How AI is quietly rewriting the M&A sourcing playbook in India’s startup ecosystem

Amid the flurry of fundraises and deals, a quiet shift is underway. AI, once dismissed as just a buzzword, is now shaping workflows, customer touchpoints, and even M&A deals. It is transforming how mergers and acquisitions are sourced, evaluated, and executed, and in many ways, reshaping India’s startup playbook.

AI is compressing every phase of the deal cycle—right from deal sourcing to post-merger integration. No longer just the target of acquisitions, it has become the engine powering the deal pipeline. Corporate development teams can now shortlist high-potential targets within weeks, boosting productivity several-fold, while also evaluating multiple scenarios that would previously have been too resource-intensive to consider.

According to a recent Axial member survey, 74.2% of respondents already use AI tools in their deal sourcing or marketing efforts, and another 9.7% plan to adopt them later this year. According to the survey, 60% of respondents believe AI offers a moderate or significant edge in M&A today. A report by Bain & Company also shows that over 60% of private equity firms already use AI for sourcing, screening, and due diligence. 

The pool of dealmakers using AI at different stages of the lifecycle is only growing, and the implications are profound.

Traditionally, M&A sourcing depended heavily on human networks—investment bankers, VC connections, or cold outreach. This approach was not only time-consuming but also restricted to a narrow pool of known targets. For decades, dealmaking was the preserve of large enterprises with privileged access to bankers and global networks, leaving smaller companies on the sidelines.

That reality is changing. Across India and the United States, mid-market enterprises, fast-growing startups (even at the Series A stage), PE-backed firms, and corporate development teams are now actively pursuing acquisitions. The playing field is widening, and AI is at the centre of this shift.

AI is flipping the script by parsing millions of digital signals—hiring trends, funding rounds, product launches, and leadership moves—to proactively surface high-fit acquisition targets, including those not openly seeking a sale. What was once invisible or overlooked is now discoverable, giving dealmakers of all sizes the same visibility that only the biggest players enjoyed in the past.

Key ways AI is transforming M&A in India

Smarter deal sourcing

AI eliminates the constraints of traditional deal discovery by continuously scanning public and private data sources. It looks into companies’ hiring patterns, funding updates, patent filings, and even social media sentiment—to flag potential targets. This allows acquirers to build a dynamic pipeline rather than wait for intermediaries to bring deals to the table.

Automated due diligence 

AI also helps ease the cumbersome process linked with due diligence. AI tools help review contracts, compliance documents, and litigation records at scale, reducing the time and cost of legal and financial due diligence. They help flag hidden risks and anomalies that humans might miss. 

Further, AI now analyses behavioural signals—hiring slowdowns, reduced marketing spend, leadership churn, or even shifts in founder communication tone—to predict receptiveness to a deal. This makes outreach more personalised and timely, increasing the chances of engagement.

Advanced valuation models

Every acquirer is unique. Some seek geographic expansion, others prioritise product synergy or access to new technology. AI-driven predictive analytics considers alternative data—consumer behaviour, ESG scores, digital footprint, competitor activity—to provide more accurate valuations and forward-looking growth forecasts. 

AI enables acquirers to create highly customised scoring models that go beyond surface-level firmographics and financials. Automated early-stage diligence and signal tracking accelerate deal velocity while maintaining confidentiality.

Risk assessment & compliance at a pocket-friendly cost

Historically, M&A was the domain of large corporations with deep pockets and dedicated corp development teams. AI-powered platforms now level the playing field, enabling bootstrapped startups, mid-sized firms, and regional players to run sophisticated deal-sourcing programs. 

As a result, we are seeing a surge in strategic tuck-ins, team acquisitions, and product bolt-ons by companies that might not have considered M&A feasible a few years ago.

Post-merger integration

AI tools optimise integration by analysing workforce synergies, supply chains, IT systems, and customer overlap. Sentiment analysis also helps gauge employee morale and customer response post-deal. It also helps in integration in case of cross-border acquisitions. AI-powered translation, cultural sentiment analysis, and cross-jurisdictional compliance tools are helping streamline global dealmaking.

AI is not replacing dealmakers—it’s empowering them. Algorithms can scan, score, and surface opportunities, but human judgement remains essential for negotiation, trust-building, and cultural fit assessment. We are seeing this play out in practice—where data and AI, combined with human expertise to make deal sourcing more precise and efficient. 

For startups and growth-stage companies, this often means access to a ‘ready-to-transact’ pipeline of opportunities, built through a mix of proprietary algorithms and confidential outreach.

The old episodic, banker-led model of M&A is giving way to continuous, always-on deal discovery. With funding slowdowns making founders more receptive, Indian firms—especially in sectors such as fintech, enterprise tech (AI/SaaS), transportation and logistics, healthcare, and consumer brands—are actively pursuing acquisitions.  AI makes these strategic moves faster, scalable, and replicable, shortening the path from intent to engagement and from insight to action.

For founders, this means more strategic exit opportunities. For acquirers, it means faster, smarter deal discovery. And, for the ecosystem at large, it signals a shift toward a more efficient, transparent, and dynamic M&A landscape.

The author is Co-founder and CEO, Growthpal, an AI-led M&A deal sourcing platform.