Private Equity Firms Embrace AI for Their Portfolio Companies

By Drake Paulson, VP Strategic Partnerships, Anduin

The integration of Artificial Intelligence (AI) into business operations has moved beyond mere speculation to tangible ROI. Recognizing this shift, private equity firms are eager to position their portfolio companies at the forefront of reaping these benefits. Investment managers and venture capitalists are already trying their hand with AI, albeit on a limited basis. However, they have more ambitious goals to significantly enhance the growth and efficiency of their portfolio companies with AI. And it makes sense. A striking 87% of businesses actively utilizing AI report noticeable improvements in revenue and cost reductions.

This enthusiasm is not without strategy; private market firms have been diligently searching for AI applications that promise the highest return on investment (ROI). This search is shaping up to be a crucial element in these firms’ strategies to outperform the market. Some of the larger players have gone as far as establishing dedicated committees aimed at accelerating the development and implementation of AI strategies within their portfolio companies.

The push towards adopting cutting-edge technology is not a new role for private equity firms. They have historically played a pivotal role in guiding their portfolio companies through technological transformations—be it transitioning to cloud computing, embracing mobile technology, integrating e-commerce into traditional retail models, or automating key business processes. 

Today, the focus has shifted to capturing the early-mover benefits offered by AI. With a palpable sense of urgency, these firms understand that quick action is essential to fully leverage AI’s value-enhancing potential. Given the nascent stage of AI’s application in various business domains, many firms are adopting a trial-and-error approach to pinpoint the most effective use cases for AI. This phase of exploration is critical for identifying where AI can deliver the greatest impact.

How private portfolios use AI today

AI-driven solutions are already in development or up and running in many private portfolio companies, and promising early application areas include:

 

• Marketing. AI helps marketers to better understand customer behavior, market trends, and competitive dynamics. It accelerates development of targeted marketing campaigns, enhanced product offerings and creating personalized customer experiences at scale. 
• Supply chain optimization and logistics. For companies involved in manufacturing or distribution, machine-learning AI optimizes routes, saving fuel and other costs, and finds fast answers to inventory management, shortages and bottlenecks. Overall, AI  in supply chain management reduces waste and smooths operations. 
• Quality control and predictive maintenance. Manufacturing and shipping are exciting areas for AI-driven machine vision, watching products from assembly to transport and receiving. AI systems can also observe a truck tire for 50,000 miles, or stare at a skyscraper support column for decades to detect signs of failure. 
• Human resources. AI is instrumental to scaling up recruitment processes, complete talent search procedures faster, search for red flags in short-list candidates, and avoid liability issues in recruiting.
• Organizational structure and staffing. AI can apply a private equity firm’s trusted formulas to workforce reorganization, eliminating redundant roles and reallocating resources to support company strategy.
• Analysis and decision-making. Use of AI in large-scale analysis for data-driven decision-making in challenging areas such as pricing. AI has unmatched ability to combine text and non-textual information from many sources for improved management analytics. It excels at catching subtle red flags and risk factors, and helps boost performance across a business.
• Revenue enhancement. AI-powered recommendation engines and machine learning algorithms increase the lifetime value of customers. AI identifies  opportunities to cross-sell, enter new markets and adapt product lines. 
• Financial engineering. Analyzing and selecting optimal financial structures, leveraging debt to increase return on assets. AI speeds up management decisions in complex financial scenarios. 

Balancing Innovation with Risk

Private equity firms have the unique opportunity to foster a culture that prioritizes digital transformation and AI innovation across their portfolio companies. By actively seeking and aggregating expertise in both machine learning and generative AI, these firms are positioning themselves to enhance their skills and strategies significantly. One effective approach is to invest in companies that are at the forefront of AI adoption, thereby gaining access to their knowledge and capabilities and subsequently disseminating these across the entire portfolio. Another strategy involves supporting a portfolio company in the comprehensive implementation of AI solutions, then sharing the lessons learned and successes achieved with other companies within the portfolio.

However, it’s crucial to acknowledge the inherent risks associated with AI. Private equity firms can play a pivotal role in mitigating these risks by creating a knowledge-sharing ecosystem. This collective wisdom can help portfolio companies navigate the complexities of AI deployment, such as avoiding biases in machine learning, preventing generative AI “hallucinations,” steering clear of copyright infringement issues related to training data, and ensuring the accurate training of Large Language Models (LLMs). By pooling resources and expertise, private equity firms can guide their portfolio companies through the challenges of AI adoption, ensuring both innovation and risk management are balanced effectively.

Accelerating AI Integration to Boost Portfolio Company Performance

In the coming years, private equity managers will intensively focus on ensuring their portfolio companies not only adopt AI but also leverage it aggressively to enhance operational efficiency and accelerate business growth in areas where it can have the most significant impact. Forward-thinking investment firms recognize AI’s potential to unlock exceptional value from existing assets. Moreover, by accumulating and utilizing data assets effectively, these firms see an opportunity for their portfolio companies to not only enhance their value but also potentially launch new business ventures.

AI as a Competitive Advantage

As these investment firms gain insights into the most effective AI applications, they are committed to sharing this knowledge and these capabilities with the management teams of their portfolio companies. This proactive distribution of insights and tools is designed to empower these companies to outpace their competition. Through a combination of strategic AI deployment and shared learning, private equity managers are setting the stage for accelerated growth and innovation across their portfolios.

AI within portfolio companies is still in its nascent stages, yet the urgency to leverage it is real. Portfolio companies are encouraged to collaborate with their investors to identify the areas where AI can deliver the most significant benefits. These areas typically include operational enhancements, financial structuring, strategic planning, talent management, and governance—sectors where private equity firms traditionally play a vital role.

The drive towards AI adoption may be fueled by a clear vision for its future role in the portfolio or by a fear of missing out. Regardless of the motivation, the imperative to act is immediate. AI technology, even more so than cloud computing in its formative years, has quickly become an essential component for businesses. It is critical for private equity firms to acquire and nurture AI expertise to deploy across their portfolios effectively.

The benefits of integrating AI are manifold, promising not only to build competitive edges but also to enhance the value of data and other assets significantly. Private equity firms that hesitate to embrace AI and fail to equip their portfolio companies with these capabilities risk falling behind in a rapidly evolving market landscape.