Generative artificial intelligence (AI) is poised to trigger a transformative shift across various industries, with the potential to unlock a surge in mergers and acquisitions (M&A) activity, as outlined in a comprehensive white paper released by Goldman Sachs Global Banking & Markets.
The paper emphasises the necessity for a significant shift in the adoption of generative AI solutions, progressing beyond proof-of-concept stages towards full-scale production. The crucial transition from training AI models to the inference phase, where these systems can effectively discern and respond to novel situations based on their prior training, is pivotal for driving M&A momentum.
In tandem with technological readiness, the M&A landscape hinges upon a matured legal and regulatory framework. Furthermore, it demands greater clarity concerning the structure and function of foundational AI models – whether they will be sizeable and proprietary or compact and open-source.
The white paper underscores, “As clarity on these critical facets is attained and AI applications evolve, the M&A arena will inevitably transform. Specialised generative AI applications will emerge, leading buyers to adopt a proactive stance, targeting proven entities with established product-market alignment.”
Indeed, the past year witnessed a notable upswing in strategic activity, commencing in January, marking a turning point. In the wake of this pivotal moment, several major incumbent technology giants made substantial investments in or acquisitions of generative AI startups. Notably, some of these targets were early-stage companies devoid of revenue, acquired primarily to harness the talent pool they offered.
Nonetheless, post this initial surge, M&A activities may be constrained until AI enterprises substantiate their potential and the sector attains maturity. Yet, discernible M&A theses are already emerging.
Emerging M&A Themes
One potential focal point for M&A activity, as suggested by the paper, is intelligent vertical applications. The amalgamation of AI capabilities with industry-specific datasets promises increased operational efficiency, expedited product launches, and enhanced end-user experiences. This phenomenon is currently being observed across sectors like education, media, and law.
Another potential avenue for M&A lies in the transformation of customer support activities and contact centres. AI is anticipated to revolutionise customer interactions, providing empathetic, personalised experiences and automated solutions for addressing customer and product-related issues.
Enterprises’ imperative to transition onto foundational AI models and cloud services may fuel another M&A trend. Key to this transition is the growing significance of interconnections between semiconductors, software, and systems. An array of components, ranging from data centre design to software applications to privacy systems, must seamlessly integrate to manage increasingly complex AI use cases. In the modern computing era, the epicentre of control may well be closer to the silicon foundation of AI infrastructure.
Convergence between analytics platforms and DevOps-MLOps is also on the horizon. Given the pivotal role of data science and analytics in machine learning, these functions are becoming integral components of the new enterprise technology stack. Consequently, tools for DevOps, facilitating the integration of software and IT, are primed to amalgamate with analytics platforms to form cohesive systems.
The rapid adoption of generative AI technologies is unprecedented, presenting a unique moment for decision-makers, investors, and the wider public. As the paper observes, “Venture capitalists are eager to invest in the next disruptive AI startup, public market investors seek insight into AI’s impact on all sectors, and companies are keen to understand how AI will fundamentally reshape the strategic landscape.”
In conclusion, the prospect of an AI-driven M&A supercycle looms large, contingent upon the alignment of several critical factors and the ongoing evolution of the generative AI landscape. The future holds significant promise, with the potential for AI to redefine industries and catalyse transformative mergers and acquisitions.