Top private equity firms unlock value with AI. Can you afford to fall behind?
In the first article of our new Accelerate: Private Equity and Value Creation Series, we examine how Canadian private equity firms can leverage AI by building strong data foundations, piloting innovative projects, and scaling responsibly for sustainable results.
Key takeaways
- AI adoption is essential for Canadian private equity firms to remain competitive and drive national productivity. Success depends on combining advanced AI models with strong data management and quantitative frameworks.
- Human judgment remains indispensable. AI should augment, not replace, human expertise, with processes ensuring that data-driven insights are balanced by strategic interpretation and oversight.
- The shift to AI-powered automation enables firms to focus on strategic value creation rather than routine tasks. Responsible and measured adoption starts with high-quality data, pilot projects, and clear ROI.
The investment management and private equity sectors are undergoing a profound transformation, fueled by rapid advances in artificial intelligence (AI).
Canada, however, faces unique challenges. Despite our strength in AI research and development, Canadians are more skeptical; only 31% say they trust AI, compared to a global average of 50%.1 Meanwhile, U.S. firms are leading in AI innovation, producing 40 notable AI models in 2024 alone.2
(Note: notable models are those that achieve state-of-the-art results, are highly cited, or are recognized for historical or practical impact.)3
In 2024, global investment in AI reached $252.3 billion USD (about $354.4 billion CAD), according to a recent Stanford University report.4 For Canadian private equity, the question is no longer whether to embrace AI, but how to do so responsibly and effectively.
AI has become a competitive necessity for strong returns and long-term growth. As Canada lags in adoption, PE firms that leverage AI to scale mid-market companies can drive national productivity and economic prosperity.
By embracing AI, Canadian private equity can help build a stronger, more innovative economy.
Three key insights for Canadian PE firms and AI
1. Success requires more than language models
While the excitement around large language models (LLMs) is justified, firms need to look beyond the hype. Are LLMs alone enough for investment-grade analysis?
To truly unlock AI’s potential in investment management, LLMs must be paired with robust quantitative frameworks. Data quality and integrity, once considered back-office concerns, have become strategic assets, making a “Single Source of Truth” (SSOT) central to fund success. For private equity firms, prioritizing data integrity and governance is now the foundation for any successful AI initiative.
AXA Investment Managers highlight both the promise and the limitations of AI in quantitative equity investing.5 Unlike the massive datasets used to train LLMs, real-world financial datasets are often much smaller, leading to issues such as data scarcity and overfitting. For example, a global equity dataset with monthly data spanning 30 years contains just 3.6 million stock observations. That’s a sizable dataset, but still several orders of magnitude less than those available to LLMs.
As a result, AI’s impact in this space is via enhancing and augmenting established quantitative methods rather than replacing them.
By integrating LLMs with proven quantitative frameworks, you can ensure AI-driven insights are both reliable and actionable.
For Canadian private equity firms, the greatest value will come from a balanced approach that leverages the strengths of advanced AI models and robust quantitative methods, built on a strong data foundation.
2. Human judgment is more essential than ever
As AI becomes increasingly embedded in investment management, it’s clear that technology is here to augment rather than replace human judgment. Critical investment decisions still depend on intuition, negotiation skills, and the nuanced assessments of founders that AI simply can’t replicate. There are times when a human is required to look at a founder in the eye and explain why certain decisions must be made. A “human-in-the-loop” approach ensures that data-driven insights are enhanced by face-to-face evaluation and strategic interpretation.
We’re already seeing success with innovations like “chatting with the data room,” where AI surfaces hidden opportunities for investors, but every insight is validated by human expertise. Building processes that seamlessly combine AI analysis with human oversight is essential for sound decision-making.
According to the CFA Institute’s AI Pioneers in Investment Management report, the “AI + HI model” (where human intelligence is augmented, not replaced, by AI) has become the industry standard. Survey findings show that AI supports, but rarely supplants, human decisions. In fact, over 90% of asset managers are already using or planning to deploy AI, primarily to expand data sets and accelerate analysis.6 The evolving role of investment professionals is now centered on strategic interpretation and oversight, leveraging both machine and human intelligence to deliver superior outcomes.
For Canadian private equity firms, success will depend on ensuring technology and human expertise work together to achieve superior results.
3. Shifting from routine to strategy
AI’s ability to automate manual, time-consuming tasks is reshaping the investment landscape, allowing professionals to focus on alpha generation and strategic value creation rather than routine operations. The rise of agentic AI and autonomous agents marks a significant shift to actively executing multi-step tasks throughout the deal cycle rather than simply offering suggestions.
Within portfolio companies, AI-driven operational improvements deliver real benefits, such as faster revenue growth, optimized supply chains, and higher exit multiples. By automating routine processes, AI lets us reallocate human capital to more strategic activities, with success measured by gains in productivity and improved financial outcomes.
Looking ahead, the idea of the agentic AI-powered “Pilot” in the office points to a future where autonomous agents streamline sourcing, analysis, and reporting. This evolution positions AI as an indispensable partner in driving operational excellence and unlocking new sources of value across investment management.
Deloitte’s Agentic Enterprise 2028 highlights how pilots will address “more complex, end-to-end processes with human oversight and quality data supporting the effort.”7
Meanwhile, Goldman Sachs Asset Management offers a compelling example of how AI can drive both productivity and innovation in financial services. By deploying generative AI assistants, the firm enabled relationship managers to achieve a 30% increase in client outreach efficiency through “next-best-action” tools.8 Internally, AI assistants automated routine tasks like document summarization and knowledge retrieval, freeing teams to focus on strategic initiatives.
Can AI help boost Canada’s productivity?
Canada’s adoption of AI may trail global peers for now, but that gap creates a window for nimble firms to leapfrog the competition.
AI has the potential to drive national economic growth.
Private equity firms, with both the capital and a disciplined focus on value creation, are uniquely positioned to accelerate AI adoption in ways that individual companies often can’t achieve alone.
Of course, Canada’s smaller market size and collective risk aversion present real challenges. But generative and agentic AI technologies offer a way to level the playing field. To capture AI’s full value, you need to learn from global best practices while tailoring your approach to Canada’s unique strengths and realities.
What should Canadian PE firms and portcos do right away?
Start with these no-regret moves:
1. Establish a single source of truth
Invest in data quality and management as the foundation for any AI initiative. Reliable, well-governed data is essential for success.
2. Pilot AI projects and encourage experimentation
Begin with targeted initiatives linked to strategic objectives and measurable ROI. At the same time, be open to learning and experimenting. Early investment in AI can unlock significant future value.
3. Combine AI with human expertise
Develop “human-in-the-loop” processes to ensure decision-making and oversight remain grounded in human judgment.
4. Measure impact
Start with small, quick wins. Once you see positive results, accelerate and scale these processes.
5. Scale responsibly
Transition from pilots to enterprise-wide adoption, always prioritizing responsible, data-driven strategies.
Seize the AI advantage in PE
The fusion of AI and human expertise is unlocking new sources of value for Canadian investment firms.
By prioritizing return on investment (ROI), AI adoption becomes a no-regret move that delivers clear, measurable results.
Now is the time for Canadian private equity firms and their portfolio companies to build AI-enabled strategies that drive sustainable growth and enhance competitiveness.
To learn more about unlocking ROI and driving Canadian productivity through responsible AI adoption, connect with Deloitte’s leaders.
