A clear-eyed view of Gen AI for the private capital industry
Jul 17, 2024
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Join Ben Ellencweig, a senior partner at McKinsey specializing in alliances at QuantumBlack, as he delves into the transformative role of generative AI in private equity. He discusses how this technology can enhance operational efficiency and navigate diverse data challenges. The conversation also sheds light on the essential balance of human oversight and accountability to mitigate risks. Personal stories weave in creative possibilities, encouraging listeners to explore AI's impact not just in business but also in personal projects.
Generative AI offers private equity firms the potential for enhanced operational efficiency through the creation of new content, differing from traditional analytical AI.
Successful integration of Generative AI requires a strategic approach to balancing quick-impact projects with aligning initiatives to long-term business goals.
Deep dives
Understanding Generative AI
Generative AI differs from traditional analytical AI in that it creates new content rather than merely analyzing existing data. Analytical AI focuses on improving speed and accuracy for tasks like customer segmentation and sales forecasting, while Generative AI can produce original material such as music, text, or software code. For example, it may aid in drug discovery by generating new chemical compounds or enhance marketing efforts by creating tailored content. The distinction is critical for private equity firms as they look to leverage this technology to enhance their operational efficiency.
Current Use Cases and Adoption Levels
There is significant experimentation with Generative AI among private equity portfolio companies, but few have fully integrated it into their operations. While approximately 60% of operators in a recent forum acknowledged their companies were exploring Generative AI, only about 5% reported using it at scale. This highlights a common trend where companies struggle to move from pilot testing to impactful results due to challenges in data governance, change management, and broader organizational adoption. As 2024 approaches, it is expected that firms will transition from experimentation to scaling applications with tangible business impact.
Strategic Approaches to Generative AI Implementation
Private equity firms are advised to adopt a strategic approach when considering how to implement Generative AI, focusing on both smaller, quick-impact projects as well as larger, transformative workflows. Simple applications, such as automated call summarization or employee engagement bots, can serve as entry points to demonstrate value without overwhelming costs. On the other hand, it is essential to align these initiatives with the firm's core business processes and long-term goals, ensuring that efforts are not just tech-driven but strategically grounded in the organization's mission. Measurement of success should involve establishing baselines to assess effectiveness and avoid complacency with superficial improvements.
Addressing Risks and Ethical Considerations
As firms begin to integrate Generative AI, it is crucial to understand the associated risks, including biases, inaccuracies, and ethical implications. This technology should be viewed through a lens of critical evaluation, akin to assessing the performance of an intern who produces initial drafts of content but requires human oversight. Companies must also consider the environmental impact of data centers that support AI operations and ensure alignment with ESG compliance. By maintaining a human-in-the-loop approach during the implementation of Generative AI, firms can better harness its potential while mitigating risks.
In this episode of Deal Volume, McKinsey partner and host Brian Vickery speaks with Ben Ellencweig, a senior partner in McKinsey’s Stamford office. Ben leads alliances and partnerships for QuantumBlack and spends much of his time working with private equity (PE) firms and their portfolio companies. In this discussion, they get beyond the hype surrounding generative AI (gen AI) and discuss its implications for PE stakeholders.