Episode Details

Live from Morgan Stanley’s European Tech, Media and Telecom conference in Barcelona, our roundtable of analysts discuss artificial intelligence in Europe, and how the region could enable the Agentic AI wave.

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Paul Walsh: Welcome to Thoughts on the Market. I'm Paul Walsh, Morgan Stanley's European head of research product. We are bringing you a special episode today live from Morgan Stanley's, 25th European TMT Conference, currently underway. 

The central theme we're focused on: Can Europe keep up from a technology development perspective?

It's Wednesday, November the 12th at 8:00 AM in Barcelona. 

Earlier this morning I was live on stage with my colleagues, Adam Wood, Head of European Technology and Payments, Emmet Kelly, Head of European Telco and Data Centers, and Lee Simpson, Head of European Technology Hardware. The larger context of our conversation was tech diffusion, one of our four key themes that we've identified at Morgan Stanley Research for 2025. 

For the panel, we wanted to focus further on agentic AI in Europe, AI disruption as well as adoption, and data centers. We started off with my question to Adam. I asked him to frame our conversation around how Europe is enabling the Agentic AI wave.  

Adam Wood: I mean, I think obviously the debate around GenAI, and particularly enterprise software, my space has changed quite a lot over the last three to four months. Maybe it's good if we do go back a little bit to the period before that – when everything was more positive in the world. And I think it is important to think about, you know, why we were excited, before we started to debate the outcomes. 

And the reason we were excited was we've obviously done a lot of work with enterprise software to automate business processes. That's what; that's ultimately what software is about. It's about automating and standardizing business processes. They can be done more efficiently and more repeatably. We'd done work in the past on RPA vendors who tried to take the automation further. And we were getting numbers that, you know, 30 – 40 percent of enterprise processes have been automated in this way. But I think the feeling was it was still the minority. And the reason for that was it was quite difficult with traditional coding techniques to go a lot further. You know, if you take the call center as a classic example, it's very difficult to code what every response is going to be to human interaction with a call center worker. It's practically impossible. 

And so, you know, what we did for a long time was more – where we got into those situations where it was difficult to code every outcome, we'd leave it with labor. And we'd do the labor arbitrage often, where we'd move from onshore workers to offshore workers, but we'd still leave it as a relatively manual process with human intervention in it. 

I think the really exciting thing about GenAI is it completely transforms that equation because if the computers can understand natural human language, again to our call center example, we can train the models on every call center interaction. And then first of all, we can help the call center worker predict what the responses are going to be to incoming queries. And then maybe over time we can even automate that role. 

I think it goes a lot further than, you know, call center workers. We can go into finance where a lot of work is still either manual data re-entry or a remediation of errors. And again, we can automate a lot more of those tasks. That's obviously where, where SAP's involved. But basically what I'm trying to say is if we expand massively the capabilities of what software can automate, surely that has to be good f