Private equity (PE) players, particularly those with ventures/early-stage programs, have already identified artificial intelligence (AI) as a focus area of investment going forward—and for good reason:

  • The number of financing transactions to AI start-ups increased 10x over the last six years.[1]
  • The share of companies using AI is expected to grow from 38% today to 62% in 2018.[2]
  • The market for AI solutions is forecast to grow at a CAGR of >55% between 2016 and 2020.[3]
  • A 2016 study by Accenture and Frontier Economics suggests that AI has the potential to boost rates of profitability by an average of 38 percent by 2035.[4]

But how will AI impact the private equity industry itself? I see three main areas that could be affected:

Reshaping the private equity industry

Most investors look at a range of factors when assessing a PE manager (e.g., investment track record, team experience, key person provisions)—but such assessments are often performed in isolation for each variable, with overall decisions made based on professional judgement.

To minimize the probability of suboptimal outcomes, some investors are starting to use AI to assess PE offerings, drawing on a range of qualitative and quantitative variables to estimate the odds of achieving superior risk-adjusted returns.

As this approach gains traction, it could enable greater transparency into a manager’s ability to drive alpha—which could lead to a redistribution of value across the PE value chain. High-performance managers would likely see increased demand for their services, and could command higher fees from investors. Low-performance managers might be forced to reduce their fees or even go out of business.

For investors, this will likely mean lower return volatility across their private equity portfolios. For institutional investors with captive managers, it could mean better measurement of relative performance and compensation alignment. And for managers, it would mean greater incentives to perform.

Improving investment decision-making

A handful of PE investors are already using AI for security selection, mostly in the venture capital space. A couple of interesting examples include:

  • Hone Capital, the Silicon Valley-based arm of CSC Group (one of the largest venture capital/private equity firms in China), partnered with AngelList (an online platform for startup investments) to use AI to support the investment team in selecting seed investments.[5]
  • Deep Knowledge Ventures, a Hong Kong life science venture firm, appointed—with a vote—an AI system called VITAL to its investment committee. The system makes its decisions by scanning prospective companies’ financing, clinical trials, IP and previous funding rounds.[6]

Although it’s unlikely that AI will have the same disruptive impact on PE that it’s had on quantitative hedge funds, there’s no doubt that machine-assisted decision-making is on its way. For managers, that will drive a greater need to invest in data—commercially available sources at first, followed by proprietary sources down the line—and in cybersecurity capabilities.

Redefining the private equity career path

The PE career path has traditionally been very linear. One starts out as an analyst, working in the realm of financial modelling. Over the years, he/she gradually develops “deal instincts” and becomes more involved in driving the due diligence process, executing deals and developing new business.

However, AI algorithms can already perform many tasks faster and more efficiently than human PE analysts (e.g., assess a company’s probability of success). As their numbers decrease with AI adoption, the industry’s ability to form new professionals will likely be hindered, leading to a fundamental redesign of the PE career path (e.g., more professionals joining from the industry at the VP/director level).

AI and your firm

AI is poised to fundamentally reshape not only the PE industry structure, but its investment processes and talent model too. As the technology and data sources continue to improve, early adopters will find themselves in a good position to extract sustained and meaningful returns from their AI investments.

Curious what your next step should be? Let’s discuss. You can reach me directly at paulo.salomao@accenture.com.

 

[1] https://www.forbes.com/sites/louiscolumbus/2017/06/11/how-artificial-intelligence-is-revolutionizing-enterprise-software-in-2017/#95f601c24638
[2] http://www.datascienceassn.org/sites/default/files/Outlook%20on%20Artificial%20Intelligence%20in%20the%20Enterprise%202016.pdf
[3] https://www.forbes.com/sites/louiscolumbus/2017/06/11/how-artificial-intelligence-is-revolutionizing-enterprise-software-in-2017/#377459b32463
[4] https://www.accenture.com/us-en/insight-ai-industry-growth
[5] https://www.forbes.com/sites/rebeccafannin/2017/08/13/china-vc-fund-relies-on-machine-learning-to-invest-in-u-s-startups/#4de490756f05
[6] https://outsideinsight.com/insights/outside-insight-in-venture-capital/

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