As Peter Gassner, CEO of Veeva Systems, the long-established cloud software provider dominating the life sciences industry, prepared to take the stage at the Veeva Commercial Summit in Boston, Salesforce made a significant counter-announcement: over 140 life sciences organizations are now actively utilizing its competing Agentforce Life Sciences platform. This assertive move signals an intensifying battle for market share in a sector increasingly reliant on advanced technological solutions, particularly artificial intelligence. Among Salesforce’s growing roster of clients are several marquee industry names, including pharmaceutical giants like Novartis, AstraZeneca, Moderna, and animal health leader Merck Animal Health, underscoring the platform’s broad appeal across diverse segments of the life sciences landscape.
Joe Ferraro, Senior Vice President and General Manager of life sciences at Salesforce, emphasized the breadth of Agentforce’s adoption. "The 140 represents customers across our entire portfolio," Ferraro stated, clarifying that client engagement spans various critical functions. "Regardless of whether they are using it for patient engagement, clinical engagement, commercial engagement, or medical engagement, these organizations are leveraging our platform." This positions Agentforce Life Sciences as a versatile, AI-native solution designed to integrate seamlessly across the full spectrum of life sciences operations, aiming to optimize every interaction point from drug discovery to patient support.
The timing of Salesforce’s announcement, coinciding with Veeva’s major industry event, highlights the direct competitive challenge. Veeva, for its part, is also aggressively pursuing an AI-centric strategy. At the Commercial Summit, Veeva CEO Peter Gassner articulated his company’s vision, stating, "The Agentic Commercial model changes everything about how we approach commercialization." Gassner pointed to a wide array of applications, "from digital and non-personal promotion" to transforming how field teams operate and streamlining content approval and creation processes. Both tech titans are clearly betting on the transformative power of agentic AI to reshape how life sciences companies engage with stakeholders and manage complex workflows.
The Accelerating Race for AI Dominance in Life Sciences
The current landscape reflects a rapid acceleration in the adoption of AI agents, with both Salesforce and Veeva vying for leadership. When questioned about Salesforce’s agentic AI strategy in comparison to Veeva’s, Joe Ferraro asserted Salesforce’s pioneering role. "Everybody is using agents now," Ferraro acknowledged, before drawing a sharp distinction. "Salesforce has been pioneering AI for the last decade, whereas many legacy systems have been slow to innovate. I would say a combination of our product vision two years ago, when we started this process of [building Agentforce Life Sciences], and customer pressure really forced Veeva’s hand on this." This statement underscores Salesforce’s confidence in its long-standing commitment to AI development, framing Veeva’s recent moves as a reactive measure.
Ferraro further differentiated Agentforce Life Sciences from Veeva’s offerings by emphasizing Salesforce’s deep-rooted experience in AI. "We are talking apples and oranges," he contended, reiterating, "We have been in the AI game at Salesforce since the predictive and machine-learning days." This historical perspective is crucial to understanding Salesforce’s strategic positioning. The company’s journey into AI dates back well before the recent generative AI explosion. At an internal all-hands meeting in 2014, CEO Marc Benioff famously declared Salesforce an "AI-first company." This declaration was swiftly followed by the acquisition of the machine-learning startup RelateIQ for approximately $390 million. Two years later, at Dreamforce in 2016, Salesforce launched Einstein, its first integrated CRM AI, marking a significant step in embedding AI capabilities directly into its core products.
In the years since, Benioff has consistently amplified Salesforce’s focus on autonomous agents, culminating in the launch of the Agentforce platform at Dreamforce in September 2024. Branding this new paradigm as "digital labor," Salesforce set an ambitious goal: to empower one billion agents by the end of 2025. This commitment is not merely rhetorical; it is backed by substantial investment and tangible results. On the company’s first-quarter fiscal 2027 earnings call on May 27, Benioff reported that Salesforce had processed an astounding 28.6 trillion AI tokens, representing a 152% increase quarter-over-quarter. He unequivocally called agentic AI "the biggest growth opportunity" for the company since it pioneered CRM in the cloud, with Agentforce’s annual recurring revenue already reaching an impressive $1.2 billion. This financial performance validates Salesforce’s aggressive AI strategy and its increasing traction in the enterprise software market.
Ferraro highlighted the scale of Salesforce’s engineering efforts dedicated to AI, stating, "We have thousands of engineers working on AI at Salesforce right now. There is nowhere near that scale for Veeva, so we are able to move a lot faster from an agentic standpoint." This emphasis on engineering might and rapid development cycles serves as a key differentiator in the intensely competitive AI space.
Veeva’s Strategic Counter-Moves and Platform Evolution
While Salesforce touts its long AI heritage and massive engineering investment, Veeva Systems is far from static. Recognizing the imperative to integrate advanced AI into its industry-specific solutions, Veeva has made significant strides, particularly in drug development. On May 27, Veeva announced Falcon, a new agentic platform and a suite of standard agents specifically designed for drug development. Falcon is built to run within Veeva Development Cloud, encompassing its clinical, regulatory, and safety applications, with early-adopter availability projected for November 2026. Peter Gassner positioned Falcon as the company’s "first offering in agentic labor," signaling a comprehensive push into this new era of intelligent automation.
Veeva’s journey into agentic AI, while perhaps presented as more recent by competitors, has been a strategic and methodical one. Its Vault CRM’s Free Text, Voice, and Pre-call agents went live in December 2025, providing early capabilities to enhance productivity and customer-centricity. The company’s public roadmap outlined the introduction of Safety and Quality agents for April 2026, and its 26R1 release saw the debut of a Narrative Agent for Veeva Safety, aimed at automating complex documentation tasks.
Beyond internal development, Veeva has also pursued strategic acquisitions to bolster its AI capabilities. In March 2026, the company acquired Ostro, an AI brand-engagement platform tailored for life sciences, for approximately $100 million. This acquisition significantly enhanced Veeva’s conversational AI prowess, enabling it to answer patient and healthcare professional (HCP) questions using only Medical, Legal, and Regulatory (MLR)-approved content, thereby ensuring compliance and accuracy rather than generating novel, potentially unverified responses. This approach aligns with the stringent regulatory requirements of the life sciences industry, prioritizing safety and compliance.
At its Commercial Summit, Gassner offered a preview of an upcoming Vault AI Tab, slated for release in August. This feature will introduce a conversational layer within Veeva Vault, allowing users to query their Vault data while adhering to existing security permissions. This ensures that AI-driven insights are contextually relevant and secure, operating within the established data governance framework that is critical for life sciences companies.
Philosophical Divergence: "Headless" AI vs. Integrated Platforms
The competition between Salesforce and Veeva extends beyond product features to fundamental architectural philosophies regarding AI deployment. Salesforce is making a significant bet on what it terms "headless" AI. Joe Ferraro described this strategy as "popping the top off the platform, exposing all the APIs, and exposing all the data models and workflows as MCP tools." MCP, or Model Context Protocol, is a standard introduced by Anthropic in 2024 and subsequently donated to the Agentic AI Foundation, a Linux Foundation-directed fund, in December 2025.
Salesforce’s "headless" approach means that instead of compelling users to operate exclusively within Salesforce’s proprietary interfaces, the company exposes its productized workflows as MCP servers. These servers can then surface within any AI tool a customer already uses. Ferraro provided a compelling example: "I was with a customer yesterday who has made a significant investment in Anthropic, and they are going to use our MCP service for Agentforce Life Sciences to bring all of those compliant workflows directly inside Claude." This strategy emphasizes interoperability and customer choice, allowing life sciences organizations to leverage their existing AI investments while still benefiting from Salesforce’s specialized workflows and data models. Furthermore, Salesforce supports a range of models for Agentforce, including Salesforce-managed solutions and customer-supplied models, offering flexibility in AI foundation.
Veeva, in contrast, adopts a more integrated, in-app approach. Its Vault AI Agents are specifically designed to run within Veeva’s own applications, working in-context against its proprietary data, documents, and workflows. This posture prioritizes depth within the application, ensuring that AI functionalities are deeply embedded and optimized for Veeva’s ecosystem. While third-party connectors like CData exist to expose Veeva data to outside models, Veeva’s core strategy for its standard agents involves a fixed model layer. These agents, including those in Vault CRM, run on Anthropic and Amazon models hosted on Amazon Bedrock. Model choice is only opened for custom agents, where customers can opt for Veeva-hosted models or bring their own on Bedrock or Microsoft Azure AI Foundry. This distinction highlights a fundamental divergence: Salesforce aims for broad, ecosystem-agnostic integration, while Veeva focuses on deep, optimized integration within its specialized vertical platform.
Compliance and Determinism: The Imperative in Regulated Industries
In highly regulated sectors like life sciences, the probabilistic nature of large language models (LLMs) presents a significant challenge. While LLMs excel at tasks like summarizing lengthy PDFs, predicting likely next tokens from context, life sciences workflows demand absolute predictability and determinism. Questions such as how often a sales representative can message a physician, the exact wording of the message, and the existence of explicit consent are not merely operational details but critical regulatory requirements. For this reason, determinism is a core theme dominating the discussion around agentic software in regulated industries.
Both Salesforce and Veeva recognize this critical need and have developed mechanisms to ensure compliance. Salesforce addresses this through a feature it calls Agent Script. This functionality weaves deterministic checks, pre-approved templates, and consent status directly into the probabilistic layer of its AI. This means that while the AI model can synthesize information and surface insights, any regulated action it proposes or executes must pass through a fixed set of tools backed by deterministic workflows and confined actions. Ferraro explained this safeguard, stating, "[The model] cannot go off script, because those tools are unavailable. The tools are outside its toolbox." This architectural design ensures that innovation in AI does not compromise the stringent regulatory frameworks governing pharmaceutical and life sciences communications and operations.
Veeva’s approach to compliance mirrors this commitment to determinism, albeit within its integrated framework. By running its standard agents in-context inside its own applications and against its verified data and workflows, Veeva ensures that AI-driven actions are inherently compliant. The controlled environment of Veeva’s platform allows for tight integration with existing regulatory safeguards, ensuring that all AI outputs and actions adhere to industry standards and legal requirements. This deep integration is a cornerstone of Veeva’s value proposition in a highly risk-averse industry.
Efficiency Gains and Transformative Industry Impact
The advent of agentic AI is already demonstrating tangible benefits, particularly in operational efficiency. Salesforce has observed that some of its smaller life sciences customers have completed onboarding processes in as little as a month, a remarkable improvement over traditional implementation timelines. This rapid deployment is partly attributed to the intelligent automation provided by AI agents, which significantly reduce the need for extensive teams of consultants typically required to oversee complex software implementations.
Joe Ferraro highlighted the transformative impact on resource allocation: "You get one forward-deployed engineer, and they can do the work of five or 10 previously, because they have Claude Code, or they have Codex, and they can point those tools at the Salesforce platform." This dramatic increase in productivity is exemplified by Salesforce’s own internal use of AI. For instance, Salesforce has built an MCP server within Agentforce Life Sciences that can configure the product itself. A task that a human would typically perform by navigating through multiple nested configuration screens – such as adding a quick action to an iPad app that launches a specific UI prompt – can now be executed automatically by an AI agent.
Beyond rapid onboarding, companies like Chiesi Group and CSL are leveraging Salesforce’s platform to unify vast amounts of customer data and coordinate engagement strategies across both commercial and medical operations. This consolidation of data and the application of AI agents empower these organizations to gain a holistic view of their customers and optimize interactions, leading to more personalized and effective engagement strategies.
The broader implications of this AI-driven transformation are profound. By automating routine tasks, streamlining complex workflows, and ensuring regulatory compliance, agentic AI promises to free up human capital to focus on higher-value activities, accelerate drug development cycles, enhance patient engagement, and ultimately drive innovation across the life sciences sector. The intense competition between Salesforce and Veeva is not just a battle for market share; it is a catalyst for pushing the boundaries of what is possible with AI in an industry that impacts global health. As these two technology powerhouses continue to innovate, the life sciences industry stands on the precipice of a new era of efficiency, intelligence, and transformative patient care.
