AI Adoption Beyond the Hype
I discuss the gap between AI enthusiasm and the real-world adoption and productivity gains many businesses are experiencing. Whilst AI has transformed the way I work, I explore why stronger frameworks, best practices and production-ready standards are needed before AI-first organisations become widespread.
Key Takeaways
- AI is powerful for individual productivity, but business-wide adoption and measurable uplift remain lower than the hype suggests.
- AI-generated software can be impressive, but it is often not production-ready, secure or capable enough for serious deployment.
- Wider impact will depend on practical frameworks and best practices for embedding AI into everyday operations.
Topics
- AI & Machine Learning
- Business Strategy
- Productivity
- Security
Transcript
So if you've been watching my content for a while, it probably will be no surprise to you that I'm deeply enthusiastic about AI, but I'm also quite sceptical. Inside of my business and other businesses that I see, I'm not seeing the levels of adoption or productivity uplift that you might have expected from all of the marketing and hype over the last few years. As a power user myself, it's incredible that I can build software again, but I've also realised that a lot of that software isn't fit for production, in fact isn't secure, and doesn't really do as much as advertised. Despite all of that, I will still keep using AI in everything that I do, and it has genuinely transformed the way that I work. But I think in order for it to really have an impact across a business, we need to find frameworks and best practices for how to include it inside of every single operation. With everything I've seen so far and the increasing costs of tokens, it feels to me that we're still quite far away from having AI-first businesses far and wide. I'm exploring that more over the next year, and I believe in 2027 we'll start to make some of those breakthroughs. I will keep sharing, and I will keep using AI every day.