At a glance
- AI's value extends beyond automation and efficiency gains.
- Leading firms are embedding AI across the PE deal lifecycle.
- Scalable intelligence can support stronger value creation outcomes.
- Strategy, governance, people, and partnerships are key AI enablers.
- Human oversight remains critical in AI-enabled private equity.
It’s only natural that many private equity (PE) firms are looking to the transformational power of AI as a potential new lever in their value-creation toolkit.
We’re seeing experimentation across the board. A growing number of AI solutions are coming into the market, plugging into different aspects of the PE lifecycle to improve efficiencies. PE firms are increasingly evaluating discrete AI use cases, primarily focused on automation and other low-hanging fruit to reduce friction points within their operations and enable their people to be more productive.
But the opportunity for AI in the private equity space is much greater than that. It’s about institutionalizing intelligence across the PE deal lifecycle to drive fund differentiation and help generate higher returns in an increasingly competitive market.
The end of spreadsheet alpha in private equity: Embracing a new approach to value creation
Given the recent slowdown in PE deal activity, including exits, PE firms are holding onto companies for longer. Because of this, they’re increasingly turning to operational value creation to enhance ROI, including the use of AI to improve the performance, margins, and growth of their portfolio companies. Over the next five years, leading PE firms will likely also turn to AI to differentiate themselves at the fund level to better compete for deals. This means moving beyond spreadsheets to embrace a more holistic value creation model—one built on scalable intelligence, where AI is embedded end-to-end across the deal lifecycle, from capital raising and deal sourcing to diligence, value creation, exit, and investor relations.
What might an AI leader in private equity look like in 2030?
Establishing a scalable intelligence model with AI: Four pillars for success
We’ve worked directly with private equity firms on a diverse range of AI initiatives, from helping them define their AI strategy and ideate where they want to be as an AI-enabled PE firm in five years time, to helping them develop a change management plan that considers where their people are today and the skills, training, and other supports needed to work confidently within a future AI-enabled operating model.
Through our work, and our own AI transformation experience, we’ve found that there are four foundational pillars that can help PE firms target their AI efforts so they are well-positioned to achieve their strategic objectives and measure impact—both at the fund level and portfolio management level—while staying onside of their regulatory and fiduciary responsibilities.
Leadership AI strategy aligned to business value
Over the last few years, we’ve seen many PE firms invest in AI in an ad-hoc manner, such as by obtaining licenses to use specific AI tools. This makes it difficult to measure the value of AI activities. According to a 2026 BDO Canada survey conducted by Angus Reid, 36% of financial services firms (including PE firms) are experimenting with AI but have not yet achieved meaningful ROI. More insights on Canadian AI trends can be found in our report, AI Vision Report: Past the Pilot to the Agentic Future of Work.
Developing an AI strategy is a critical starting point for success because it gives you a foundation to start with and a focus for driving performance across the deal lifecycle. As a part of your AI strategy, you should clearly define:
- your future target operating model and objectives (e.g., enabling PE deal teams with AI-powered analytics and automation to improve deal sourcing, creating a competitive advantage in fundraising by enhancing LP transparency);
- where your organization is today; and
- a framework for identifying, evaluating, prioritizing, and scaling AI use cases across your operations.
You can then use this strategy to create a roadmap for change, one that considers both quick-wins and the structural changes (e.g., people, process, technology) needed to transform into an AI-enabled PE firm.
Data, AI governance, and controls that help drive intelligent decision-making
A robust data strategy, AI governance, and controls aren’t nice-to-haves if you’re looking to institutionalize intelligence across your PE firm; they’re must-haves given your regulatory obligations and fiduciary responsibilities.
This means you need to get your data house in order so that any data AI agents and solutions use is accurate, consistent, secure, and regulatory compliant. It also means you need to develop a clear governance model so that your people understand where and how they should use AI in their work, where they shouldn’t, and their responsibilities when it comes to verification of any AI outputs. Making accountability clear can help you significantly manage your risks as your move forward with embedding AI into your deal activities.
A people focused change management approach
The importance of change management can’t be understated. On the one hand, you need AI savvy deal-makers and professionals who understand where AI fits in the PE lifecycle—which means determining how you will recruit and retain them in a market where competition for AI talent is incredibly high.
On the other, you also need to meet your current people where they are at. If you don’t provide your people with the training and support they need to feel confident using and working with AI, they’ll fall back on spreadsheets and what they did in the past. But if supported with clear communications, ongoing training, and insights into how changes are resulting in better dealmaking or to higher-value portfolio companies, you can help reduce anxieties and better set your organization up for success.
The right partner to help drive AI value and impact
Moving from a spreadsheet alpha model, where many PE firms are today, to a scalable intelligence model of value creation can be challenging, particularly if you have limited resources and technology capabilities internally. This is where bringing a partner on board can make a major difference. The right partner can help you understand AI transformation, establish the foundational pillars you need to be successful, manage your risks and regulatory requirements, and help you measure the impact and ROI of your efforts.
Turning AI into your competitive advantage—let’s work together
Whether you’re just beginning your AI journey and want to understand how AI can support value creation at the fund or portfolio company management level; need help with a specific aspect of your AI strategy, such as AI governance or change management; or are looking for practical support to embed AI responsibly across your end-to-end activities, we can help.
We’ve worked with private equity firms across Canada to build practical AI approaches that support intelligent decision-making, to establish robust change management programs that foster employee confidence and buy-in for AI initiatives, and to embed AI agents into PE lifecycle activities like deal sourcing and due diligence. We’ll bring this experience, along with the lessons we’ve learned from our own AI transformation, to help you focus your efforts and turn AI into a real competitive advantage.