I write these lines on the train headed to Gothenburg, where I will once again host a series of talks and roundtables at D-Congress, the largest retail-tech event in the Nordics. It’s a safe bet to say that most, if not all, of the booths and banners inside the trade show area will talk about AI in some form or other. Agentic commerce was the topic du jour at NRF, the big brother event in New York back in January, and it’s about to intensify in the days to come.
Globally, we are seeing a slaughter in the stock market of established SaaS companies, which are expected to be replaced by feisty upstarts like Claude Code. Personally, I’ve gotten pretty tired of this doomsday narrative. It seems obvious to me that the promise of the moon-aiming AI tools is vastly overstated. Mostly because they NEED to sell transformation at such an epic scale, given their multi-billion-dollar fundraising rounds. But also because the dynamics of enterprise software adoption are far more conservative than venture capital narratives suggest.
Large organisations optimise for stability and accountability, not disruption for its own sake.
Ben Thompson had a sobering take on this on the Sharp Tech podcast a few weeks ago, where he layed out the dynamics of why companies actually use different type of technologies. Any large corporation use somewhere in betweren 350-450 differnt Saas tools (staggering!) and one of the main reasons for it is to reduce riskl. Meaning it’s not just about storing data and executing a task smarter than an Excel file, but to implement processes that make the business more robust and reliable.
A new shiny vibe coded AI tool won’t solve for that in the immiediate future.
This also brought to mind the recent column by the great Tom Goodwin, a personal favourite and one of the most reasonable tech writers out there. Here writes:
And we’ve a painfully loud 3% of the world thinking about it far far too much. People mesmerized by promises, who underestimate the truly VAST real world challenges of turning even the most magical tech into something that can be implemented or add value, in the slightest of ways.
Goodwin underscores that the stats of AI inside corporations are less than great:
Everyone loathes MS Copilot, OpenAI seems to use remarkably little of their own AI, 95% of Gen AI pilots fail, 85% of AI projects show no significant impact, even the people who boasted most about integrating Vibe coding went a bit quiet after the IPO.
And this:
It’s really, really easy to think that AI will change the world fast, until you place one foot in reality.
That sentence captures the core tension of this moment. What you learn once you start looking into AI in more detail is that the reality of business is messy and still reliant on “humans in the loop” (a buzz term we will hear a lot during D-Congress). Implementation remains one of the most important topics for companies trying to infuse AI into their business. And implementation is slow, political, and often invisible from the outside.
Stefan Palm spoke about this at our event in New York during NRF (you can watch it in full here). The founder of fashion retailer Lager 157 clearly stated that AI is a tool, not a decision-maker. He emphasised culture, brand, and the individual know-how from working a lifetime in the fashion industry.
“We will have, let’s say, 80 per cent of the analysis coming from different kinds of product data or AI-driven data, but on top of that, of course, we need to bring in the cultural aspect, the brand perspective of it”, he said on stage.
During my prep-calls with the speakers at the executive roundtable we are hosting on Thursday, I’ve peeked into some of the tech vendors’ strategies for AI. Some startups have built machine learning into their very tool. More established players are building AI layers onto their current offerings. Which will be the best way forwar for fashion companies is up for discussion. We will certainly go into it at the roundtable on Thursday, and most definitely at our upcoming Transformation Conferences later this year.
I’ll keep you in the loop.
