It was boxing day, and I was watching football on TV with my brother in law. 'So, how do you use AI, anyway?' he asked. I was completely stumped.

I work for an AI company, and we build AI products for customers. It's kind of ...everywhere. How could he not be using it?

While AI dominates tech & social headlines, its adoption tells a tale of two worlds: big biz investing in innovation yet struggling to implement it, and successful small businesses searching for practical applications that align with their immediate needs. This gap isn't about resources – it reveals fundamental differences in how businesses approach innovation based on their size and priorities.

My brother in law runs a successful medical product & services company. He and his friend have nurtured the company over the last fifteen years. Starting out in the in-laws living room, to now distributing more than 200 products to a global customer base. If you need to know about medical grade lube, he's your guy.

I told him that I use it for everything, and it was a game-changer. Last week I'd used it to review a contract -- unpicking unwieldy legalese that my brain couldn't make sense of. It helped me simplify complex language, with examples, so I could work through it. It saved me hours of back and forth with legal, and saved them a huge amount of frustration.

"Oh, cool" he said.

The reason his question stumped me is because it became clear that I exist in a social and tech bubble. Normal, down to earth "business folks" aren't seeing much value from AI, so they don't talk about it. But if you use X, it's all anyone talks about. If you've seen the announcements for OpenAI's o3, you'll know what I mean.

I then wondered how many businesses are actually using AI. From my own experiences, who do I talk to and what do they seem to care about? Generally they're bigger businesses, more complex businesses (operationally, configuration and people). They have people responsible for optimisation or efficiencies or transformation. They have the luxury of thinking about innovation. They might even think about innovation as an annual cycle, setting targets and budgets as a percentage of sales.

But smaller businesses are more practical in their analysis. It's raw and more fundamental: How will I apply it? Who will use it? Does it make them better at their work? Why would I do this over that? Market research (Savanta, '23) suggests smaller companies care more about cash flow and working capital. This makes sense to me, focus on innovations that deliver pay off in the short term. Long term is a luxury.

The ONS reports that as of Oct 2024, c. 15% of businesses are planning to implement AI in the next three months. This tells me there's still a way to go before it hits the mainstream, at least for smaller businesses. This is because there's friction when it comes to identifying how best to apply the tools to the problem.

When companies get bigger, innovations are way more difficult to scale. Innovation usually happens in an ivory tower, far removed from where the actual "thing" happens. A lot of elements need to line up to see something make its way into business as usual. I've delivered projects (optimisation algorithms) with ROI of 200X or more, that "failed." Why? Because of a lack of leadership alignment and buy in. I was amazed. Even at the time, the barriers were obvious. The business was engaged but not ready for the transformation. Other emergent reasons for failure include the inability to embed and support innovations.

The Innovation Index (NTT Data, '23) suggests that 96% of big business executives think innovation is critical for growth and long term success. But only 21% meet their innovation goals. The reason for this is lack of employee skills, infrastructure and low trust in data. This tells me that innovation is hard and consistent with my observations.

With smaller businesses more focused on staying in the game, innovations have to enhance the core product or proposition. Big business is incentivised differently: they've "made it". So innovation will focus on incremental improvements rather than radical innovations. Unless of course, some existential crisis looms. So, when working on innovation in a big corp setting, efforts will remain bound by these incentive structures.

Bringing it back to how I started this article, my answer to my brother in law should have been "Well, it depends on the progress I'm trying to make." And there, I think, all innovation should focus. Your customers "job to be done", and how innovation helps you deliver more for your customer. Amazon adopts this philosophy by focusing on customer centric outcomes. They prioritise metrics such as successful deliveries, rather than internal metrics: add to cart, sales, pick, pack & ship, etc. "....So, where could you improve value to your customer?" That is where AI could play a part.

Twitter: @josephlangford_