In a landscape dominated by AI hype and shiny tech demos, some businesses are of the mindset that the technology meant to simplify operations is often doing the opposite.
According to David Tyler, founder and CEO of London-based Outlier Technology, it’s time to stop asking how AI can be used – and start asking what problems actually need solving.
“The worst thing you can do is ask the question, ‘How can I use AI in my business?’,” he told BusinessCloud.
“It’s a non-question – it’s meaningless and it’s pretty much guaranteed to help you waste a lot of time and money on white elephants.”
Outlier Technology, a consultancy that helps organisations untangle and streamline complex systems, is pushing back against the tech-first mentality that seems to be the norm. He believes the answer isn’t more tools, but better thinking.
Tech as a tool, not a goal
With decades of experience in technical and systems roles, Tyler has seen a recurring pattern of businesses investing heavily in platforms like ERPs, CRMs and data warehouses, only to be left disappointed.
He said: “I had a long and successful career in technical roles and kept seeing time again technology taking centre stage in so many businesses, but it quickly failing to deliver on any of the promises made during the sales cycle.
“From my perspective, it was clear that so many organisations were being blinded by technology and its bells and whistles but lost focus on the value it could provide when implemented properly.
“Our objective is to make technology actually work for organisations by using less of it rather than more. You can’t fall out of bed without landing on some form of technology – it’s the easy bit when you understand the core fundamentals.
“We take a human-centred approach to system design – we focus on the outcomes, the decisions and the actions people need to take and we align technology with that to solve real problems.”
Cutting through the noise
From trading systems to data platforms in regulated industries, Outlier’s work spans sectors. But the throughline is clear – fewer buzzwords, more clarity.
“We’ve developed a framework for this where we look at the decisions being made and the actions being taken at different levels of an organisation,” continued Tyler, who was previously a lead data scientist at IHS Markit.
“We look at the roles of those involved and we look at the model for making the decision. Once we understand those things we can make very targeted decisions about what to automate and why.
“It’s so easy to automate for the sake of it and it’s easy to get lost in the fun and spectacle of doing something ‘cool’.
“But if we focus on the people, the decisions and the actions we can see where it makes sense to add – or remove technology.”
The AI reality check
While most tech headlines are dominated by generative AI, the two-time graduate believes a tweak could be in the offing.
Tyler explained: “We’re headed for a massive correction. The hype cycle in AI is massive and we’re seeing open source presenting an existential threat to the likes of OpenAI, Anthropic and so on. Their business model is built around technology for which there is no moat.
“I think what’s likely is we will see the likes of Microsoft and Amazon focus on helping smaller businesses host their own private models and offer a selection of open source models.
“I think the biggest thing businesses can do is start by forgetting that AI exists. Then analyse their business and look at where decisions are made, how they’re made and what can be done to improve those decisions. Once you have that, then start looking at which elements of AI can help you.
“Ultimately, to get anything meaningful out of AI, you need to get very good at defining the problem you want to solve – in detail. That will become the new superpower.”
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