AI promises to provide private equity firms with a competitive advantage—as long as it is suitably integrated into existing workflows. In the fiercely competitive world of private equity, a tool that optimises operations and boosts productivity is a holy grail, and studies are already revealing the power of AI tools. One study by researchers at MIT revealed that professionals who used generative AI solutions saw their productivity improve by almost 60 per cent.
However, integration is not as simple as it may first seem. Effectively harnessing the power of AI today requires a clear integration framework tailored to your firm’s unique workflows because not every task will be suitable for AI at this moment in time.
AI and Private Equity: Integrating AI Into Existing Workflows
Not every task or process will be well-suited to AI, at least for now. Despite the “quick fix” narrative that some are peddling, successfully integrating AI tools into your workflow takes time and careful planning. AI prompt engineering has emerged as an essential role in fully leveraging generative AI’s capabilities and integrating AI tools into workflows. Even with off-the-shelf AI solutions, prompt engineers bring valuable expertise to the table—they fine-tune prompts to align with the firm’s objectives, optimise the performance of AI tools and, vitally, help firms integrate AI within their existing workflows.
To understand if/how AI can assist with workflow steps, you need to break up tasks into smaller components. Let’s break down where AI can be integrated into the various stages of the deal cycle:
Deal sourcing and origination with AI
The private equity deal sourcing process leans heavily on human interactions and expertise, namely the firm’s professional networking activities, industry relationships, direct outreach and market research. However, this process is time-consuming and costly.
Private equity firms can integrate AI into the deal-sourcing workflow in various ways. For example, expediting the direct outreach process by drafting AI cold emails and adding personalised details. But that’s just the beginning—AI can also be used to analyse large amounts of data, including but not limited to financial reports, news updates and market trend data to identify potential deal opportunities.
Additionally, AI may allow firms to gain insights into industries or companies that are not immediately apparent through more traditional research methods or deal activity databases. After all, AI can rapidly glean insights that human analysts may miss or analyse data that would simply take humans too long to analyse. The result is faster and more efficient identification of potential deals, allowing firms to get one step ahead of their competitors to obtain lucrative opportunities.
Rich Klee, Product and Technology Director at Palladium highlighted the capabilities of AI in streamlining the investment analysis workflow, stating, “AI can be used to ingest new investment memorandums to provide a critique of them by pulling on both historical and specialist real-time data.” Not only can AI play a role in sourcing deals but also in accessing their viability.
Due diligence with AI
The traditional due diligence process comprises various tasks, including but not limited to document review, interviews, background checks, visits and more. While it’s not currently possible to automate the entire workflow, there are areas that would benefit from AI integration. Ben Martin, Global Head of Transaction Advisory (Growth) at Palladium, explained that AI will make the due diligence process more efficient. “There is a huge opportunity for efficiency. Private equity firms are able to use AI to supplement their workflows and provide highly privatised access to achieve very tailored outputs.”
AI systems can save firms significant amounts of time during the due diligence process by boosting workflow efficiency and reducing risk. For example, during the document review phase, AI systems can scan documents for potential liabilities and risk factors in a fraction of the time it would take a human. Additionally, AI can scrutinise the target asset’s financial statements and tax returns to flag potential discrepancies.
Portfolio management with AI
Today, portfolio management is a very hands-on process—but AI has the power to optimise some of the workflows involved. For example, post acquisition, AI can process and analyse data relevant to portfolio performance, including financial and operational data, news and social media sentiment, competitor company growth and industry-specific trends to give a rapid fire, accurate and standardised overview of asset performance. With faster access to essential decision-making data, the potential to mobilise returns-generating incentives increases rapidly and performance overall might be increased.
AI’s portfolio management capabilities don’t end there. You can also use AI to create scenario analysis reports to simulate scenarios, risk assessment reports that highlight the risk profile of each company, and formulate exit strategies by evaluating the current market conditions and comparable exits to create a data-driven exit plan. Integrating AI into the portfolio management stage of the private equity lifecycle can result in more efficient workflows and support a proactive portfolio management approach.
Plus of course there are numerous ways in which integrating AI into portco systems and operations might bring efficiencies, improve productivity and allow for innovation in sectors that might otherwise remain stagnant. Though discussions around how AI in certain sector scenarios can make or break a firm’s proposition in this rapidly accelerating tech environ is a wider piece which can be discussed separately.
Final Thoughts: Integrating AI into Existing Private Equity Workflows
Private equity firms are racing to understand the impact of advances in AI, and firms have so far only made tentative progress using AI to improve portfolio company operations. Firms are understandably taking a cautious approach to integrating AI into their workflows, as hasty AI adoption could result in security breaches, poor data quality and reputational damage.
Successfully integrating AI tools, like Palladiums’s privacy-first conversational AI, PrismGPT, into existing workflows requires a holistic approach that takes into account your firm’s current capabilities and unique workflows. That’s precisely why Palladium launched the AI Impact Assessment—to help private equity firms get AI integration right.
CEO James Prebble explained, “By launching our AI Impact Assessment service, we aim to provide our private equity clients with the insights and guidance they need to make informed decisions about the value and impact of AI on their investments. Our clients can have confidence in our ability to help them navigate the complex landscape of AI adoption and harness its power for future growth.”