1. Introduction

When cryptocurrency exchange Kraken acquired trading platform NinjaTrader in April 2025 for $1.5 billion, its team used AI to complete due diligence in just hours1 – an exercise that previously would have taken weeks and dozens of analysts. By automating vast parts of the process, Kraken could pursue multiple acquisitions simultaneously without compromising accuracy.

This reflects a growing trend: AI is fast becoming a catalyst for modern M&A in a turbulent and unpredictable economic climate. According to Bain & Company2, only 16% of deal teams employed generative AI in 2023 – and that number is forecast to surge3 to 80% by 2028, as early adopters continue to prove the technology’s value.

2. The AI M&A boom: Why now?

This growing reliance on AI comes at a time when dealmakers are navigating heightened volatility and an uncertain economic outlook. Firms are turning to AI not just for speed, but for clarity and control.

Since 2021, the M&A landscape has contended with high inflation, unfavorable interest rates and regional conflicts – from supply-chain disruptions stemming from the Ukraine war to diplomatic tensions in the Asia-Pacific. These factors pushed borrowing costs to multi-year highs, forcing buyers to reassess valuations and contributing to a slump in global deals.4

The tide began to turn in 2024. As central banks tentatively eased rate-hike cycles and commodity prices stabilized, dealmakers regained confidence. Global M&A activity climbed by more than 15%5 year-on-year to over 45,000 deals, collectively worth $3.7 trillion. Technology led the charge: 7,455 transactions took place, with a combined value of $740.7 billion.

Despite this rebound, the start of 2025 has been subdued. Protectionist trade measures introduced by the new US administration, including stricter tariffs, tighter foreign-investment rules and heightened regulatory reviews, coincided with a 30% decline in US deals6 in January compared with the same month in 2024.

Research by Dechert7 found that 71% of private equity professionals globally anticipate greater scrutiny from antitrust and other regulatory authorities will negatively impact their dealmaking this year.

Against this backdrop, AI has become a strategic imperative as deal teams look to maintain margins by becoming more efficient. McKinsey8 estimates that by 2030, in a midpoint adoption scenario, up to 30% of current hours worked could be automated, accelerated by generative AI. Today’s deal teams use AI to streamline target screening,9 de-risk negotiations through scenario modelling10 of regulatory outcomes and drive better collaboration through smart search11 and auto-translation.12

These capabilities are reshaping every stage of dealmaking, delivering tangible benefits in time, cost and accuracy.

Abb. 1 Change in M&A deal duration since 2020

Quelle: Ideals H1 2024 M&A Trends Report

Source: Ideals H1 2024 M&A Trends Report

3. Due diligence, but not as you know it

At the heart of today’s transformation in M&A is the use of AI to revolutionize the due diligence process. What was once a physical “data room” filled with bankers, lawyers and reams of paper has evolved into a digital environment – and now, an intelligent one. AI is turning due diligence from a manual, time-intensive task into a streamlined, high-precision operation.

This shift comes at a critical time. Increasing regulatory scrutiny13 and deal complexity14 have stretched due diligence timelines. Between 2022 and 2023, regulators challenged $361 billion worth of transactions15, extending pre-close periods from the traditional three-month horizon to as long as two years. Ideals research16 shows that deals closing in the first half of 2024 had lasted on average 258 days. That’s 32% longer than in 2020, when the average duration was 195 days.

In response, M&A teams have turned to AI-powered virtual data rooms (VDRs),17 which give dealmakers the ability to organize, secure, analyze and collaborate on documents in one centralized hub. This quiet revolution is streamlining workflows, reducing manual effort and boosting the accuracy and speed of due diligence. For example, automated redaction tools18 detect personal or sensitive information within seconds, so team members don’t have to spend hours masking details that certain stakeholders shouldn’t see. Meanwhile, AI translation capabilities19 allow teams to review documents in multiple languages without relying on external services, which can slow down deal timelines.

Another significant advantage lies in AI search20, which allows dealmakers to quickly locate critical documents and insights. In the past, teams would spend hours searching through vast amounts of data for key information. Today, everything they need to know about the deal is available at the touch of the button.

All this is helping dealmakers cut through complexity, act with greater confidence and keep due diligence moving at the pace the market demands.

4. Beyond the close: AI’s role in post-merger integration

But it’s not just in deal execution that AI delivers value. The most forward-looking firms are embedding AI well beyond the due diligence process and into the post-merger phase, where real value is realized – and where many deals stumble. Research by Eight Advisory21 shows that while over two-thirds (71%) of M&A transactions were perceived as successful from a strategic and financial standpoint, “expected synergies” were achieved or exceeded in just 40% of cases. Around two thirds (67%) of respondents identified cultural convergence and change management as the most underestimated challenges during integration.

AI is beginning to transform post-merger integration through ongoing data-driven guidance. Sentiment-analysis algorithms22 scan employee feedback, communication platforms and collaboration tools to identify cultural issues before they impact productivity. Machine-learning models23 use predictive analytics to anticipate cash flow trends, identify potential financial risks and optimise resource allocation based on historical and current data. And forecasting tools – which can automate resource planning and performance management – are reducing errors by 25%-50%, according to McKinsey.24

But it’s not just about the technology: ensuring successful adoption means equipping teams with the skills and confidence to use AI effectively. A recent Boston Consulting Group (BCG) study25 found that while 75% of executives ranked AI among their top three priorities, only 25% reported seeing “significant value” from their investments.

This disconnect stems not from weak algorithms or poor data, but from a failure to change how people work. To bridge this gap, BCG recommends that only 10% of effort and resources be spent on building algorithms or training models, with another 20% focused on data and infrastructure. The lion’s share – 70% – should be dedicated to transforming workflows, reskilling teams and embedding AI into day-to-day decision-making.

5. Welcome to the deal room, AI agents

As dealmakers become more confident using AI during due diligence and integration, attention is shifting to how the technology will evolve in coming years – and what these innovations will mean for the M&A lifecycle.

Central to this conversation are AI agents,26 which are quickly becoming integral members of the deal team. These machine-learning tools are capable of acting autonomously to carry out tasks with minimal human oversight. AI agents can assign tasks dynamically – routing responsibilities to deal team members or other tools based on complexity and priority. This creates a faster and more seamless deal flow from sourcing through to post-close.

A glimpse of this future can be seen in Rogo,27 a four-year-old AI startup that recently raised $50 million in Series B funding at a $350 million valuation. Its investment banker chatbot can analyze market positioning, competitor activity and valuation benchmarks in minutes – tasks that previously took junior analysts days.

Already in use at investment banks Moelis and Nomura, and at investment firms Tiger Global and GTCR, the technology has sparked a fierce debate. Some worry the efficiency gains will reduce entry-level positions on Wall Street, while others – including Rogo’s Founder, Gabriel Stengel – think it will free up banks to handle more deals, potentially increasing hiring.

For now, the consensus is that these tools won’t replace human judgment, but they will elevate it. By automating routine tasks and delivering actionable insight, they allow deal teams to spend more time on what matters most: value creation and high-stakes decision-making.

6. Time for a new era in dealmaking

The need for speed, precision and insight in M&A has never been greater – and now is the perfect time for financial services firms to capitalize on the growing opportunities that AI presents to dealmakers. With over half (58%) of European CEOs28 in the sector planning to pursue M&A in 2025, we’re standing on the precipice of exciting change.

Making the most of this momentum demands a strong focus on accelerating due diligence. AI-driven VDRs promise to not just speed up deal timelines, but also to uncover deeper insights, mitigate risks more effectively and unlock more value than ever before.

The firms that act now to embrace AI-enhanced due diligence and integrate it into their workflows have the potential to fundamentally reshape how value is identified, captured and sustained throughout their transactions. In doing so, they’ll accelerate deal execution, stay resilient in the face of uncertainty and redefine the art of dealmaking for years to come.

1 https://www.businessinsider.com/how-ai-was-used-kraken-ninjatrader-acquisition-2025

2 https://www.bain.com/insights/generative-ai-m-and-a-report-2025/

3 https://www.bain.com/insights/generative-ai-m-and-a-report-2024/

4 https://www.privatebankerinternational.com/opinion/2025-ma-outlook-how-technology-can-power-dealmaking-in-uncertain-times/?cf-view

5 https://www.privatebankerinternational.com/opinion/2025-ma-outlook-how-technology-can-power-dealmaking-in-uncertain-times/?cf-view

6 https://imaa-institute.org/mergers-and-acquisitions-statistics/ma-statistics-by-countries

7 https://www.dechert.com/content/dam/dechert%20files/services1/practice-areas/private-equity/2024-Global-Private-Equity-Outlook.pdf

8 https://www.mckinsey.de/~/media/mckinsey/locations/europe%20and%20middle%20east/deutschland/news/presse/2024/2024%20-%2005%20-%2023%20mgi%20genai%20future%20of%20work/mgi%20report_a-new-future-of-work-the-race-to-deploy-ai.pdf

9 https://www.bain.com/insights/generative-ai-m-and-a-report-2024/

10 https://www.ilpabogados.com/en/the-impact-of-artificial-intelligence-on-mergers-and-acquisitions/

11 https://helpcenter.idealsvdr.com/en/articles/9699421-ai-search-how-to-accelerate-document-review

12 https://helpcenter.idealsvdr.com/en/articles/10327394-ai-document-translation