Most organisations can tell you how many people have access to AI and how many have completed the training. Very few can tell you whether anyone's work has changed. In this episode, Andy Lambert, co-founder of AcademyAI, talks to Darrell Fear, founder of Adoptive Learning and former Lloyds Banking Group leader who spent 24 years at the bank and helped build its AI Academy, about what it really takes to turn AI ambition into workforce capability.

Darrell calls the problem capability debt: the growing gap between what a strategy asks people to do and what they can actually do in practice. Every transformation creates a temporary gap, but the debt builds when organisations keep launching new tools, campaigns and courses without closing it. AI doesn't create capability debt, he argues, it accelerates it.

The 7 lessons:
1. Access to AI isn't adoption, and learning about AI isn't capability.
2. Diagnose before you prescribe, using realistic scenarios rather than self-rated confidence.
3. Segment by the work people do, not by the tool.
4. Build the environment around the person: access, time, permission, guardrails, manager support and relevant use cases.
5. Treat managers as adoption infrastructure, not a communications channel.
6. Measure workflow change, not completions, and design the measurement before you launch.
7. Start with the business problem, not the academy, and answer five questions before any work begins.

Darrell shares what the Lloyds academy achieved, including over 300,000 learning completions in its first three months and active AI use moving to 41% from a low starting point, and why he separates reach, adoption and value. He explains why confident, capable and responsible all have to travel together, why AI capability is an organisational problem rather than a technology or people problem, and what he'd do differently with hindsight. He also sets out the six signals of capability debt, from unowned and underdefined to unevidenced and unanchored, and the five questions every leadership team should answer before funding an AI programme.

Chapters
00:00 Welcome to Swansea and Darrell's background
01:39 Access isn't adoption, training isn't capability
02:50 Inside the Lloyds AI Academy and its 67,000 people
04:32 Confident, capable and responsible
05:28 Why personal productivity isn't organisational transformation
07:48 Four design choices behind the academy
12:53 Separating reach, adoption and value
16:22 The academy as one part of a wider ecosystem
19:39 Where AI capability should sit in the business
21:50 Why the best car parts won't make a car start
23:58 What Darrell would do differently
27:17 Managers as adoption infrastructure
28:55 What capability debt is
30:47 The six signals of capability debt
34:51 Five questions for leadership before you start
40:10 Doing the right thing righter
44:06 Access, learning and capability are three different things
46:14 Where to find Darrell

Connect with Darrell
LinkedIn: Darrell Fear

Learn more about AcademyAI: academyai.co

#AITransformation #AICapability #LearningAndDevelopment #FutureOfWork #AIAdoption

Most AI rollouts start with the tools and wonder why nothing changes. In this episode, Andy Lambert, co-founder of AcademyAI, talks to Rich Merrett, Head of AI at Bellrock, about the framework he has used to AI-enable two businesses, first at Citation and now at Bellrock.

Rich's starting point is that AI is an 80% people problem and a 20% tech problem. His strategy rests on four pillars: governance built around a yes-first AI policy rather than an infosec policy wearing an AI T-shirt, a people pillar that runs company-wide training, leadership workshops, hands-on build days and self-selecting champions all at once, a solutions pillar for building what people need, and a monitoring pillar that most organisations miss.

Rich explains how a sales callback tool built at Citation made a quarter of a million pounds in its first four weeks and won the National AI Award for innovation in 2025. He walks through his week of half-hour sessions, open to the whole business every nine months, ending with an "art of the impossible" day where colleagues show what they've built. He covers the four tiers of risk in Bellrock's AI policy, the 10-day feasibility sprints his team runs, why being caught out by the GPT-4 deprecation led him to monitor for model drift and bring subject matter experts back every six months, and how a Teams chatbot feeds hundreds of ideas into a pipeline that Claude scores on impact, strategic fit, time to value and reach against effort. He also talks about matching tools to job role and skill level, calling out objections like sustainability and hallucinations before anyone raises them, a new 12-level badge system for Bellrock's 71 champions, and why active reading may be the most important skill of the next decade.

Chapters
00:00 Introduction
00:52 From teacher to Head of AI
02:21 Why AI is 80% people and 20% tech
03:34 The award-winning sales tool at Citation
05:26 Pillar one: a yes-first AI policy
06:00 Pillar two: people, starting with a week of open sessions
09:07 Why champions must be self-selecting
11:43 Pillar three: DIY wins, 10-day sprints and transformation projects
12:57 Pillar four: monitoring ROI and model drift
14:48 Minimum viable AI governance
17:06 Who should own AI?
19:58 Top down, bottom up and inside out
21:00 Calling out the elephant in the room
26:23 Making the training stick
28:25 Matching tools to role and skill level
33:07 Scoring hundreds of ideas with Claude
36:22 Keeping champions engaged, and 12 levels of badges
41:30 Why active reading is the skill of the future

Connect with Rich
LinkedIn: Richard Merrett

Learn more about AcademyAI: academyai.co

#AITransformation #AIStrategy #AIGovernance #AIChampions #FutureOfWork

Logins and prompt counts tell you people have opened the tool. They don't tell you whether anyone's work has changed. In this episode, Andy Lambert, co-founder of AcademyAI, talks to Donna Lovitt-Edwards, Head of AI Fluency at Informa, about how a 15,000-person business is shifting from AI adoption to genuine enablement.

Donna's starting point is simple: you can mandate access, but you can't mandate curiosity. Instead of pushing tools at people, Informa creates pull. Its learning labs start with a real bottleneck in someone's workflow rather than with AI, and attendees vote on which problems to solve. Everyone leaves with a new way of doing their own work, and some leave having learned that a problem isn't one AI can solve, which is fine too.

Donna explains how she measures enablement by working with finance to put a value on time saved, including a sales team targeting a 3% lift in conversions that saw 2% within two months. She talks about the loud 5% who already love AI and the silent 95% she's really trying to reach, and why some of the strongest resistance has come from early careers colleagues worried about whether their skills will stay relevant and about AI's environmental impact. She also covers why human in the loop is a design decision rather than a slogan, how Informa's AI Innovation Council weighs risk against value before ideas reach production, and why she believes AI transformation should sit with HR rather than IT.

Chapters
00:00 Introduction and Informa at a glance
01:47 From sales and L&D to Head of AI Fluency
05:13 Shifting from adoption to enablement
06:51 How to measure enablement
09:02 Being a super connector
10:48 Why you can't mandate curiosity
13:00 The loud 5% and the silent 95%
13:42 How Informa's learning labs work
19:21 Understanding resistance
20:39 The surprising sceptics: early careers colleagues
24:07 Human in the loop as a design decision
26:44 Prioritising ideas through the AI Innovation Council
32:42 Colleague-built apps and the internal marketplace
34:35 Commitment from the top
37:12 Finding the right person to lead AI transformation
38:01 Why AI should sit with HR
39:34 Fail fast, learn quick, move on
40:10 Where to find Donna

Connect with Donna
LinkedIn: Donna Lovitt-Edwards

Learn more about AcademyAI: academyai.co

#AITransformation #AIFluency #LearningAndDevelopment #FutureOfWork #AIAdoption

Most organisations have bought AI. Fewer can say they are actually better at anything that matters.

Andy Lambert (AcademyAI) talks with Richard Geary of Flow HQ about practical AI adoption: diagnose the real problem before you buy the shiny tool, train for adoption rather than checkbox tool skills, and close the gap between personal productivity wins and organisation-wide value.

Richard has worked through the early SaaS wave (Salesforce, Oracle), helped build SeatGeek’s B2B business toward unicorn status, and has trained thousands of people on AI. His bar is clear: he is not training a tool. He is training for adoption, so people leave able to do something they could not before, and want to keep doing it.

In this episode:

• Why rolling out licences first creates a shiny tool looking for a problem
• People → process → technology, in that order
• Why Sally in accounts and Brian in the stores know what leadership misses
• Enablement vs one-and-done certificates when models change weekly
• AI as “the world’s most well-read intern” and critical review after every output
• Personal Copilot wins vs measurable organisational ROI
• A cabinet-maker proposal workflow cut from hours to about 40 minutes
• What to say when someone tells you “we need to do AI”

Start with why. Find the people who know how the work really breaks. Buy the shiny tool last.

Guest: Richard Geary, Flow HQ Host: Andy Lambert, AcademyAI

AcademyAI: https://academyai.co

Andy's LinkedIn: https://www.linkedin.com/in/andyrlambert/

Richard;'s LinkedIn: https://www.linkedin.com/in/gearyrichard/

Most organisations have the AI tools. Far fewer are actually AI capable. That's exactly where individual productivity and enthusiasm fail to add up to real organisational value.

Andy Lambert (co-founder AcademyAI) and @EricaFarmerai , Influential AI Skills Speaker and Author (Quantum Rise Talent Group) discuss why AI capability spreads so unevenly, across teams, seniority levels, and individuals.

We get into what's really driving the gap, including the organisational design decisions sitting behind it, what HR and people teams are doing about it that works, and why proving capability matters more than assuming it, especially once a board or regulator asks for evidence rather than a training completion rate.