Below is a summary of our discussion points, followed by a detailed overview of the key topics covered at our PE CFO lunch and roundtable in New York City on January 28, 2025.

Summary

Many firms are adopting AI to boost their operational efficiency, particularly in areas such as financial reporting, due diligence questionnaires (DDQs), compliance monitoring, data summarization, and expense management. However, several challenges impede broader implementation.

These include data privacy issues, the necessity of securing sensitive information, inconsistent data for model training, and resistance from leadership. Additionally, security concerns, such as AI-driven fraud and potential legal risks associated with AI-generated content, further complicate the adoption process.

There still seems to be a wide chasm between the promise of AI and its current reality. Ensuring data cleanliness and consistency presents a challenge like what has faced previous technological advancements.

Establishing tight controls on data privacy, such as personally identifiable information (PII), and the ability to “ring-fence” specific data sets must be addressed to gain the full benefit of AI. Without these elements, AI may not be fully implemented and only empower the senior leaders within an organization who possess the necessary “clearance” and trust.

Key Discussion Topics

1. Adoption of AI & Technology

  • Several firms are integrating AI to enhance operational effectiveness, particularly in financial, DDQ, and compliance tasks.
  • Data privacy and security remain a key concern, especially for firms handling sensitive information like healthcare data (healthcare portcos) and other PII.
  • AI is being used for tasks like data summarization, meeting notes, and expense management.
  • Many firms are experimenting with AI for DDQs, compliance monitoring, and financial reporting.

2. Challenges with AI Implementation

  • There is a need to “ring-fence” AI models to ensure sensitive data isn’t exposed.
  • Difficulty in training AI models with inconsistent or incomplete data.
  • Resistance from leadership or compliance officers regarding AI adoption.
  • Practical limitations of AI in automating certain financial and regulatory tasks.

3. Efficiency Gains & Cost Savings

  • AI helps to automate tasks such as accounts payable processing and vendor management.
  • Many firms are assessing the cost-benefit tradeoff of AI tools and whether they reduce headcount or allow for better resource allocation.
  • While firms think that implementing AI will not decrease total staffing levels any more than outsourcing and automation have already done, it may alter the skill sets they seek in future hires.

4. Vendor & Consultant Insights

  • Some firms rely on vendors to develop AI tools rather than building them in-house.
  • Consultants like West Monroe and Lionpoint provide sound guidance on AI strategy and implementation.
  • Firms are cautious about becoming early adopters or being a test case for new AI products.

5. Portfolio Company Applications

  • AI is increasingly used in sales pipeline management, patient outreach, and financial modeling within portfolio companies.
  • Companies are leveraging AI-driven search tools to improve internal data accessibility.
  • Portfolio company CFOs and IT teams meet regularly to discuss AI and share best practices.

6. Security & Compliance Concerns

  • Cybersecurity risks include AI-powered fraud (such as deepfake voice cloning for wire fraud).
  • Strict data access policies limit how AI can be implemented.
  • AI-generated meeting summaries create legal risks due to discoverability in audits.

Software Mentioned

  • Copilot – AI-powered assistance for summarization and data analysis.
  • Anthropic – AI tool provider.
  • Cyberhaven – Security tool that monitors data movement across networks.
  • Lupio – Used for DDQs and collaborative data storage.
  • Zoom AI – AI-powered meeting summarization.
  • Glean – Internal search tool for networked data.
  • DealCloud – CRM and deal pipeline management tool with AI features.
  • Anaplan – Financial planning and budgeting tool.
  • Snowflake – Cloud data warehousing solution.
  • SiftScore – AI-driven talent search tool.
  • Trace Vista – AI-based expense review system.

Vendors & Consulting Firms Highlighted

  1. West Monroe – Consulting firm specializing in AI and technology strategy.
    • Helps firms assess AI tools and implement AI strategies across portfolio companies.
    • Provides insights into market trends and AI adoption.
  2. Lionpoint – Consultant for technology implementations.
    • Works on Anaplan deployments and AI solutions for asset management.
  3. Deloitte – Conducted system audits to reduce redundancy and improve efficiency.
  4. Blue Flame – AI-driven solutions for investment materials and compliance.
    • Seen as an emerging player, but firms are hesitant to adopt early.
  5. ACA Aponix – Cybersecurity and compliance advisory firm.
  6. Prime Brokerage Consulting Teams – Hedge fund-focused technology advisors.
  7. Gartner – Provides technology research and benchmarking for AI adoption.
  8. Consero – Helps with vendor negotiations and software purchasing optimization.

Overall Observations on Vendors & Software

  • AI adoption is slow, with most firms still in the evaluation and experimentation phase.
  • Security and compliance are major concerns, limiting how firms can use AI tools.
  • Microsoft Copilot is widely used, but concerns exist around data exposure.
  • West Monroe and Lionpoint are trusted consultants frequently used for AI strategy, insights, and implementation.
  • Cyberhaven and Blue Flame are emerging but not yet widely adopted.
  • Glean and Zoom AI tools are seen as beneficial for efficiency but require careful implementation.
  • Anaplan is effective but took years to integrate for budgeting and reporting.
  • Snowflake’s data integration capabilities remain challenging due to legacy system constraints.