Key facts
- Société Générale strategist Manish Kabra outlined a three-part AI investing playbook.
- The playbook categorizes opportunities into AI builders, AI sellers, and AI users.
- AI builders include chipmakers, data center stocks, and power companies.
- AI sellers are companies monetizing AI through their models.
- AI users are companies improving their economics and margins through AI adoption.
- Financials, healthcare, and industrials are identified as leading sectors for AI productivity gains.
Société Générale is advising investors to maintain their exposure to the AI-driven market, noting that new phases of the trade are emerging and expected to continue driving returns. Manish Kabra, the bank's chief US equity strategist, stated in a client note that after significant infrastructure investment over the past three years, AI value creation is expanding into downstream applications and services.
Kabra highlighted that evolving use cases and a growing ecosystem of software, agents, and physical AI applications are broadening the investment opportunities. This includes not only infrastructure providers but also companies directly profiting from AI products and those benefiting from productivity gains due to AI adoption. Meta's agentic AI model, Muse, is cited as an example that has renewed optimism about AI's monetization potential and the ongoing investment in developing AI agents.
To capitalize on the AI theme, SocGen has developed a three-part investment strategy:
AI builders: This segment focuses on the AI infrastructure trade, encompassing chipmakers, data center companies, and power providers that are benefiting from substantial capital expenditures by hyperscalers. Kabra identified specific stock picks within five areas of the supply chain: chipmaking enablers (Applied Materials), chipmakers (Nvidia), server and networking providers (Arista Networks), power suppliers (GE Vernova), and cooling solutions (Vertiv).
AI sellers: This category includes companies that are monetizing the AI buildout through their AI models, where adoption directly translates into revenue. Examples include hyperscalers like Microsoft, cybersecurity firms like CrowdStrike, AI software and data companies like Salesforce, and physical AI companies like Tesla. Partnerships with AI developers like OpenAI and Anthropic are accelerating monetization for some of these firms.
AI users: This segment comprises companies that are leveraging AI to enhance their underlying economics and increase profit margins. SocGen screened for companies with strong future revenue potential and rising earnings per employee. The financial, healthcare, and industrial sectors are identified as leading areas for AI productivity gains, with example stock picks including JPMorgan (financials), Eli Lilly (healthcare), and GE Aerospace (industrials).