JUNE 03 2026
Artificial intelligence is reshaping private equity from multiple directions at once, touching everything from how firms assess companies' long-term resilience to the capabilities that portfolio companies need to build if they are to remain competitive. At Nordic Capital, that spans working with a portfolio of around 60 companies to embed AI into operations through maturity assessments, dedicated frameworks and peer networks, through to how AI is changing the way the firm evaluates businesses and the durability of their models.
Less visible, but equally consequential, is what AI adoption looks like inside the firm itself. How does Nordic Capital run its investment process, manage its data infrastructure and unlock the institutional knowledge it has accumulated over decades?
That is the territory Mark Peacock, Chief Technology Officer at Nordic Capital Advisors, knows best and shares his perspective on here.
How has Nordic Capital approached AI adoption, and where does it stand today?
"The first cycle was about identifying tools that could slot into specific processes without disrupting how we work. The focus was on finding the right match between capability and task, and that discipline was important. The second cycle is a different conversation altogether. It is about systems, connected workflows and building AI into something durable, rather than accumulating a set of useful but disconnected shortcuts."
Mark's description reflects a pattern visible across the industry. As he sees it, the companies making the most lasting progress have tended to invest in data quality, governance and internal capability first, deploying technology on top of that foundation rather than the other way around.
What has driven that shift?
“Over the past year, Nordic Capital has become more deliberate about what it want to build internally and what it should offer as an owner, both in terms of capabilities and consistency across the portfolio. There is a growing recognition that AI is not just an efficiency lever, but part of how value is created and how investors differentiate.
Close dialogue with portfolio companies has helped validate that direction. As their AI agendas accelerate, expectations on the owner are evoling in parallel, reinforcing the need for a more systematic and scalable approach.”
Nordic Capital has a proprietary portfolio monitoring platform called Cockpit. Where does AI fit into that, and where is it heading?
"Cockpit is currently built on structured data drawn from our portfolio companies' ERP systems, providing a consistent layer of financial and operational KPIs across the portfolio. The next step is introducing generative AI to handle unstructured data, which opens up a much richer set of questions.
Take the HR functional stream as an example. Nordic Capital already tracks sales performance, conversion rates, revenue per person, but why stop there? What about how a company coaches and develops its salespeople? That kind of insight tends to sit in performance reviews and manager notes, scattered and subjective. AI could help bring structure and consistency to something that has historically been hard to measure."
The same logic, Mark notes, applies to Nordic Capital's own institutional memory. Over decades, Nordic Capital has accumulated a substantial archive of deal memos, analyses and outcome data, most of it unstructured and largely untapped as a source of insight. Using AI to interrogate that archive and connect it with structured data in Nordic Capital’s own data lake could, in his view, surface patterns in how decisions were made, where value was created and what conditions tended to produce the best outcomes.
Where do you see the most immediate opportunity within the investment process itself?
"Early-stage screening is where the impact is likely to be most significant. Investment teams spend lots of time on pre-screening work before anything reaches the investment committee. A bid/no-bid decision that currently takes up to two weeks could, with the right tools, be brought down to a matter of days. But the key word is ‘right’. Speed only creates value if the quality of the analysis holds.”
If you look further ahead, what does the ideal situation look like?
“In the long run, the ambition is to give investment professionals access to something close to an all-seeing, all-knowing and unbiased source of analysis, one that can inform and sharpen judgment. I think that is achievable, but there are many steps between here and there. In the meantime, if I ask my team what they actually want, the answer is usually something like ‘a tool that builds PowerPoint decks to the standard we currently produce ourselves’. What has changed is not the ambition, it is the nature of the conversation. The question is no longer whether these things will happen, but how."