Managing key risks in deals involving proprietary AI systems

This whitepaper is part of a series focused on how IT can increase deal value and minimize business risks during a transaction. The series will highlight principles that the Technology M&A team in KPMG in Canada leverages to help maximize value and minimize risks for clients across industries.

In today’s market, there is a growing trend of Artificial Intelligence (AI), which is intelligence demonstrated by machines, helping modern businesses increase revenue and boost operational savings. In particular, the applicability of AI technologies for a variety of use cases has enabled value creation for organizations across multiple industries, including IT services, health care, cybersecurity, financial services, retail, manufacturing, and transportation and logistics.

In recognition of AI’s benefits, private equity firms and corporations are progressively acquiring companies that leverage AI capabilities. According to the Global AI market report published by Drake Star Partners, the M&A activity in AI has experienced sixfold growth since 2015, reaching $12.3-billion in total disclosed transaction value in 2022. While IT services has led in terms of volume of capital invested, cybersecurity has seen the highest growth in deal count with an astonishing compound annual growth rate (CAGR) of 135% between 2016 and 2021.

Additionally, Canadian insights from a global survey by KPMG International reveal 95% of technology leaders at private- and public-sector organizations in Canada plan to invest in Web3, 70% plan to invest in 5G and edge computing, 67% plan to capitalize on quantum computing and 54% plan to invest in the metaverse over the same period. All of these technologies rely on AI to power the respective use cases.

While AI has increasingly embedded itself into organizational processes, we have seen a number of commercial, technology, organizational and data security risks inhibiting successful value creation in the deal context. Our objective for this whitepaper is to present a framework that would enable buyers to proactively identify and mitigate these risks in the pre-deal due diligence phase, in order to create value from proprietary AI systems after the deal.

We have seen a growing trend of AI technologies enabling key operational processes across industries, and increased deal activity in the AI space.

However, M&A deals involving such technologies can create several commercial, technology, organizational and data security risks.

We have presented a framework containing key considerations for buyers to mitigate these risks.

The framework can help structure the assessment of the seller’s product roadmap, technology tools and processes, talent strategy and data security mechanisms. Proactively managing the key risks early in the deal process can help maximize the value of AI systems and position the buyer for digital leadership.

Download the PDF below to read the full whitepaper.