Salesforce's $50B Buyback Plan Stirs Debate Over AI Investment vs. Shareholder Returns

What happened

Salesforce has announced a record $50 billion stock-buyback program to repurchase shares amid a sector-wide software selloff that has driven its stock price down sharply. Wall Street is contesting this move, arguing the capital might be better spent on bolstering artificial-intelligence capabilities to secure long-term growth against competitors. The DeepValue report notes Salesforce already demonstrates material AI monetization with Agentforce ARR near $1.4 billion and backlog growth holding firm, but flags risks in consumption pricing and margin durability. This buyback, while leveraging strong cash flow from operations, risks appearing as a short-term fix that could underfund critical AI investments needed to sustain expansion. Critically, management's capital allocation now faces heightened scrutiny, with the potential to erode investor confidence if AI progress stalls due to resource constraints.

Implication

The buyback may temporarily support the stock price by reducing share count and signaling management's belief in undervaluation, but it diverts substantial capital that could accelerate AI development in a competitive landscape. If AI investments are shortchanged, Salesforce risks falling behind in agentic AI adoption, threatening the revenue growth and margin expansion central to the investment thesis. DeepValue's monitoring points, such as cRPO growth and Agentforce ARR metrics, become even more critical to verify that buybacks aren't compromising strategic bets. Over the medium term, this move could strain the balance between shareholder returns and growth funding, especially if restructuring costs persist or AI economics disappoint. Ultimately, investors should demand clarity on AI investment levels and integration progress to ensure capital allocation aligns with long-term value creation rather than short-term optics.

Thesis delta

The buyback announcement amplifies the cash return aspect of the thesis but introduces a new risk of capital misallocation away from AI investments. This does not fundamentally alter the core thesis—which still hinges on AI monetization and backlog growth—but adds a layer of uncertainty around management's prioritization. If future disclosures show AI funding lagging or competitive pressures mounting, the thesis could degrade, requiring a reassessment of growth sustainability.