Sep 3, 2026 · 1 hr 2 min · 13 segments
Millions are being poured into enterprise AI programmes, yet many organisations are still struggling to see the benefits they were promised. So what's going wrong? In this episode, Kiran Kachela is…
Scott BowlerGuest
Kiran KachelaHost
I was recently talking to a leader at a big hospitality and travel sector organization.

He was telling me all about the tech that they're putting in, this big AI transformation program that they had underway.

and the fact that they'd invested millions in it and how it was going to transform their entire organization, starting with finance and procurement and then spreading across the wider organization.

And it's because, in their own words, this project was sexy, right? It was something that they were really excited about.

So much so that they actually canceled a number of other projects that they had already underway.

But they decided that they were going to put all of their investment in this one project because they only had a finite capacity of resource and funds.

Essentially, their dashboards were showing that they had something like 20% adoption.

All of those exciting benefits that they thought this project would deliver hadn't come to fruition.

It was a bit like buying an exercise bike and then sticking it in the box room and sticking your laundry on it.

I was recently talking to a leader at a big hospitality and travel sector organization.

He was telling me all about the tech that they're putting in, this big AI transformation program that they had underway.

and the fact that they'd invested millions in it and how it was going to transform their entire organization, starting with finance and procurement and then spreading across the wider organization.

And it's because, in their own words, this project was sexy, right? It was something that they were really excited about.

So much so that they actually canceled a number of other projects that they had already underway.

But they decided that they were going to put all of their investment in this one project because they only had a finite capacity of resource and funds.

Essentially, their dashboards were showing that they had something like 20% adoption.

All of those exciting benefits that they thought this project would deliver hadn't come to fruition.

It was a bit like buying an exercise bike and then sticking it in the box room and sticking your laundry on it.
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