In the fast-paced realm of mergers and acquisitions (M&As), artificial intelligence (AI) is emerging as a key catalyst to drive efficiency. M&A is time-consuming, with deal origination relying on networks and relationships, and due diligence (DD) involving massive amounts of data review. AI is transforming this domain, offering significant efficiencies, cost savings and speed.
Since 2017, AI adoption has more than doubled across organisations, with 77% of companies using or exploring it. A similar trend is also seen in the M&A space, especially during the pre-deal stage, where AI is revolutionising traditional practices and is aiding in gaining efficiencies during target screening, DD and valuation.
Capitalising on promising investment opportunities requires meticulous target evaluation in the initial phase of the deal-making process. In the high-stakes endeavour of target evaluation, AI tools assist in research and market analysis, reducing the time spent on screening by 50-60%. These tools go beyond traditional data analysis, uncovering potential risks hidden within unstructured sources, such as news articles and hand-written notes.
For instance, a global life sciences organisation used an AI tool to scrutinise the existing market landscape, recent transactions and competitors within its targeted segment and applied AI algorithms, enabling rapid identification of highly promising acquisition targets. This tool helped to shortlist from a list of companies that matched value proposition and geographical focus, saving over 90% of the time in identifying and shortlisting potential targets.
When evaluating a potential acquisition, AI tools assist the DD process in many ways. While it manages data rooms for organising critical documents, summarising documents, etc., it also provides insights on key risks, contract data and financials, eventually guiding reviewers to make informed decisions faster. For example, AI can reduce document review time by up to 70% during contract assessment, which is a critical component in the DD process.
A notable case involved an AI-enabled tool used for contract assessment that analysed about 400 contracts in multiple languages and identified risks in the change of control and termination clauses. This tool used advanced character recognition and natural language processing models to automatically identify and extract key data, resulting in a reduction of about 80% in document review time compared with conventional methods. Furthermore, advanced AI technologies can help create detailed reports.
The next critical step is determining a range of valuations for negotiations and successful deal closures. Accurate and reasonable valuation from buyers and sellers’ perspectives is vital, as almost 50-60% of M&A transactions globally fail to deliver the value envisioned. Estimating a reasonable valuation range requires a comprehensive approach that combines financial analysis, market assessment and consideration of various qualitative factors. AI tools assist in financial assessment, including identifying various value drivers and potential sources of synergy benefits, market data, comparison with similar companies, sensitivity and scenario analyses.
In one such instance, an AI tool assisted advisors at an investment banking firm with the valuation process by performing multi-variable sensitivity analysis and evaluating alternative scenarios using market data. This reduced the time required for valuations and eventually increased the teams’ confidence in the accuracy and reliability of their valuation outputs.
Early adopters of AI (including GenAI) are discovering that this technology has a competitive advantage. However, adopting AI comes with its set of challenges, including privacy concerns, bias and compliance. Addressing these challenges is important. While AI can automate tasks, human expertise remains essential for strategic decision-making, negotiation and relationship management. Integrating AI with human intelligence effectively is crucial for maximising the value of technology in M&A.
AI's role in M&A promises broader applications across the entire transaction lifecycle. Beyond the pre-deal phase, AI is poised to transform post-merger integration by streamlining the process and maximising synergies. AI-driven project management tools can enhance efficiency by identifying crucial milestones and monitoring progress during integration. Advanced AI tools are also expected to identify integration and cultural challenges.
In conclusion, using AI, combined with human intelligence, can streamline the pre-deal phase of M&A transactions. This can help accelerate the process (such as target identification and DD), identify risks and drive more informed negotiations, leading to successful deals.
Anuj Suneja is Partner, Deloitte India. Views expressed are personal.
