The mergers and acquisitions (M&A) industry is experiencing its most profound transformation in decades, and the casualties are mounting. What began as experimental AI adoption by a few forward-thinking firms has rapidly evolved into a fundamental restructuring of competitive dynamics. M&A practitioners who continue to rely on traditional processes now face an existential question: adapt or lose ground to competitors.
The numbers detailed in our latest whitepaper tell a stark story.
In 2025, M&A firms where AI is fully integrated in the deal-making process are achieving up to 1.6 times higher shareholder returns than their traditional counterparts, completing deals in weeks rather than months, and identifying value creation opportunities that conventional analysis often overlooks.
Meanwhile, traditional firms, which may use AI in part, are increasingly relegated to smaller, less strategic transactions – a vulnerable place to be in an industry where scale and sophistication determine survival.
The widening performance chasm
The competitive divide between AI-enabled and traditional M&A firms has moved beyond incremental advantages to fundamental performance gaps that threaten the viability of conventional approaches.
Early adopters aren’t just working faster; they’re operating in an entirely different paradigm. Consider the reality of deal execution speed. AI-powered firms close deals in weeks while traditional firms take months. In competitive bidding situations, this speed advantage often wins the deal. The faster firms also deliver better financial returns.
Research included in our whitepaper indicates that 80% of acquirers using AI achieve superior shareholder returns, with revenue growth from AI-enabled combinations averaging 1.5 times higher than traditional deals. These aren’t marginal improvements – they represent a fundamental shift in value creation capability that traditional approaches cannot match.
Perhaps most damaging is the depth of the analytical capability gap between early M&A AI adopters and traditional teams. Traditional teams, constrained by human limitations, typically review subsets of available documentation and rely on sampling methodologies that inevitably miss critical details. AI systems analyse complete document sets with consistent thoroughness, revealing insights and risks that partial analysis overlooks.
The due diligence revolution
Nowhere is the traditional firm’s disadvantage more pronounced than in due diligence – historically, the most time-intensive and resource-intensive phase of any transaction. AI-powered platforms have transformed this critical process through automated document review, real-time risk identification, and the extraction of intelligent insights.
Traditional due diligence remains largely manual, requiring teams of analysts to spend weeks reviewing thousands of documents, contracts, and financial records. This approach is not only slow but inherently inconsistent. AI systems complete initial reviews in days with unprecedented consistency and thoroughness, reducing due diligence timelines by up to 50% while improving analytical quality.
The sophistication gap extends beyond speed to analytical capability. Large language models (LLMs) and natural language processing (NLP) enable AI systems to analyse thousands of contracts simultaneously, identifying standard terms, unusual clauses, and potential negotiation points that human reviewers might miss. They assess management presentations, employee communications, and market research to gauge organisational culture, strategic alignment, and integration challenges – analysis that traditional approaches cannot match at scale.
Integrated AI real-time risk assessment capabilities provide continuous monitoring throughout the due diligence process, tracking regulatory changes, monitoring target company news and social media sentiment, and alerting deal teams to emerging issues that could impact valuation or transaction structure.
The compounding disadvantage
Traditional M&A firms face a particularly unenviable challenge: their disadvantages compound over time while their competitors’ advantages accelerate. Each transaction completed by AI-enabled firms generates additional data and insights that improve their algorithms, expand their pattern recognition capabilities, and enhance their predictive accuracy.
The talent implications are equally challenging.
As AI adoption spreads throughout the industry, the most capable professionals gravitate toward firms that offer cutting-edge tools and methodologies. Traditional firms are increasingly struggling to attract and retain top talent, as ambitious professionals recognise that AI-enabled environments offer better learning opportunities, more engaging work, and superior career prospects.
Client expectations have evolved rapidly as well.
Corporate development executives and private equity partners who have experienced AI-enhanced deal processes become unwilling to accept traditional timelines and analytical limitations. They demand the speed, depth, and insight that AI enables, making it increasingly difficult for traditional firms to compete for premium mandates.
The late adopter trap
Companies that haven’t adopted AI yet are falling behind fast. AI users can analyse deals in a fraction of the time non-users still need. This puts late adopters at a major disadvantage when competing for deals or spotting problems early.
The financial implications are severe.
Traditional acquirers struggle to justify transaction premiums without AI-enhanced synergy identification and capture capabilities. They find themselves competing for deals with firms that have superior analytical capabilities, faster execution timelines, and better post-merger integration track records.
Perhaps most challenging is the escalating cost of catching up.
As AI capabilities advance and become more sophisticated, the investment required for competitive implementation increases. Traditional firms must simultaneously invest in technology, retrain their personnel, and redesign their processes while competing against firms that have already undergone this transformation.
Security and compliance: The hidden vulnerability
Traditional firms face additional risks in an increasingly regulated environment where data security and compliance requirements continue to expand. Manual processes create inherent vulnerabilities that sophisticated AI systems can address through built-in safeguards, advanced encryption, and comprehensive audit trails.
Traditional methodologies, relying on human handling of sensitive documents and manual compliance processes, create exposure to regulatory fines and reputational damage that have in recent years. AI-enabled platforms provide enterprise-grade security with automated compliance monitoring that traditional approaches cannot match.
If you want to find out how Drooms handles data security and compliance in relation to AI, read our blog.
The path forward: Transform or perish
The facts are clear: AI is no longer optional in M&A – it’s essential. Traditional firms using old methods are in serious trouble, and this will only get worse as more companies adopt AI.
Research evidenced in our whitepaper shows 80% of dealmakers will use AI throughout their entire deal process within three years. AI is moving from cutting-edge to standard practice, leaving traditional approaches behind.
The choice facing traditional M&A firms is stark but clear: embrace comprehensive AI transformation now or accept progressive marginalisation in an industry that’s rapidly evolving beyond recognition. Half-measures and gradual adoption won’t suffice – the performance gaps are too wide and the pace of change too rapid for incremental responses to be effective.
The future of M&A is already here, and it’s powered by artificial intelligence. Traditional firms that recognise this reality and act decisively still have time to transform. Those that don’t will find themselves casualties of the industry’s most profound evolution in decades. The great M&A divide isn’t coming – it’s already here. The only question is which side of history your firm will choose to be on.
Author’s note
The content and data in this article are drawn from our latest whitepaper, which synthesises research and insights from leading consulting firms and industry sources, as well as our insights and experiences, to provide a comprehensive view of AI’s impact on mergers and acquisitions. The analysis is based on transaction data, performance metrics, and industry surveys from 2024 to 2025, representing the most current available intelligence on this rapidly evolving topic.
