Briefing #23: Here's How to Stop "Doing AI"
One simple change puts AI on a path to lasting value.
Note: This briefing was originally published on LinkedIn on January 9, 2026. It has been migrated to our new home on Substack to create a complete archive. Multi-format features like video and audio commentary are available for all new briefings published from April 2026 onwards.
There’s little doubt 2025 was the year of the AI initiative. Enterprise businesses are estimated to have spent between $400 billion to an eye-watering $1.5 trillion on AI in the past 12 months alone.
That’s an unfathomable amount of investment — especially when just 6% of organizations report experiencing “significant” value from their AI investments.
What are the 94% who aren’t experiencing significant returns from AI doing?
They’re funding prediction models, building chatbots, and “AI-powered” features, declaring victory as soon as they can show off a demo. When these demos fail to garner support or the organizational momentum needed to carry on, they’re quietly shelved — or replaced by the next shiny object. The business itself remains unchanged.
The historical precedent for this age of AI we’re in isn’t the Internet, the smartphone, or even the desktop PC. It’s actually something many of us likely take for granted today: it’s electricity.
Let me explain: the companies that won the electric age weren’t the ones who simply bought dynamos to light up their existing, inefficient factories. The winners were the ones who realized the new technology allowed them to fundamentally redesign the factory itself — creating the modern assembly line and unlocking massive gains in productivity.
They didn’t just use electricity. Instead, they built their entire operating model around it.
This is actually the AI-native mindset.
It wasn’t too long ago that many businesses were building “innovation” or “digital” teams, proudly appointing Chief Innovation Officers or Chief Digital Officers with a mandate and deep pockets to lead sweeping organizational transformations. I spent time with one such organization some years ago, an insurance provider, who had made impressive investments to secure a leadership position in the early days of AI, even before the current wave of generative AI we’re all in today.
They had an innovation team including outstanding PhDs in AI and data science. They also had a strong portfolio of AI initiatives. But, the team was disconnected from those who owned P&L. They became a “cost center,” arms length from the actual business. Ultimately, they proved unable to generate discernable value — and were quietly disbanded.
They were a company with AI, but they were not an AI company.
A company that embraces the AI-native mindset looks at AI very differently. They view their core business processes as AI products themselves. A shipping company’s product isn’t “moving boxes,” but rather, is a dynamic engine for “logistics optimization,” for example. These businesses don’t look at AI like it’s a technology you buy, but more like AI is an integral part of the very infrastructure that enables the business to operate.
That 6% of organizations who are seeing significant growth in their EBIT from AI also happen to be the ones actively seeking the AI-native mindset. They’re the ones redesigning processes and workflows, targeting areas where they can scale quickly, and making investments to transform the organization, not just their tech stacks.
Adopting an AI-native mindset means making a fundamental shift in how you invest in AI, who you hire, and where you create value. The call to action is surprisingly simple.
Stop funding demos. Start rewiring your factory.