcomes.

• Surface real opportunities: Rekap reveals inefficient workflows, repeated tasks, and high-friction processes that are prime candidates for automation or augmentation.
• Make AI tangible: Instead of pitching abstract potential, your CoE can point to concrete before-and-after benchmarks powered by Rekap data.
• Create compounding value: Rekap acts as a memory layer, capturing what was tried, what worked, and where there are repeatable patterns—so your AI CoE doesn't reinvent the wheel every quarter.
• Accelerate enablement: With auto-generated documentation of workflows, processes, and usage patterns, training becomes easier, onboarding is faster, and AI tools integrate more naturally into daily work.

Rekap helps your AI Center of Excellence go from advisory body to operational engine.