Following reports suggesting that Salesforce regretted firing thousands of employees and replacing them with AI agents, the company has issued a clarification disputing key claims around job cuts and its artificial intelligence strategy. In an email response addressing the report titled “Salesforce regrets firing 4000 experienced staff and replacing them with AI agents”, Salesforce said it did not lay off 4,000 employees, but instead carried out a strategic rebalancing of roles. The confusion, the company noted, stemmed from a video interview of CEO Marc Benioff dated August 29, 2025.
According to Salesforce, the company redeployed roles internally—primarily shifting headcount from support functions into sales—to strengthen distribution capacity, rather than reducing its overall workforce. The move was described as a redeployment of talent aligned with evolving business priorities, not a workforce downsizing exercise.
Salesforce also pushed back against claims that it is retreating from large language models (LLMs). The company said its current approach reflects optimisation rather than withdrawal, as enterprises move from pilot projects to production-scale AI deployments. Salesforce emphasised that real-world AI applications require more than raw model capability, pointing to the need for accurate data, business logic, and governance to ensure predictable and trusted outcomes.
Clarifying remarks made earlier by Sanjna Parulekar, senior vice president of product marketing, Salesforce said her comments on “trust” were taken out of context. The company explained that these statements were aimed at customers transitioning from experimentation to production environments and did not signal any loss of confidence in LLMs. Instead, they underscored the importance of augmenting models with proprietary data, safeguards, and deterministic systems for enterprise reliability.
The clarification follows earlier reporting that Salesforce had reduced its support workforce from 9,000 to 5,000 employees as part of a broader push toward agentic AI. Benioff had mentioned this shift during a podcast, which later fueled interpretations that thousands of jobs were eliminated in favour of AI agents.
Reports also cited challenges faced by customers using Salesforce’s Agentforce platform, including reliability issues in real-world deployments. These included instances where AI agents struggled with long instruction sets or lost focus when presented with irrelevant queries. Such concerns were highlighted through examples like home security firm Vivint, which uses AI agents for customer support at scale.
Responding to these issues, a Salesforce spokesperson told The Times of India, “While LLMs are amazing, they can’t run your business by themselves. Companies need to connect AI to accurate data, business logic, and governance to turn the raw intelligence that LLMs provide into trusted, predictable outcomes. That’s why we built Agentforce: trusted AI infrastructure that drives real business value. We ground AI in tight guardrails and deterministic frameworks, optimising LLMs to deliver enterprise-grade reliability. Trusted, Reliable, Secure. This is what AI is meant to be.”
Salesforce maintains that its AI strategy remains firmly focused on augmenting human capability—not replacing it—while building systems designed for enterprise-scale trust and reliability.
