AI. AI. AI. It’s everywhere. And I’m sorry, this is another Artificial Intelligence post, but it’s more a “hold your horses” sort of post…

You see, yesterday, I was helping a colleague review slides for an upcoming AI presentation. He wanted to make sure he gets past the hype, but was suggesting we’re coming out of that phase now as we’re seeing some negative press about generative AI.

I disagreed. Generative AI in particular feels like it’s right at the peak of inflated expectations…

Why I think generative AI is at peak hype right now

I know Gartner is just one (albeit influential) analyst firm, and Hype Cycles aren’t everything, but their Hype Cycle for Emerging Technologies (Aug 2023) shows GenAI approaching the Peak of Inflated Expectations and 2-5 years from productivity.

I don’t have a Gartner subscription but the diagram is taken from an article by The Next Web (and also available directly from the Gartner website). Quoting the TNW article directly,

“Gartner’s warning echoed across our conversations with European tech insiders. In 2024, they expect a cautious and pragmatic approach to AI adoption.”

The Next Web: After a year of breathless hype, AI will face reality in 2024

Another source (which is freely available) is the Gartner Emerging Technologies and Trends Impact Radar for 2024. This contains several AI techs, but shows Generative AI starting to break through:

So what does that mean? To answer that question, we look at another Gartner resource – their Top 10 Strategic Technology Trends for 2024. There are several AI-related trends mentioned, but the TL;DR is that now is the time for strategic planning.

It’s time to get AI ready

Move fast and break things is an often-used phrase suggesting agility. But sometimes, breaking things is less than ideal. And moving fast is great – as long as you’re moving in the right direction.

It’s a good time to increase your awareness of trending technologies (including the democratisation of generative AI) and think about how they can provide benefit to your organisation. But don’t worry if you’re not implementing AI right now. You’re not the only one, despite what you might think from reading around.

To take one example, yes, Microsoft Copilot is huge. The productivity benefits could be significant. But consider your AI readiness before turning on features that could expose data and information that you didn’t even know was there. Think about:

• AI Principles: How will your organisation use AI. What are your boundaries? Can you clearly articulate and have you articulated what you will (and will not) do with AI?
• AI Ready: Data: This is a good opportunity to examine the data you have, what you use it for, and who can access it. Making sure your data is AI ready means that it is ethically governed, secure, free of bias and accurate.
• AI Ready: Security: Understand and prepare for new attack vectors that AI makes possible. Create an acceptable use policy for public-facing generative AI products.

Then, when you’re AI Ready, you’ll be in a position to move fast, hopefully without breaking anything.

Featured image: generated with AI, in WordPress!