AI in Private Equity: Foot Anstey’s value creation roundtable highlights

On 6 November 2025, Foot Anstey hosted the first session in its Private Equity roundtable value creation series on current tech hot topic Artificial Intelligence ("AI").

The event was hosted by Paolo Sbuttoni, partner in the Commercial, Tech & Data team with guest speaker Zoë Webster at Authentic Innovation.

The roundtable brought together PE firms and portfolio companies interested in the impact of AI on the PE sector. The participants discussed how AI is reshaping value creation and the risks and challenges with implementation.

The topics for discussion focused on:

1. AI trends in PE firms and portfolio companies.
2. Key considerations when implementing AI.
3. Deciding when to build versus buy AI.
4. What level of AI PE should expect in portfolio companies.
5. Are we in an AI bubble?

Zoë opened the event with an overview of how AI is being used as a strategic tool in Private Equity. There are many use cases and a lot of potential for AI in PE. However, there is also a lot of hype and many challenges particularly around security and how to ensure that businesses get a return on their AI investments.

AI trends impacting PE & portfolio companies

Zoë shared the following key trends she has been seeing in her role as an AI strategy consultant in AI:

• Adoption of generative AI – ever since ChatGPT launched, businesses across various sectors have been focused on making the most of generative AI. This is having a real impact on the PE sector from tools to assist with deal sourcing/due diligence, to value creation and exit strategy.

• AI Agents – the 2025 hot topic is the use of "AI agents" which are beginning to have significant impact on productivity within PE firms and portfolio businesses.

• AI Literacy – as AI is being adopted, it is important for staff to fully understand how to use it effectively and safely and to implement enterprise wide AI governance. The EU AI Act has specific requirements for users of AI to undergo AI literacy training.

• Information security – a key risk for businesses to overcome when implementing AI is to ensure that the AI meets robust information security requirements and complies with data protection laws. For that reason, we are seeing many large businesses gravitate towards using AI within secure environments that are already implemented at an enterprise level (eg CoPilot within Microsoft 360). We are also seeing many AI vendors building technology that integrates within larger platforms and/or acts as a separate enabling layer on top of the existing technology stack.

Key considerations when implementing AI

There are many new AI vendors offering different specific solutions. The challenge for buyers of AI is knowing which technology to back.

One attendee commented that their portfolios were increasingly pushed to use AI to increase efficiencies. They started their AI journey with Microsoft Copilot - this is their current technology vendor and all security and data protection requirements are already being met. It was therefore easier from a risk management perspective to build an AI layer of functionality through an already onboarded trusted tech vendor.

The risk of "shadow AI" was discussed at length. If companies are not implementing AI there is a risk that employees will look to use unapproved AI services for work purposes, such as free versions of ChatGPT or other LLMs. Microsoft and LinkedIn's survey showed that 71% of people are using AI in this way and it creates significant data security risks for businesses. Transferring personal or confidential data into a free version of an LLM such as ChatGPT would likely be classed as a data leak. Adopting an AI policy is therefore important along with investing in a secure enterprise approved equivalent to free AI services.

Deciding when to build versus buy AI

Most businesses will likely first encounter AI when looking to "buy in" AI capabilities through their existing technology vendor, such as Microsoft, or an alternative AI vendor. For more information on key issues to consider when "buying AI" have a look at our Foot Anstey Guide to Buying AI.

The roundtable discussed that whether building or buying AI, the quality of training data is essential. If AI does not have good quality data, then the results it produces will not be as useful. Therefore in AI strategy, as with all technology projects, time needs to be factored in to plan for structuring datasets to ensure that quality, reliable data is being used. Companies must always be mindful of sources of data to reduce the risk of bias and discrimination.

If you are looking for operational efficiencies, then buying in AI capability is likely more cost effective. However, if you are considering using AI to change the experience of your customers and intend AI to create value/intellectual property - then building that AI functionality in-house will likely be worthwhile.

What level of AI PE should expect in portfolio companies

PE firms are raising the bar on what they expect from portfolio companies when it comes to AI adoption. Understandably, expectations vary by industry, stage and holding period strategy.

Many PE firms will look for a "baseline" of AI productivity tools when assessing businesses for acquisition (eg MS Copilot, ChatGPT for Teams). We are seeing PE firms look to implement AI in core functions (if not there at acquisition) to use AI across marketing, operations, finance and customer support (eg chatbots for queries). At more advanced stages of a business lifecycle, PE firms will look for value creation from a data driven use of AI (for example an integrated data platform, linking sales and financial data perhaps using AI agents). 

When it comes to M&A within PE, due diligence is key and understanding how the target is (or isn’t) using AI is becoming a key question to raise depending on the sector.

Are we in an AI bubble?

It is clear that the level of adoption of AI in PE and portfolio businesses varies significantly. Whilst there is a significant amount of hype over what AI can do for businesses, there are some very clear benefits and operational efficiencies. Implementing AI successfully needs buy in from the top and appropriate AI policies, AI governance and data security protocols to cover increased risks.

If you'd like to discuss key contractual and legal issues when buying AI, AI strategy, governance or implementation across your fund or portfolio, please contact Paolo Sbuttoni.

For further information on Authentic Innovation please contact AI Consultant Zoë Webster on [email protected].

For further information on how we work with Private Equity portfolio companies across all stages of the investment journey to add value see here.

The Foot Anstey Private Equity roundtable series is set to continue in 2026 with our next meeting on planning and implementing your international M&A strategy for success. For more information or to register your interest contact Sarah Laughton on [email protected].