The Case Study Trap: Why Asking for AI Case Studies Is the Easiest Way to Do Nothing

Australia, Apr 3, 2025

Within executive teams and boards across the globe - one phrase keeps showing up when AI is mentioned:

“Can you show me a case study?”

It sounds harmless. Even wise. A reasonable request to reduce risk before investing in something new. But in practice? It’s become the most respectable way to do nothing.

And in a domain as fast-moving and transformative as artificial intelligence, that default mindset is a quiet killer of opportunity.

Why We Keep Asking for Case Studies

Let’s be honest — leaders ask for case studies because they’ve been burned before.

They’ve seen flashy technology promises fall flat. They’ve been sold innovation on PowerPoint and delivered complexity in real life. So they want proof before they commit. Sensible, right?

Yes — but not in the world of AI.

Here’s why: AI isn’t a product you install. It’s a capability you build. And building that capability is 90% internal readiness and 10% tooling. That’s where the case study model breaks down.

The Ugly Truth No One Wants to Talk About

Here’s the real reason most AI initiatives fail — and why looking for external proof won’t help you:

The biggest blocker to AI adoption in most organisations isn’t the technology. It’s the mess underneath.

The data chaos.
The outdated retention policies.
The spreadsheet-based workarounds.
The shadow IT.
The complete absence of real data governance.

These aren’t sexy topics. They’ve been kicked down the road for years. But AI brings them all into the spotlight — because without trustworthy data and clearly governed information, AI cannot work. Full stop.

You don’t need a case study. You need to open that cupboard under the stairs and start cleaning it out, putting shelves in, organising it with new lighting and a suitable lock to make sure it can’t once again become that unkept, unorganised cupboard.

The Real Problem: Leaders Aren’t Being Enabled for This

Here’s what’s even more concerning:

The lack of AI enablement for organisational leaders is astonishing.

We’ve enabled technical teams for years. But executive teams? Often flying blind — unsure what AI actually means for their business, and even less sure how to lead it.

So they default to the familiar: Let’s ask for a case study. Let’s defer the risk. Let’s wait.
All the while, competitors are moving, testing, learning — and building the muscle memory to lead in an AI-first future.

What You Lose While You Wait

When organisations cling to case studies instead of taking action:

You outsource your courage.
You’re waiting for someone else to prove it works, when the opportunity could be yours.
You reduce AI to replication.
Case studies reflect someone else’s business model, data, and market. Yours is different — and deserves its own blueprint.
You delay the inevitable.
AI will expose every crack in your information ecosystem. Waiting won’t fix it. Getting started will.

What to Do Instead: Be the Case Study

You don’t need a 12-month roadmap or a major investment to start. You need movement. Here's how:

Start small. Choose one business problem — one that matters — and explore how AI might improve it.
Focus on your readiness. Audit your data landscape. Ask the hard questions about access, governance, and quality.
Invest in leadership enablement. Your executive team must understand enough about AI to ask better questions — and stop reaching for outdated playbooks.

At Logicalis Asia Pacific, we work with clients to do just that.
Not just implementing AI — but helping leaders and organisations become ready for it. Because technology doesn’t drive value. People and processes do.

About This Series: The Case Study Trap

This article is the first in an 8-part series exploring AI from a business and leadership lens — cutting through the buzzwords to confront the real blockers and enablers.

Over the coming weeks, we’ll dive into:

The Case Study Trap (this article)
Why Most AI Roadmaps Fail Before They Begin – Because the biggest roadblocks are the ones hiding in plain sight: your data, your silos, and your governance.
The Real ROI of AI Isn’t Just Cost Saving – Productivity, insight, speed — and why bad data can wipe them all out.
Proof-of-Concept is Dead: Try Business-in-Concept Instead – Why scaling AI needs business buy-in, not tech experiments.
You Don’t Need a Data Scientist, You Need a Business Translator – Connecting strategy, data, and execution.
Don’t Fear AI: Fear Wasting Time Without It – The cost of inaction is now greater than the risk of trying.
How to Pick Your First AI Project – It’s not about what's shiny. It’s about where your data is strong.
AI as a Leadership Decision, Not Just a Tech One – Governance, risk, and executive capability in an AI-first world.

If you're a business leader trying to cut through the hype and focus on what matters — this series is for you. Each piece is written for business leaders who want to move beyond buzzwords and start creating real traction.

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