Despite tech M&A activity receding from the prodigious exalted highs achieved post-pandemic, due to artificial intelligence’s (AI)’s flair for self-rejuvenation, there are compelling tailwinds propelling a 37 per cent compound growth in AI-based M&A between 2022-2030, valued at $984 billion by 2030. 58 per cent of PE and 38 per cent of corporate firms forecast an increase in volumes, 51 per cent predict an upsurge in deal values, as a reflection of the deep stores of accessible dry powder.
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Primary drivers of AI and tech M&A strategy are increasing competitiveness and keeping pace with technological advancements. Here are some noteworthy trends. AI playing a disruptive and transformative role. While global corporate investments in AI have diminished post pandemic, tech giants continue to invest heavily in AI development.
Turbocharge diligence is required for generating agile winning synergies. AI serves as a force enhancer – boosting efficiency, optimizing document review, data mining, rapid identification, and extraction of key provisions – thereby increasing M&A activity.
Data Protection – Intensifying (data driven) AI deals expand multi-jurisdictional compliance, with sanctions for processing illegally obtained personal data including erasure of databases and algorithms (‘algorithmic disgorgement’ imposed in US). Hence investors must closely review identified risks impacting valuation and remedy them (if feasible) as a pre-closing action item.
Regulators Scrutiny – Few jurisdictions trigger scrutiny upon transferring of ownership in AI technologies. Thus, AI acquirors / targets must secure prior regulatory approvals.
Antitrust Review – Concentration of data in the hands of a competitive acquiror may raise antitrust concerns increasing transaction costs and time to closing. US and European regulators are challenging “killer” acquisitions of nascent competitors.
Environment – AI tools have dual impacts harming and improving the environment, while they are the heaviest carbon emitters, some AI systems can optimise energy usage. With environmental, social and governance (ESG) being the biggest theme driving M&A activity in Q2 2023, AI acquirors / investors should evaluate the target’s carbon efficiency and net-zero strategies.
Workforce Training is required to meet the soaring demand for AI trained talent pool. McKinsey suggests that AI impact will predominantly require reskilling the workforce, without any decrease.
Buy and Sell Side Considerations –2023 is a buyers’ market.
Buyers are eager to know the target’s:
Generative AI and technological transformation capabilities
AI training and talent retention policies
ESG, sustainable transformation and CO2 reduction tools
Sellers are to postulate:
AI and technology transformation roadmap targets
New cost-saving capabilities.
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AI tool / platform – upsides and risks analysis
Reskilling talent strategies
Data evidencing AI tools meeting the sustainability reporting requirements.
AI USE CASES:
Automotive: in design, production; vehicle maintenance and autonomous driving.
Retail: In predictive logistics; customer service; tracking sustainable measures; generative AI to address customer queries, provide purchase suggestions through chatbots.
Energy and Utilities: In smart grids, smart meters, and grid management; AI analyzes usage patterns, predicting future demand. US and UK, use AI smart grid strategy to avoid blackouts and develop cloud-based analytics. In Q2 2023, AI accounted for $50mn worth of oil and gas deals.
Financial and Identity Management: In algorithmic trading, automated investing and detecting fraudulent patterns. In September 2023, Punjab and Haryana HC using the AI powered facial recognition solution found 11 mobile connections issued using identical photographs, fake names, and tampered identity documents.
Healthcare: In drug discovery and diagnostics, AI recommends personalized treatment options.
Education: AI supports in personalized, innovative, and immersive edtech solutions with automated assessments, augmented and virtual reality, student enrollment, and smart tutoring tools. In Edtech, Indian and US courts require investors to verify the AI tools’ quality and data security parameters.
Music / Media: Music videos are synchronized through AI. In August 2023 Columbia court mandated human creativity / authorship as fundamental for copyright eligibility, thereby denying copyright to AI works generated, without human involvement.
Pharma and Medtech: Telemedicine, nanotechnology, robotics and 3D printing use AI, machine learning and virtual reality.
Agriculture: Robotics automates soil and crop monitoring and optimizes resource management. Predictive analysis, accesses real-time market information. AI-powered weather forecasts; automated tractors for plant harvesting, cultivation, fertilization, and potato cultivation facilitate informed decisions and meeting sustainability targets, thereby mapping deforestation.
Supply Chain Management: AI predicts potential goods movement bottlenecks. Amazon uses AI for predictive logistics and Walmart for planning inventory levels, and mapping demand.
Critical concerns
Tech M&A trends in the next 3 years include the rise of industry disruptors like generative AI taking the lead. Q2 2023 witnessed 7 new AI unicorns — including 5 generative AI companies. Currently 40 per cent of AI deals are with US-based start-ups, however Indian markets are steadily making AI strides, generating $1.11 billion funding in 2023.
The first international summit on AI safety (in November 2023), witnessed multilateral agreements for testing AI models, international declarations addressing AI risks, and United Nations supporting an expert AI panel.
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While AI accelerates swift, efficient M&A deals, however, privacy, cyber security, accuracy, reskilling, ecological sustainability, and eliminating algorithmic bias are critical points to be considered by the acquirors and investors.
