Free live webinar, 100 places, filling fast

Your employees are already using AI.
You just don't know how.

“AI doesn't just change how people do their work. It changes how people think about themselves in relation to their work.” Devon Passmore, Director of Product, ethyx

Join Devon Passmore and Dr. Darren Coppin for the real psychology behind AI adoption, plus evidence-based strategies you can use next week.

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Why your AI rollout looks great in the deck, and falls flat in the office. Watch the full video here

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Wagon labelled A.I. with stacked jet engines firing, four horses straining to keep up across a desert — Deloitte's tech-first adoption metaphor.
“AI adoption without work redesign is like putting a jet engine on a horse-drawn carriage.” Deloitte, Humans × Machines, 2025
75%
of knowledge workers use AI at work; half hide it from their manager (Microsoft Work Trend Index and related workforce surveys, 2024–25)
1%
of companies report reaching AI maturity, while 92% plan to increase AI spend (McKinsey, 2025)
4
distinct anxiety types block your AI adoption. Each needs a different intervention.
25%
of AI initiatives delivered expected ROI (IBM CEO study, ~2,000 CEOs globally, 2025)

The Problem

You've invested in the tools. So why isn't your team using them?

IBM surveyed 2,000 CEOs globally and found only 25% of AI initiatives have delivered expected ROI. Deloitte found a big part of the reason: most organisations take a “tech-first” approach, and those companies are roughly 160% more likely to report their AI investment is falling short.

That statistic in the bar above (75% using AI, half hiding it) is the human side of the same problem. It isn't your stack, your training budget, or your rollout deck.

The research is clear: when adoption falls flat, psychology is the driver. Anxiety. Identity. The fear that a tool that can match years of expertise makes you replaceable.

“When asked about the leading obstacles to scaling AI value, executives cited people factors above all else: leadership alignment, workforce readiness, and lack of adoption.”

Deloitte, Humans × Machines, 2025

Most organisations are measuring training completion rates while their most anxious employees stay invisible. Competent, engaged, and hiding it.

What we cover

The seven things your AI program needs to address

01

Your dashboards are lying

The anxious, capable people are often power users in private. Completion rates and licence counts will not show them.

02

Seniors and experts are your leakiest cohort

AI is not a shortcut for them; it is an identity threat. Why they stall, and why boilerplate onboarding makes it worse.

03

Four fears, four fixes

Learning, replacement, sociotech, configuration: different anxieties, different interventions. No one-size template.

04

The classic adoption model fails for GenAI

The textbook framework does not predict AI use the way the slide decks claim. What to rely on instead.

05

Five moves you can run next week

Concrete steps from peer-reviewed work, not vendor theatre.

06

Spot risk before the next cheque

What to measure so hiding, fear, and readiness surface before budget and reputation are gone.

07

Live Q&A, real seats

Bring your scenario. Small room on purpose so questions get answers.

The Research

This isn't opinion.
It's science.

Peer-reviewed sources and large-scale industry studies. Core references:

P1

Venkatesh, Morris, Davis & Davis (2003)

User Acceptance of Information Technology: Toward a Unified View · MIS Quarterly · 30,000+ citations

UTAUT Framework
P2

Wolfe et al. (2025)

Revisiting UTAUT for the Age of AI · arXiv · n = 2,257 professionals across a multinational firm

AI Adoption
P3

Kim et al. (2024)

Determinants of Generative AI Adoption in Korean Companies · MDPI Behavioral Sciences · n = 300

Generative AI
P4

Soulami, Benchekroun & Galiulina (2024)

Exploring How AI Adoption Affects Employees · Frontiers in Artificial Intelligence · Systematic review of 92 studies

Systematic Review
P5

Wang & Wang (2022)

Development and Validation of an AI Anxiety Scale · Interactive Learning Environments · 88,000+ views · 382 citations

Anxiety Framework
P6

Deloitte · Humans × Machines (2025)

59% of organisations take a tech-first approach to AI; those firms are 1.6× more likely to report AI investments falling short of expectations.

Industry
P7

IBM · CEO Study (2025)

Only 25% of AI initiatives have delivered expected ROI across ~2,000 CEOs surveyed globally.

Industry

Who This Is For

This is for you if:

You have been handed an AI rollout and quietly suspect the technology is the easy part.

Your dashboard says licences are paid. Your gut says people are not really using it.

You are expected to bring people along, and you know that is harder than anyone at the top admits.

You have invested in AI and need a return that shows up in behaviour and productivity, not only in a completion report.

You want the science, not a vendor pitch, and you are willing to act on what it shows.

You want time with the people who built the research and the product, with space to ask your own questions.

Your Hosts

The people behind the research

Devon Passmore
Devon Passmore
Director of Product · Azurum / ethyx

Devon leads product at ethyx, with close to a decade across SaaS, HR technology, and organisational behaviour. He has been inside organisations where the official adoption story and the human reality were completely different, and he built LEAP to close that gap. He has designed and shipped AI in highly regulated environments; his work starts with people, not technology.

Dr. Darren Coppin
Dr. Darren Coppin
PhD · MBA · Chief Behavioural Scientist · Azurum / ethyx

Dr. Darren Coppin has spent 25 years and a PhD on what predicts human commitment, behaviour, and action. His research has been validated across government programs in seven countries and presented at national forums on workforce wellbeing. He has worked with Prime Ministers, senior public servants, and CEOs globally, and is the scientific foundation behind ethyx.

Together they bring what almost no one else in this space does: the science and the product built on top of it.

Why only 100 places

This is not a broadcast. It is a conversation.

We cap attendance at 100 so every question can get a real answer, including yours. When we hit capacity, the list closes.

A smaller live room is a signal of quality, not a gimmick: you are not a row in a spreadsheet.

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After the session

Every live session, someone asks: how do we measure this?

LEAP is the answer we built: a validated readiness model that surfaces each person's primary anxiety pattern, barrier, and profile before you roll the next tool out. Not a generic score. A map to evidence-based next steps.

Reporting looks like this in practice: cohort readiness, category mix, and individual signals so managers know where to intervene.

Illustrative UI, not live data.

See what we would surface in your organisation: book a 30-minute private walkthrough. No sales pitch, just your questions and the tool.

Book a private walkthrough

Thirty minutes, no commitment. We walk the reporting with you, not at you.

Use the registration form above and note “LEAP demo” in your question, or reply to your confirmation email.

Don't miss it

The science exists. The measurement exists. The only variable is you.

Your next AI rollout doesn't have to fall flat. But only if you know where your people actually are.

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