By Jerome Pottier, EMEA Chief Revenue Officer at Datasite
Artificial intelligence (AI) is transforming mergers and acquisitions (M&A) far beyond automation. The rise of agentic AI, systems that autonomously learn, adapt, and act, marks a turning point in how deals are sourced, evaluated, executed, and integrated. Rather than simply assisting deal teams, these AI agents operate as autonomous co-pilots, enabling faster, more strategic decisions across the deal lifecycle.
Industry Adoption and Efficiency Gains
The financial and professional services sectors are embracing this shift. A Datasite survey of 500 M&A professionals found that more than half expect AI to halve deal timelines, and two-thirds are prioritizing AI tools for operational improvements this year. Correspondingly, new global deals initiated on Datasite rose 11% year-on-year in Q3 2025, while median diligence times shortened to 160 days, signaling real efficiency gains even amid increased complexity.
This trend aligns with broader industry indicators. Bain & Company and BCG reports show that AI-driven deal acceleration now spans analysis, diligence, and integration phases, with top private equity firms already deploying multi-agent systems for data-informed bidding. Overall, agentic AI spending is projected to exceed $155 billion by 2030, representing one of the fastest-growing enterprise technologies globally.
How Agentic AI Works in M&A
Agentic AI merges machine learning, large language models (LLMs), and decision engines to autonomously execute core M&A functions. Current tools from Datasite, Grata and Blueflame AI
already enable deal teams to:
- Identify and qualify acquisition targets using dynamic market intelligence
- Analyze earnings and SEC filings in real time
- Automate redaction and compliance reviews with precision
- Categorize and summarize diligence documents at scale
- Model valuations dynamically based on new market data
- Track post-merger milestones and cultural integration health
Recent integrations, including Datasite linking with Grata and Sourcescrub in 2025, are enabling real-time company intelligence inside live transactions, giving dealmakers an agile, continuously updated picture of deal pipelines.
Challenges and Regulation
Despite increasing adoption, skepticism persists around data integrity, reliability, and regulatory alignment. Over one-third of dealmakers still cite data privacy as a key concern, while 74% favor government oversight of generative and agentic AI in transaction workflows.
A major trust milestone arrived in October 2025 when Datasite became the first global virtual data room (VDR) platform to achieve ISO 42001 certification, setting a new benchmark for ethical AI governance. The certification verifies that Datasite’s AI systems meet rigorous AI Management System (AIMS) standards, including transparency, risk mitigation, and continuous improvement.
McKinsey’s Agentic Organization model further reinforces that successful AI adoption requires restructured workflows in which autonomous agents collaborate alongside human teams, balancing speed with interpretability.
Responsible AI and the Road Ahead
For firms seeking to deploy AI in M&A responsibly, the path forward is clear:
- Ensure transparency in AI decision-making and logic chains
- Train systems on high-quality, domain-specific data
- Embed cybersecurity safeguards across systems and cloud layers
- Align governance with ISO 42001 and equivalent frameworks
Organizations using tools that meet these standards will set the benchmark for trustworthy, scalable dealmaking.
Successful Dealmaking in 2026
Agentic AI is redefining what successful M&A looks like. It’s graduated from proof-of-concept to indispensable infrastructure. In 2026 and beyond, those who combine strategic intent, certified governance frameworks, and continuous learning systems will lead the next era of dealmaking.