If you call your work evidence-based but can't define evidence in one sentence, that's a structural gap. Here I break down what the term requires.

In this episode we cover:

• How data collection differs from evidence generation
• Why classifying claims builds personal diagnostic skill
• How 4 evidence sources expose organisational blind spots

If you want to go further

When we work with clients we gather evidence to serve one purpose: to support or undermine a claim, an assumption or a hypothesis.

It stops you building work around unexamined issues and keeps you grounded in evidence your colleagues trust.

Here's our method on one page.

Get it here.

If your AI dashboard looks healthy but your decisions haven't improved, here I unpack 3 AI mistakes hurting your inclusion work right now.

In this episode we cover:

• Why AI is an inclusion problem now
• How more dashboards hide worse decisions
• Why AI adoption doesn't mean AI capability

If you're finding that your AI tools are generating more reports but your decisions haven't improved, start here: https://realitycheck.elementofinclusion.com/

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If 450 episodes have taught me one thing, it's that every inclusion failure traces to missing evidence. Here I unpack the idea that survived them all.

In this episode we cover:

• How every inclusion failure traces to one gap
• How 4 evidence sources create a complete foundation
• Why scrutiny strengthens work built on evidence

If you're finding that your inclusion work keeps getting questioned because the evidence isn't there, start here: https://realitycheck.elementofinclusion.com/

If you're making inclusion decisions without a system for testing whether your assumptions are true, I break down the 3 frameworks I use with clients every week.

In this episode we cover:

• How 4 evidence sources ground every client decision
• Why assertions without evidence deserve dismissal
• How to separate claims from testable hypotheses

If you're finding that your inclusion decisions are built on claims nobody has tested, start here: https://realitycheck.elementofinclusion.com/

If AI makes your juniors better but leaders keep cutting them, your talent pipeline breaks down. Here I trace the mispricing no one is naming.

In this episode we cover:

• How AI lifts novice performance more than experts
• Why polished output misleads leaders about junior value
• Why cutting entry-level roles starves future leadership

If you're finding that your leaders are cutting the people AI improves the most, start here: https://xray.elementofinclusion.com/

If the inclusion projects you start keep quietly slipping away, your work never compounds. Here I unpack how to fix the leaks.

In this episode we cover:

• Why every body of work quietly leaks
• How correcting yourself protects what you built
• Why starting small builds the bigger arc

If you're finding that the inclusion work you start keeps slipping away before it sticks, start here: https://implementation.elementofinclusion.com/

If your team uses AI but nobody is building judgement, the gap is forming now. Here I break down three modes of AI use and why only one builds skill.

In this episode we cover:

• How adoption metrics hide a growing capability gap
• Why the most common AI mode builds nothing
• When polished output disguises missing judgement

Resources referenced in this episode: Dell'Acqua, F. et al. (2024). Cyborgs, Centaurs, and Self-Automators: The Three Modes of Human-GenAI Knowledge Work and Their Implications for Skilling and the Future of Expertise. Harvard Business School, MIT, Warwick, Wharton.

If you're finding that your team is using AI but you can't tell whether it's building capability or replacing it, start here: https://implementation.elementofinclusion.com/

If your organisation measures AI adoption by usage, the metric masks a deeper gap. Here I break down what the best AI organisations measure instead.

In this episode we cover:

• Why AI competency requires evidence not usage
• How unspoken assumptions shape your AI culture
• Why your future team won't be entirely human

If you're finding that your AI work produces activity but no measurable outcomes, start here: https://realitycheck.elementofinclusion.com/

If your inclusion results rest on circumstantial evidence, you take credit you cannot defend. Here I explain how to look for causation.

In this episode we cover:

• How circumstantial evidence masquerades as proof
• Why good work can produce wrong conclusions
• How the 3 I's test causation

If you're finding that you can't prove your results actually belong to you, start here: https://realitycheck.elementofinclusion.com/

If AI fluency in your organisation means learning tools, the thinking underneath is being skipped. Here I break down a 4 step framework.

In this episode we cover:

• Why human thinking is non-negotiable with AI
• How vague prompts mirror vague inclusion strategies
• Why AI adoption has an ethos problem

If you're finding that AI is reshaping decisions faster than your processes can keep up, start here: https://implementation.elementofinclusion.com/