The People Who Will Drive Change Long After We Leave
Software doesn't transform organizations. People do. The AI Champions program identifies and trains the individuals in each department who will build, deploy, and sustain AI-powered workflows from the inside.
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One person per department. Outsized impact across the entire organization.
An AI Champion is not a technical hire. They're an existing member of your team, someone who knows your department's processes deeply, understands what slows work down, and has the credibility to lead colleagues through change.
What makes a Champion different from a regular AI user is depth. Where most employees learn to use AI tools for their daily tasks, Champions learn to build them. They translate department knowledge into working AI solutions, prompt architectures, agents, connected workflows, that their colleagues can then use as finished tools.
The result: AI that's built from the inside out, by someone who actually knows how your team works. Not by an external vendor guessing at your processes.
What Champions are Trained to Do
1. Process analysis
Identify which workflows in the department are best suited for AI acceleration. Prioritize based on impact, feasibility, and adoption readiness.
2. Solution design
Design AI-powered workflows that fit the department's existing tools and data sources. Structure prompts, agents, and automation pipelines that non-technical colleagues can use reliably.
3. Build and deploy
Use no-code and low-code AI building tools, agents, custom GPTs, prompt templates, connected workflows, to create finished solutions ready for department-wide deployment.
4. Maintain and evolve
Update solutions as tools change. Collect feedback from colleagues. Iterate. Become the department's permanent point of expertise on AI, the person others turn to when they have a question or idea.
Program Structure
The Champions program is intentionally longer and more demanding than standard employee training. That's by design. Champions need to internalize AI fluency at a depth that allows them to teach, build, and troubleshoot, not just use.
Phase 1, Foundation (Sessions 1–2)
AI fluency fundamentals at a technical depth. How large language models work. How prompting shapes outputs. How to evaluate AI output critically. The AI landscape: what tools exist, how they compare, when to use which.
Phase 2, Applied AI for Your Department (Sessions 3–4)
Deep-dive into the specific use cases, document types, and decision workflows of the Champion's department. Hands-on scenario work with real organizational data and processes. Building prompt architectures for repeating workflows.
Phase 3, Building Department Solutions (Sessions 5–6)
Agent design and deployment. Building custom AI tools for colleague use. Connecting AI to data sources and existing tools. Designing workflows that are robust enough for non-expert use.
Phase 4, Change Leadership (Session 7)
How to introduce AI tools to colleagues effectively. Managing resistance. Building adoption gradually. Creating feedback loops. Communicating with management about AI progress and priorities.
Phase 5, Project Presentation (Session 8)
Each Champion presents a completed AI solution they've built for their department. Peer review. Refinement. Documentation for handoff.
Format: Roughly 8 sessions over 10–12 weeks. Can be delivered in parallel with employee training or sequenced afterward. Sessions are 3–4 hours each, on-site or hybrid.
What Champions Build
Real tools. Used by real colleagues. From day one of deployment.
Examples of what past Champions have built:
- A contract review agent for the legal department that flags non-standard clauses and summarizes key terms
- A production summary generator that pulls from shift reports and outputs a structured daily brief for operations management
- A proposal drafting workflow for the sales team that uses CRM data and past proposals to produce first drafts
- A technical documentation assistant for engineering that transforms meeting notes into structured specification documents
- A financial commentary tool that generates variance analysis narratives from monthly Excel reports
These are not proofs of concept. They are deployed, regularly used tools built by department insiders with deep knowledge of the problem they solve.
The Organizational Effect
One Champion creates a multiplier effect across the whole department.
When a Champion deploys a tool that saves 45 minutes per week for 12 colleagues, that's 9 hours of recovered capacity per week, every week, indefinitely. When they build three such tools over a year, the department's relationship with AI has fundamentally changed.
This is the difference between AI adoption as an event (a training day) and AI adoption as a process (an ongoing internal capability). The Champions program plants that capability inside your organization permanently.
Who Makes a Good Champion?
Champions don't need to be technical. They need to be:
- Credible within their department, colleagues will follow their lead
- Curious and motivated, willing to invest in the program seriously
- Process-oriented, they think in workflows, not just tasks
- Communication-capable, they can explain new tools to skeptical colleagues
Most organizations identify 1 Champion per department. Larger departments or departments with complex AI use cases may benefit from 2.
Build the transformation capability your organization will rely on for years.
The Champions program is the highest-leverage investment in your AI transformation. Let's discuss which departments to prioritize and what your Champions will build.
45 minutes · Senior advisor · No commitment