AI Hype Paradox

For science, big enterprise, tech companies investing millions into AI transformation the hype is real.

Plus, open YouTube and there are many newly made millionaire AI solopreneurs telling you AI hype is real. Which for them it is, but that is like a millionaire footballer telling you there is money in football. With the right combination of skills, timing, and market positioning millions can be made.

But what about the remaining 99% of the population?

In the real world...

SME hype is a bit 'meh' right now

Without scale and without technical expertise, the path from "AI sounds amazing" to "AI is generating measurable ROI" remains frustratingly unclear for most SMEs.

You've probably felt this yourself. You read yet another article about AI transforming business. You watch a demo that looks incredible. You think "we should be doing this" - and then... what? Where do you actually start? What's the business case? Who's going to implement it? And crucially, who's going to fix it when it goes wrong?

The truth is, we're in an awkward middle period. AI is transformative, but the pathway for typical SMEs is still being built.

What is Really Happening

Shadow Use Is Huge

While businesses wrestle with official AI strategies, something interesting is already happening in most businesses, that is shadow AI use.

You and your team members are probably using AI every day. But quietly. Individually.

Many are secretly using ChatGPT to draft emails, polish proposals, brainstorm ideas, or explain technical concepts. They're using it on their phones during lunch breaks or at home in the evening to prep for meetings. Some are paying for subscriptions out of their own pockets.

This isn't necessarily a bad thing - in fact, it's often a good thing. It shows initiative and productivity gains at the individual level.

Managing Shadow Use

Shadow AI use is the clearest signal that there is genuine value here, as it is happening without anyone pushing it.

Don't ignore shadow AI use, harness it.

• Give training and guidance

• Share, collaborate, and discuss openly

• Control what sensitive information might be going into public AI tools

• Capture, share and learn the effective techniques people discover

• You're missing the opportunity to standardise what works

• Support people who are struggling or making mistakes

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