2026 Will Be The Year of AI In Dealmaking

Artificial intelligence is no longer simply a futuristic promise for dealmakers. It has become the defining force actively reshaping private equity, venture capital, and corporate development right now. In fact, when we ran a query on Cyndx Scholar, the research outcome reveals something remarkable: by late 2025, over half of all global venture funding flowed toward AI, and a single AI megadeal can redirect the course of an entire quarter. For dealmakers, this is the sound of markets fundamentally reorganizing around new capabilities.

According to Scholar, our AI-powered deep research product, three seismic trends are converging to make 2026 the inflection point. First, AI is shifting rapidly from experimental lab projects to embedded, enterprise-grade workflow solutions that actually work. Second, the nature of competition itself is changing, with deal success increasingly defined by the ability to harness AI for proprietary sourcing, automated due diligence, and predictive valuations. Third, the regulatory and fundraising landscape is tightening, with partners demanding direct evidence of technology adoption while new compliance standards raise the bar for every transaction.

The market entering 2026 looks fundamentally different from recent years. Companies aren’t running pilot projects anymore as AI has become more operational. They’re deploying AI into production workflows and making it core to operations. That creates immediate M&A opportunities as businesses race to acquire AI capabilities, data assets, and infrastructure they don’t have.

AI Adoption and Market Dynamics

In the first quarter of 2025 alone, venture capital-backed companies raised over $80 billion, a 28% increase over Q4 2024. But what makes that figure extraordinary is that a single record-setting $40 billion AI deal doubled the quarter’s volume. Without that megadeal, VC funding was projected to decline by 36%. That’s how much leverage AI has over deal flow right now.

AI now accounts for more than 50% of global venture capital funding, with mega-rounds significantly influencing venture economics. In Q3 2025, $17.4 billion was invested in applied AI, up 47% year over year. Investment focus has shifted decisively away from building foundational architectures and toward integrating AI into operational, customer-facing, and risk management workflows. Investors are prioritizing startups with demonstrated traction in enterprise adoption, with deal terms emphasizing integration over innovation. Translation: the market wants AI that actually does something useful, not just impressive demos.

On the M&A side, 2025 is set to be the strongest year for billion-dollar deals since 2021, with large deals up 17% and megadeals over $5 billion up 31% from the prior year. Roughly a quarter of these megadeals have a central AI theme, whether data center acquisition, AI-powered infrastructure, or strategic acquihires of AI talent. Deal value hit $1.1 trillion, a 26% increase year over year.

Agentic AI and the Next Wave in Deal Sourcing

If 2025 was about generative AI, 2026 will be the first year of agentic AI at scale. These are systems that don’t just respond to instructions but proactively initiate, sequence, and optimize multi-step deal processes based on evolving goals and real-time data. Instead of giving agents instructions, you give them goals.

Agentic AI models are evolving from single-task functions to orchestrated, multi-agent systems that mirror specialized human teams. In practice, this allows a single orchestrator agent to delegate tasks to sub-agents focused on diligence, compliance, or integration planning, maximizing efficiency and scale across the deal cycle.

For dealmakers, this means compressing due diligence timelines from weeks to days without sacrificing thoroughness. It means running multiple valuation scenarios instantly to understand how different assumptions affect deal economics. It means generating comprehensive market research reports in minutes that would traditionally take analysts weeks to compile.

The firms mastering these capabilities in 2026 will close more deals, with better terms, and higher confidence in their investment theses. The gap between AI-enabled firms and those still working manually is widening fast.

M&A Due Diligence and Smarter Company Valuation

Due diligence used to mean weeks in data rooms, manually reviewing contracts and hoping you didn’t miss anything critical. AI due diligence software can now review thousands of documents in hours, extract key terms, flag risks, identify inconsistencies, and surface patterns that human reviewers would miss after days of work.

AI-powered document review can scan thousands of legal and financial documents in minutes, extracting key terms, uncovering red flags, and ensuring regulatory compliance. Natural language processing excels at analyzing unstructured data like contracts, emails, and news articles, surfacing deal risks that manual review might miss. Some platforms are reporting due diligence cycle time reductions of up to 80%.

However, the real value isn’t just speed but consistency. AI doesn’t get tired or change moods. It applies the same thoroughness to every single page it reviews. In modern company valuation, AI can analyze thousands of comparable transactions instantly, adjust for market conditions, incorporate sector-specific factors, and generate initial valuation ranges in minutes.

An AI system can identify valuation patterns across hundreds of deals that no human analyst could manually compile in reasonable timeframes. It can spot how valuations shift based on factors like revenue mix, geographic exposure, customer concentration, or growth rates.

Purpose-Built M&A Software Makes the Difference

Generic AI tools can provide surface-level analysis, but they don’t understand dealmaking. Our platform shows what’s possible when AI is designed specifically for dealmakers rather than adapted from generic business intelligence.

Finder uses natural language processing to surface companies based on what they actually do, not just how they describe themselves. Search by concept rather than keywords, identifying targets in emerging categories that don’t have standard industry classifications yet. With proprietary data on nearly 32 million companies, Finder surfaces opportunities based on actual capabilities and market activity.
Acquirer identifies acquisition targets based on strategic fit and compatibility with your existing portfolio or mandate. The platform’s predictive analytics flag which companies are actively seeking funding or partnership discussions right now, giving you insight into receptiveness before you reach out.
Raiser pinpoints financial or strategic investors based on industry focus, check size, and most importantly, actual investment history in comparable deals. Instead of researching which VCs claim to invest in your sector, Raiser shows you which ones have actually written checks recently.
Valer performs sophisticated valuations, comparable company analysis, and precedent transactions. When you’re evaluating private companies with limited financial disclosure, Valer provides data-driven starting points for negotiations without spending weeks building models from scratch.
Scholar generates comprehensive research reports using proprietary data plus trusted external sources, complete with proper citations and validation. Scholar leverages agentic AI workflows to create 50+ page research reports in minutes, pulling from Cyndx’s database and validating insights with precision. For complex due diligence that would normally require weeks of research, Scholar creates professional-grade reports that you can present to investment committees with confidence.

These are M&A software tools built from the ground up for how deals actually get done. When your deal sourcing platform, valuation tool, investor identification system, and research capabilities all share the same data foundation and were designed for the same workflows, you eliminate the integration burden that slows down firms.

For dealmakers, this isn’t just another busy year. It’s a structural shift in how capital gets deployed, how value gets created, and how competitive advantage gets built in an AI-driven economy.

The market is active. The opportunities are real. And the dealmaking tools you need to win are here.