Artificial intelligence is reshaping how deal teams source, evaluate, and move on opportunities. In a recent webinar, Risto Siilasmaa — founder of WithSecure, longtime board member, and active investor — shared his perspective on how AI is changing the mechanics of M&A and what modern deal teams should prepare for next.

This article summarizes Siilasmaa’s key insights and connects them with real-world learnings from 1000+ M&A teams already adopting AI-native workflows using Inven.

What Did Risto Siilasmaa Say About the Future of AI in M&A?

Siilasmaa emphasized one central idea:
AI is no longer an optional enhancement for M&A teams. It is becoming a core capability.

Traditional workflows rely heavily on manual research, fragmented data, and time-consuming list building. AI, he argued, removes this bottleneck by acting as an analytical engine that augments human judgment rather than replaces it.

According to Siilasmaa, the firms that successfully adopt AI early will move faster, discover more opportunities, and outperform competitors still operating with outdated processes.

How Are M&A Teams Using AI to Avoid Missing High-Quality Targets?

One of the biggest risks in deal sourcing is the silent opportunity — the company that should be on your radar but never appears in traditional searches.

AI helps eliminate that blind spot.

1. Discover companies before competitors see them

Teams use AI to surface emerging companies in niche verticals, often months before they appear on conference lists or databases.

  • Analysts report finding 30% more targets compared to traditional tools.

2. Understand what a company actually does — not just its industry code

AI evaluates companies based on what they say on their websites, job posts, and digital footprint. This is valuable for sectors where industry codes fail, such as IT services, healthcare niches, or software subcategories.

3. Reduce research time by 70–90%

Across sectors, teams consistently report dramatic time savings:

  • Lexar Partners cut list building from a full day to 15–30 minutes
  • Crossroads Capital reduced their search process by up to 80%
  • Village Wellth saved 50–70% of research time per search

When deal teams spend less time crawling the web, they spend more time evaluating fit and building relationships: the work that truly drives outcomes.

Why AI Is Becoming Essential for Investment Banks, PE Firms, and Corporate Development Teams

Investment Banking

Banks increasingly rely on AI to:

  • Build actionable buyer and target lists in minutes
  • Identify retirement-aged founders and intent signals
  • Validate market maps with higher accuracy

Analysts note that AI-based searches feel “like scraping the entire internet”, drastically improving confidence before outreach.

Private Equity

PE firms use AI to:

  • Proactively source add-on and platform opportunities
  • Find family-owned businesses outside competitive funnels
  • Avoid sourcing from the same pools as other funds

Several PE teams report finding companies with AI that do not appear in Grata, PitchBook, or traditional databases.

Corporate Development

Corporate development teams value AI for:

  • Scanning global markets across languages
  • Identifying niche technical capabilities
  • Monitoring fast-changing segments

As Siilasmaa noted, AI levels the playing field: mid-market teams now have analytical capabilities once reserved for the largest global acquirers.

What Workflows Benefit the Most From AI in Deal Sourcing?

1. Market Mapping

Instead of starting from an empty spreadsheet, AI can instantly generate a complete view of a niche — from “Microsoft Dynamics integrators in the Nordics” to “medical equipment distributors with >20% headcount growth.”

2. Target Screening

AI evaluates signals such as:

  • Website content
  • Hiring momentum
  • Ownership structure
  • Geographic footprint
  • Digital activity

M&A professionals often describe this as having “a team of junior researchers working underneath you.”

3. Prioritization

AI highlights companies that may be:

  • founder-owned
  • nearing generational transitions
  • showing intent-to-sell indicators
  • gaining or losing traction

4. Cross-border discovery

Because AI processes multilingual content, teams can evaluate global markets without relying on English-only datasets.

Which AI Tools Do M&A Teams Actually Use Today?

Deal teams often combine two categories of tools:

General-purpose AI (ChatGPT, Claude, Gemini)

Used for:

  • Summarizing CIMs
  • Refining investment theses
  • Brainstorming search strategies
  • Interpreting financial data

AI-native M&A platforms

Used for:

  • Building comprehensive target lists
  • Automatically evaluating company fit
  • Analyzing signals across millions of entities
  • Contact discovery and outreach enablement

Where Inven Fits

Using Inven, teams consistently highlight:

  • Expansive global coverage
  • Natural language search
  • Accuracy in niche verticals
  • Stronger usability than Grata, Grasp, PitchBook, or traditional databases

Several firms — including Edgehill Management, Augusta Advisors, Desert Horizon Capital, and others — sourced real deals directly through Inven.

How Can M&A Teams Start Adopting AI Effectively?

1. Start small. Integrate AI into your existing workflow

Use AI to accelerate what you already do:

  • List building
  • Quick filtering
  • Market understanding

2. Don’t overcomplicate tool choice

The best AI tools fit how analysts already work. Ease of use matters more than sophistication.

3. Combine human judgment with AI speed

AI handles breadth; humans handle nuance. Building relationships cannot be automated, and networking and connecting is still vital to getting the deals before others.This pairing significantly improves deal selection quality.

4. Focus on iteration

Teams that see the biggest gains use AI as a constant feedback loop: refining search criteria, reshaping theses, and discovering new sub-verticals weekly.

What Does the Future Look Like for AI-Driven M&A?

1. Faster deal cycles

As research time collapses, evaluation and outreach accelerate.

‍2. More off-market opportunities

AI exposes overlooked segments where competition is lower.

3. Higher expectations for analytical depth

Boards and investment committees will soon expect AI-enhanced analysis as the norm.

In today’s environment, the question is no longer if AI will reshape M&A — it's which teams will adapt quickly enough to benefit.