Stand up an AI Champions Network in 14 Days

UK productivity is still barely above pre‑pandemic levels, and slipped on a year‑ago basis in Q2 2025. Directors and trustees are being asked to “do more with less” while keeping data safe and staff onside. A lightweight AI Champions Network is a practical way to unlock quick wins, build skills in the open, and avoid expensive false starts. ons.gov.uk

This article gives you a two‑week launch plan, the minimum roles, training cadence, KPIs, risks and costs. It’s written for non‑technical leaders in SMEs and charities.

Why do this now?

• Measured upside: credible research suggests generative AI can materially lift productivity if applied to specific workflows (customer operations, marketing, R&D), but value depends on adoption, not licenses. mckinsey.com
• Workforce readiness: UK workplace bodies report employers see productivity potential, but also call for clear policies, consultation and training to maintain trust. acas.org.uk
• Pragmatic safety: mainstream cyber agencies advise simple safeguards for users and managers (don’t put sensitive data into public tools; check outputs; use approved platforms). Your Champions make these habits stick. gov.uk

If your organisation is starting to pilot AI, pair this network with a simple quality framework such as the scorecard approach in our post on AI quality scoreboards.

The 14‑day launch plan

Days 1–2: Sponsor, scope and guardrails

• Nominate an exec sponsor (Ops, Finance or COO). Their job is to unblock time and signal support.
• Define a 90‑day scope: choose 2 functions to start (for example, Customer Support and Fundraising/BD) and 3 repeatable tasks each.
• Publish basic guardrails on day one:
  • Don’t paste sensitive or personal data into public tools; use approved accounts only.
  • Always review AI output for accuracy, tone and bias before using externally.
  • Log examples and issues in a shared tracker.
  These mirror government and international cyber advice. gov.uk

Days 3–4: Recruit your Champions

• Ask managers to nominate one champion per team (6–10 people total). Prioritise curiosity, patience and good documentation habits over technical skill.
• Agree a time budget: 2–4 hours/week per champion for 12 weeks.
• Share role expectations: you’re “first among equals” in your team, not IT; capture wins, call out risks early, and coach peers for 15 minutes a day.

Days 5–6: Kick‑off workshop (2 hours)

1. Walk through the policy basics and safety guardrails.
2. Map 10–20 candidate tasks per function (triage emails, drafting replies, summarising calls, turning meeting notes into actions, proposing next‑best‑offer to donors/customers, QA checks).
3. Pick the top 3 per function using three criteria: time spent, ease of measuring, low risk.

To structure roles and learning pathways, borrow from our AI skills matrix for UK SMEs.

Days 7–10: Prove value fast

• Run before/after time trials on the 6 chosen tasks. Aim for 10 samples per task. Capture time saved, errors found, and staff satisfaction (1–5 scale).
• Document prompts and checks that consistently work. Keep it to one page per task.
• Escalate any data concerns to your DPO/IT via a single form: data sensitivity, tool used, purpose, mitigations.

Days 11–12: Share and scale inside teams

• Run a 45‑minute “show and tell” per function. Champions demo two tasks, colleagues try them live.
• Start a weekly AI office hours: 30 minutes, same slot, open to all. Rotate hosts.

Days 13–14: Decide and announce

• Create a one‑page value summary per task: baseline time vs new time, £ estimate per month, quality notes, risks, decision (adopt/park/retire).
• Publish a 90‑day plan with 3 adopted tasks, the office‑hours cadence, and KPIs (below). Re‑baseline monthly.

Minimum viable roles (no new hires)

If you want a fuller capability map, see our 30‑60‑90 upskilling plan.

Cadence that sticks

Weekly office hours agenda (30 minutes)

1. One quick win demo (5 mins)
2. One problem/edge case and how we mitigated it (10 mins)
3. Open Q&A and show‑your‑screen coaching (10 mins)
4. Close: remind the safety rules and where to find the playbooks (5 mins)

Communities of practice thrive on rhythm. Keep the meeting short, inclusive, and focused on work that matters. gov.uk

KPIs to prove it’s working

These metrics align with the wider productivity goal: make measurable gains in output per hour while keeping quality and safety high. ons.gov.uk

Simple risk and cost guardrails

Budget the essentials (indicative)

• Time: 2–4 hours/week per Champion; 1 hour/week for the lead; 15 minutes/week for IT/DPO.
• Training: short vendor onboarding or external workshop (£0–£3k depending on size).
• Licences: start with existing suites where possible; add function‑specific tools only after time trials demonstrate value.

The aim is disciplined experimentation: small, accountable changes that compound—consistent with research showing productivity gains come from specific workflows, not blanket tool adoption. mckinsey.com

Procurement questions for any AI tool or training

Use these when talking to vendors or training partners. If answers are vague, move on.

• Use case fit: Which three tasks in Support/Fundraising/Operations do you measurably improve, and by how much in customer hours saved?
• Evidence: Can you share anonymised before/after results from UK SMEs or charities with similar processes?
• Safety: What controls prevent sensitive data from being stored or used to train global models? Where is data processed and for how long? gov.uk
• Cyber: How do you defend against prompt injection and related threats? Which secure‑by‑design guidance do you follow? cisa.gov
• Admin: Can IT centrally manage users, single sign‑on, retention, audit logs and export?
• Exit: What happens to our data and prompts when we leave? Confirm deletion timeline and export format.
• Training quality: Will you adapt your course to our tasks? How will you measure behaviour change 30 days later?

Vendors that align with recognised secure‑AI guidance and your internal policies will make it easier to scale without surprises. cisa.gov

Playbook library: 6 starter tasks most teams can adopt

As the network matures, layer in formal evaluation methods from our 5‑day AI evaluation sprint.

Operating principles to keep trust

• Transparent by default: label when AI assisted a document; keep a visible log of wins, issues and decisions.
• Small stakes first: start with low‑risk, repetitive tasks; move to higher‑stakes work only after quality and cost evidence accumulates.
• Community, not compliance theatre: avoid “policy as pamphlet”. Build habits through office hours, short demos and visible metrics—best practice in communities of practice. gov.uk
• Safety is everyone’s job: Champions model good behaviour and reinforce simple rules every week, aligned to mainstream guidance. cisa.gov

What good looks like at 90 days

• 6–9 tasks adopted with one‑page playbooks and owners.
• Consistent time‑saving in two functions, documented and reviewed monthly.
• Zero safety incidents; near‑misses discussed and addressed openly.
• Staff feedback trending up: “AI helps me finish the boring parts, faster.”
• A clear pipeline for the next quarter’s tasks and training priorities, using the skills matrix to plan who learns what next.

At that point you’ll have something more resilient than a tool rollout: a community that learns in public and compounds results—exactly the context required to translate AI’s theoretical productivity gains into your organisation’s day‑to‑day work. mckinsey.com