Speed matters in M&A, but it rarely sets the pace on its own. Deal teams have learned to work through big shifts, from a pandemic surge to inflation, higher rates, and tighter review. In 2025, the market showed steady progress even with geopolitical change and new rules.
Buyers and sellers focused on deals that strengthened operations and moved digital plans forward. On Datasite, new global deals rose 9% year over year in 2025.
That pace has held into 2026. Conflict and uncertainty still make some leaders cautious. Even so, new deals on Datasite rose 6% globally year over year in the first two months of the year. Industrials, transport and defense, and technology, media, and telecoms lead much of that activity. AI sits in the center. Companies buy AI capabilities, and deal teams use AI to run deals. That second use case changes the daily grind first.
Agentic AI in diligence
AI now cuts the time it takes to get answers. New agentic tools can take a task, break it into steps, and work through a full set of deal files. They scan large folders, sort documents, pull key terms, and draft clean summaries. They spot patterns and outliers that teams used to find late, if at all. They also connect facts across finance files, customer contracts, HR policies, and compliance records. That gives bankers, lawyers, and analysts a faster start and a clearer view of risk.
AI can also help deal teams turn review into action. They can use it to draft issue lists or move clean numbers into models and templates. With AI-driven automation, deal teams can close transactions 22 days faster than the industry average. Due diligence often costs about $100,000 a week. Saving 22 days
could mean more than $300,000 in cost savings, even before factoring in lost time for leaders or risks from market fluctuations. But those gains often stay inside the diligence lane. The full deal still waits on alignment.
Coordination Wins
AI can cut days or weeks from review. Then the deal hits its real constraint. The close depends on coordination across buyers, advisors, and internal decision-makers, not on how fast teams can read.
Run a competitive process and the coordination load can rise fast. Sellers and advisors manage several buyers at once. Each buyer brings a different team, a different playbook, and different calendar limits. AI can surface insights in hours. People still need time to meet, ask questions, agree on answers, and make tradeoffs. The process can move through gates, including management sessions, Q&A rounds, term talks, financing work, and then investment committee approval.
By design, investment committees slow deals. They test the story and challenge assumptions. They weigh risk across brand, rules, operations, and integration. Better data helps them decide. AI helps teams bring that data together. But committees still need meetings, debate, and clear sign-off. That puts a premium on process. Keep outputs clear, sourced, and easy to defend. Then set rules for how teams use AI.
Set AI guardrails
Start by setting clear AI guardrails. Teams still define what agentic AI means in day-to-day deal work. Different groups use different tools, and no single standard exists yet. Set rules now. Decide what AI can do on its own. Decide what needs human review. Keep a clear record of sources.
With those guardrails in place, put AI to work where it saves the most time. Diligence is shifting from hunting for files to testing conclusions. AI can flag a change-of-control clause fast. Lawyers still judge if it can block a deal. AI can flag revenue concentration fast. Bankers and operators still decide if the risk is acceptable. AI can draft a view of regulatory exposure. Leaders still weigh the upside against the burden. Make AI your first pass. Then lock those gains into the way you run the deal.
Build the Workflow
To lock in those gains, build a workflow that teams can run the same way on every deal. Expect AI to keep lifting output across the deal team. It will help bankers, corporate development professionals, lawyers, accountants, and analysts work faster and stay focused. It will not remove the need to align many people around one decision. In 2026, deals should follow strategic conviction more than a simple market rebound. Policy fit, resilience, and long-term position will decide which deals win. Use AI to get to clarity faster. Then execute with discipline across all stakeholders.
Put it all together and the lesson is simple. AI speeds up diligence in a clear and lasting way. But closing still depends on people. Buyers, advisors, committees, regulators, and executives must line up on price, terms, timing, and risk.
Agentic AI will keep removing friction from review and analysis. It can cut cost and reduce rework. Pair that speed with secure collaboration, clear decision rights, and tight execution and faster diligence will lead to smarter decisions.
