Collaborate, Don’t Delegate: Best Practices for Using AI in Deal Processes

Introduction

Artificial Intelligence (AI) is impacting various industries, and private equity is no exception. Historically, dealmaking has been a human-centric endeavor, but the integration of AI can significantly enhance efficiency and accuracy in the deal process. According to IBM, "Augmented human intelligence means that the use of AI enhances human intelligence, rather than operating independently of, or replacing it." This perspective is crucial as it underscores the role of AI as a complement to human expertise rather than a replacement.

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The Role of AI in Private Equity

Private equity analysts often work long hours, primarily engaged in conducting diligence, compiling data, and drafting documents. These tasks are time-intensive and can benefit immensely from AI integration. AI can process vast amounts of data quickly, identify potential investment opportunities, and assist in drafting initial documents, thereby freeing up analysts to focus on more strategic aspects of dealmaking.

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Best Practices for Collaborating with AI

1. AI as a Complement: AI should be viewed as a complement to human expertise, not a replacement. Major AI vendors describe their technology as ‘assistants’ or ‘co-pilots,’ emphasising their supportive role.

2. Data Analysis and Synthesis: AI aids analysts in analysing data sets and synthesising multiple sources of information. By processing vast amounts of data, AI can identify potential investment opportunities that might have otherwise been overlooked.

3. Human Oversight: Human oversight remains crucial. Analysts and management must verify AI outputs and take responsibility for final decisions. AI should be seen as an accelerant.

4. Relationship Building: Deal teams must continue to hold meetings with management and build relationships—tasks that AI cannot replace. ‍

5. First Draft Assistance: AI can help move from a blank page to a first draft, providing a valuable springboard from which human reasoning and insight can be added.

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Best Practices for Augmenting with AI

1. Harmonious Augmentation: Integrate AI at key points in the deal process to remove toil and create capacity for more value-added work. ‍

2. Human-AI Interaction Design: Design human-AI interactions to balance human oversight across the AI lifecycle. Address biases and promote human accountability and agency over AI system outcomes.

3. Employee Training: Provide comprehensive training and reskilling programs for employees. ‍

4. Task-Specific AI Tools: Ensure the AI tool is tailored to the specific task and organization. When used within its capabilities, AI can make teams 40% more productive. Using generalist tools for specialist tasks, however, can reduce productivity by 19% (MIT Sloan). ‍

5. AI Collaboration Policies: Publish policies that outline the key challenges, opportunities, and personal obligations for collaborating with AI. Pair these policies with the implementation of a workflow to ensure maximum team engagement.

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Practical Applications

1. Data Analysis and Synthesis

AI-driven data analysis tools can process large datasets to identify trends and opportunities that human analysts might miss. For instance, AI can analyse market conditions, historical data, and individual investor profiles to tailor investment portfolios, aligning them with specific risk tolerances and investment goals.

2. Due Diligence

AI can streamline the due diligence process by employing predictive and prescriptive analytics. By analysing past transactions, market trends, management team psychographics, corporate culture, and company performance data, AI can forecast the future success of potential investments with greater accuracy. This reduces the risk of unsuccessful investments within portfolios.

3. First Draft Assistance

AI tools can assist in drafting initial documents, such as investment memos and reports. This allows analysts to start with a well-structured draft, which they can then refine and enhance with their insights and expertise.

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Challenges and Considerations

1. Data Privacy and Security

With the vast amounts of data processed by AI tools, there are real concerns about data privacy and security breaches. Companies must ensure robust data protection measures to prevent unauthorised access and potential misuse of sensitive information.

2. Ethical Use of AI

AI lacks human judgment and intuition. It is crucial to maintain human oversight to evaluate qualitative factors and understand the nuances that can impact a deal’s success. Additionally, relying heavily on AI may inadvertently lead to non-compliance with various regulatory frameworks governing transactions.

3. Regulatory Compliance

The regulatory landscape for AI is still evolving. Companies must stay ahead of new regulations and ensure their AI systems comply with all applicable laws. This includes addressing biases in AI algorithms and ensuring transparency in AI decision-making processes.

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Conclusion

By adhering to these best practices, deal teams can effectively integrate AI into their workflows, enhancing their decision-making capabilities while maintaining responsibility for the final output. AI, when used as a complement to human expertise, can significantly improve efficiency and accuracy in the deal process, allowing analysts to focus on more strategic and value-added tasks.

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References

• IBM. "Augmented human intelligence means that the use of AI enhances human intelligence, rather than operating independently of, or replacing it." IBM

• MIT Sloan. "Using generalist tools for specialist tasks can reduce productivity by 19%." MIT Sloan

• Harvard Business Review. "Collaborative Intelligence: Humans and AI Are Joining Forces." Harvard Business Review

• Pew Research Center. "Improvements ahead: How humans and AI might evolve together in the next decade." Pew Research Center

• Forbes. "Futuristic Finance: AI's Seductive Power In Reshaping Private Equity." Forbes

• Intralinks. "Hot Deals, Cool Tech: AI-Powered, Automated Due Diligence for Enhancing M&A Decision-Making." Intralinks

• Middle Market Growth. "AI: The Future of M&A." Middle Market Growth

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By integrating AI thoughtfully and responsibly, private equity firms can harness its full potential to drive better outcomes and create more value in their deal processes.