[Fatima Rabahallah]

AI, data analytics, and virtual deal rooms are transforming the due diligence process. What tools or approaches have you found most effective in improving accuracy and reducing costs? What risks come with relying too heavily on technology?

[Saeed Zeinali]

Great topic. The technology shift in DD is real, but the conversation often focuses on shiny tools rather than practical application.

What’s Actually Working

Virtual data rooms with AI redaction and auto-indexing save significant time. The analytics showing which documents reviewers spend time on can surface concerns you might otherwise miss.

For contract review, NLP is probably the highest ROI application right now. Scanning hundreds of agreements for change of control provisions or termination rights used to take weeks. AI does the first pass in hours.

The Real Risks

The danger isn’t the technology. It’s the false confidence it creates. I’ve seen teams accept AI-generated summaries without spot-checking, only to discover missed nuances that affected deal terms.

There’s also a pattern recognition problem. AI trained on historical deals can miss novel risks in emerging industries or unconventional business models.

Technology should surface information faster, not replace critical thinking.

[RaviN]

GenAI tools can be quite helpful in identifying culture and fit issues in M&A. Numerical analysis for financial due diligence is still a bit wonky and requires a lot of verification and validation. GenAI capabilities for conducting due diligence for strategic fit is also maturing quite rapidly.

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