Generative AI has quickly gone from being a technological curiosity to becoming a commercial reality. It is expected to drive the biggest transformation in business since the internet was invented 40 years ago, affecting virtually every area of our lives.
In our previous articles on generative AI, we’ve looked at its potential to transform business operations, its strategic implications and its impact on professional services. In this final article in the series, we’ll discuss how generative AI could - and already is - shaping the future of M&A.
Implications for the M&A Deal Lifecycle
Implications for the M&A deal lifecycle is increasingly hard to ignore. M&A professionals and company executives can leverage this technology to optimise their buy- and sell-side processes, including targeting, valuation, due diligence, synergy planning, transacting the deal, TSA design and delivery, and post-deal value creation.
With study after study finding the failure rate of mergers and acquisitions somewhere between 70% and 90%, any opportunity to improve the success rate of deals by incorporating generative AI into the deals lifecycle is likely to be seized on by dealmakers. In particular, we have identified six key areas where AI can drive greater success in M&A transactions.
1. Targeting and deal sourcing
Generative AI can significantly improve the targeting and deal sourcing process by analysing large volumes of data and identifying patterns that might otherwise be overlooked by human analysts. By processing data from various sources, including financial statements, market trends, and social media, AI systems can quickly generate a list of potential acquisition targets that align with a company's strategic objectives.
2. Valuation
Accurate valuation is a critical aspect of the M&A process. Generative AI models can analyse historical transaction data, financial metrics, and industry benchmarks to generate a more accurate and data-driven range of valuations quickly. Buyers and sellers with significant deal experience, or those who partner with experienced advisors, can leverage their own historical proprietary data to create competitive advantage during the valuation process, so as not to overpay or leave money on the table.
3. Due diligence
Due diligence is a time-consuming and labour-intensive aspect of the M&A process. Generative AI can help streamline this process by automating the analysis of large volumes of data, such as legal documents, financial records, and market research. Such AI-powered tools could reduce due diligence processing times significantly, enabling deal teams to focus on more strategic tasks.
4. Synergy planning and transaction
Generative AI can also help in identifying and quantifying potential synergies between companies. By analysing financial data, operational processes, and organisational structures, AI-driven tools can generate synergy estimates and help M&A teams design optimal transaction structures. Additionally, generative AI can be used to model different deal scenarios, enabling dealmakers to make informed decisions on the transaction terms.
5. TSA design and delivery
AI-driven tools can help M&A professional’s design and deliver effective Transitional Service Agreements (TSAs) by identifying best practices from public and private knowledge banks and suggesting appropriate wording to include in TSAs. Generative AI can also model the potential impact of different TSA components on the overall deal value, enabling dealmakers to make data-driven decisions during the negotiation process.
6. Post-deal value creation
Generative AI can support post-deal value creation by identifying potential areas of improvement and growth within the combined organisation. AI-driven tools can analyse data from both companies and generate actionable insights, helping executives and M&A professionals develop and implement effective post-deal strategies.
Challenges and Drawbacks
As well as its numerous benefits, generative AI also presents certain challenges and drawbacks. Data accessibility is of paramount importance. If generative AI bots cannot access a firm’s complete data sources, they may miss out on vital information that supports and enables many of the benefits outlined above.
Secondly, data quality and accuracy are critical for AI-driven tools to deliver reliable results. Incomplete or inaccurate data can lead to erroneous insights and adversely impact the M&A process. In addition, AI systems can sometimes exhibit biases in their output, which may lead to suboptimal decision-making.
Another challenge is the potential loss of human expertise and judgment in the M&A process. While AI-driven tools can assist in data analysis and decision-making, human experience and intuition still plays a crucial role in most successful M&A transactions.
Defining the Future of AI-Driven Deal-Making
Generative AI has the potential to revolutionise the M&A deal lifecycle by streamlining processes, providing data-driven insights, and facilitating more informed decision-making. As a growing number of M&A professionals and company executives recognise the transformative potential of AI in the deals process, the adoption of these technologies is likely to increase. To fully leverage AI in M&A transactions, however, professionals must be aware of its challenges and drawbacks, and strike the right balance between AI-driven tools and human expertise. By doing so, they can harness the power of generative AI to drive efficiency gains and unlock new opportunities in the rapidly evolving M&A landscape.
So, what next?
KPMG has a successful track record of helping businesses integrate technology into their operations that could aid in developing generative AI integration and adoption plans. Our Strategy Consulting, Connected Tech, and Digital Ninjas teams can provide expertise and support to help you exploit generative AI quickly, build out test cases, and enhance digital learning across your organisation. Ultimately, we believe in learning with our clients to provide customised solutions that meet the unique needs of you and your business.
As M&A continues to evolve in the digital age, it's clear that generative AI has an important role to play. If you're interested in maximising the potential of this technology in your deal lifecycle, consider exploring KPMG's AI 360 proposition. Our approach combines the power of generative AI with our deep sector knowledge and the well-established Nine Levers of Value framework, culminating in a prioritised list of AI use cases and recommendations to accelerate your AI adoption. Whether you're at the targeting phase or in the throes of post-deal value creation, AI 360 is designed to support every stage of the M&A journey. AI 360 is not just about technology; it's about the transformative power of AI when harnessed strategically.
We invite you to join us at the forefront of the AI revolution and discover how AI 360 can revolutionise your deal process.
