One of the conference's standout sessions was the panel The New M&A Engine: AI, Data, and the Future of Deal Making, which drew on perspectives from across the industry to examine how artificial intelligence and data are reshaping the modern deal lifecycle. The panel brought together Bryan Keller, Vice President at Datasite; Pat Donoghue, National Managing Partner, Corporate Finance & Transaction Advisory Sales at BDO; and Craig Buffkin, Vice Chair at Panorama and Managing Partner at Buffkin/Baker. Their conversation was moderated by Scott Peters, Managing Partner at Growth Catalyst Partners. Together they explored where AI is delivering real results across the deal lifecycle and what deal teams need to prepare for next. 

A front-row seat to shifting deal dynamics 

Datasite's vantage point at the center of global M&A has revealed several important shifts already underway in 2026. Across the panel, a consistent theme emerged: the pace and complexity of dealmaking have both accelerated meaningfully. Deal kickoffs are rising across regions, reflecting renewed market confidence, while preparation and diligence timelines continue to compress. At the same time, document volume in data rooms has grown by roughly 40%, creating a real tension between speed and thoroughness. 

Keller pointed out that deal teams are now being asked to process more information with fewer people on tighter timelines, a combination that is fundamentally changing how diligence gets done. Panelists broadly reinforced this observation: the bar for execution quality has never been higher, even as the resources and time available to clear it continue to shrink. 

Where AI Is delivering the most value today 

While AI is influencing every stage of the deal lifecycle, deal execution and due diligence are seeing the most immediate and tangible impact. Historically the most labor-intensive phase of M&A, diligence is now being transformed through AI-powered capabilities such as document classification, searchable review, anomaly detection, and automated risk flagging-tools that eliminate manual steps, reduce errors, and allow teams to move through increasingly complex datasets with greater confidence and defensibility. 

Panelists agreed on what differentiates purpose-built deal technology from general AI tools: source transparency and auditability. In high-stakes diligence environments, accuracy and accountability aren't optional features, they are foundational to how AI gets trusted and adopted in deal workflows. 

This is the gap Datasite has built Blueflame AI and Datasite MCP to close, bringing AI directly into the data room with traceable, auditable references, while keeping sensitive deal materials inside Datasite's secure environment.

The AI-equipped buyer advantage 

One of the clearest themes across the panel was how differently AI-enabled buyers are showing up in today's processes. Before a CIM is even released, sophisticated buyers are using AI to build deep views of target companies, competitors, and markets. By the time a data room opens, these teams often arrive prepared to focus on strategic upside rather than baseline discovery. 

Inside the data room, that difference becomes even more pronounced. AI-equipped buyers are ingesting significantly more content, revisiting materials more strategically, and moving through diligence cycles faster than their peers. This evolution is reshaping expectations not just for buyers, but for advisors and sellers alike. Panelists noted this dynamic is creating a two-tier market: those leveraging AI to prepare and execute faster, and those still operating on legacy timelines and workflows. 

Getting ahead: preparation as a competitive advantage 

For any party considering a transaction, whether on the buy side or sell side, the panel's message was consistent: preparation needs to start well before going to market, and it needs to be grounded in accurate insight, not just organization. 

Panelists emphasized that sell-side teams who run the same analytical lens on themselves that buyers will apply gain a meaningful edge, identifying issues early, strengthening disclosures, and avoiding costly surprises during live processes. As deal teams increasingly deploy AI across every document and dataset they receive, those who run that same analysis on themselves first arrive at the table with a clear advantage. 

AI as an operating mindset, not a point solution 

Looking ahead, the panel framed AI adoption as a broader operating shift rather than a standalone tool decision. Over time, AI will continue to automate standardized analysis and routine workflows, freeing junior professionals to engage earlier on judgment and relationship-building. For senior dealmakers, AI-powered agents will act as force multipliers, enabling teams to evaluate more opportunities without sacrificing rigor. 

Panelists agreed that the biggest risk for any firm is opting out of AI adoption altogether. 

The consensus from the panel: firms best positioned to win are those that combine high-quality data, strong governance, and human judgment, all supported by AI that is purpose-built for the deal environment. 

AI isn't replacing dealmakers, it's raising the bar for how they operate. And Datasite is building the tools to help you meet it. 

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