In mergers and acquisitions, both buyers and takeover candidates often underestimate the impact of artificial intelligence (AI). For example, the crucial role that the integration of AI plays in the success of a transaction is regularly overlooked, PwC experts Arjan van der Hall, Deepak Chadha and Lorenzo Casciscia note.
Generative AI has significantly expanded the landscape of artificial intelligence (AI), offering new capabilities and innovations. This also applies to the deals market. There we see a growing trend where takeover candidates emphasize AI as a competitive advantage. While potential buyers may hesitate due to perceived risks associated with AI. Regrettably, our findings indicate that the full spectrum of AI’s impact – encompassing both its opportunities and risks – is not always thoroughly evaluated.
AI has the potential to create new value chains
The transformative power and rapid pace at which AI is reshaping markets might be underestimated by many in the field. Moreover, the critical role that AI integration plays in the success of a transaction is frequently overlooked. It is crucial that both the opportunities and threats presented by AI are subject to a thorough analysis. AI has the potential to revolutionise business models and create new value chains, necessitating a strategic approach.
Investors must be equipped to assess the full impact of AI, both immediate and long-term, to make informed investment decisions. Our observations suggest that these dual aspects of AI are not receiving the comprehensive consideration they warrant.
According to research conducted by PwC, AI impacts nearly every industry, yet the extent of this impact varies considerably. In sectors such as financial services and ICT, AI is poised to affect over nineteen per cent of jobs. In contrast, industries like agriculture and hospitality will see less than a five per cent impact. These changes, and especially the benefits that AI has created, are often not sufficiently highlighted in the sales process. Consider higher turnover, for example, through the use of AI-driven recommendation engines, and lower costs for sales and marketing through AI-driven content creation.
Guidelines and protocols for specific AI algorithms
Beyond these opportunities, buyers face substantial risks if they fail to thoroughly investigate a company's AI utilization. A notable case occurred in February 2024 when Air Canada was mandated to compensate a customer misled by the airline's chatbot. Furthermore, the EU AI Act, enacted in March 2024, introduces stringent guidelines and protocols for specific AI algorithms, with penalties for non-compliance potentially reaching 35 million euro or seven per cent of a company's global turnover.
Investors must, therefore, critically assess the AI landscape of potential investments, determining their exposure to both commercial opportunities and operational risks. It is imperative to gauge their preparedness to adapt swiftly and effectively, and their governance structures for identifying and mitigating risks.
An exhaustive AI due diligence or AI exit readiness assessment should be conducted by a cross-functional team, comprising strategic, technology, and AI specialists, to provide a comprehensive perspective on AI's role. The assessment should encompass the following dimensions, with depth tailored to the business model:
- Strategy – A robust AI strategy should balance immediate gains with a well-considered long-term vision, projecting three to five years into the future. Investment decisions should be informed by market analysis, competitive landscape, and business evolution, allowing companies to decide whether to lead, follow swiftly, or modulate their investments.
- Applicability – The use of AI does not always necessitate perfectly structured data. For instance, ChatGPT has provided value for over a year without users intentionally supplying their data. While companies can leverage third-party data or AI applications for ancillary processes, a significant competitive edge requires high-quality, structured, and ideally exclusive data that is appropriately harnessed.
- Platform – Access to a scalable infrastructure is essential for deploying AI applications. Some organizations hesitate to operationalize AI due to the required IT investment, risking falling irreparably behind. Partnering with a credible cloud infrastructure provider can often mitigate initial costs and enhance scalability in terms of both capacity and expenses. Also, robust data management and rigorous security compliance are key to drive valuable insights and automation in a controlled manner leveraging internal and external data sources.
- Governance – Implementing risk-based protocols for the testing and monitoring of AI applications during development and production phases is crucial for successful deployment and long-term management. Effective collaboration between AI application developers and users is vital for rapid and successful adoption. Companies with well-organized governance will be more adept at executing their strategy and mitigating potential risks.
If a company has these four dimensions in order, it is well-positioned for substantial value creation through AI. However, it is evident that not all companies are fully capitalizing on this potential. AI is increasingly becoming a focal point during the sale or purchase of a company, but from our vantage point, it is not addressed often enough.
Don't overlook the impact of AI in your M&A processes. Conduct a thorough AI due diligence or AI exit readiness assessment to fully understand the opportunities and risks associated with AI.
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