Salesforce co-crea su estrategia de IA con clientes.

Artificial intelligence (AI) has been advancing rapidly, compelling companies to innovate and launch new products at unprecedented speeds. Amidst this technological race, Salesforce has adopted a distinctive strategy to navigate the unpredictable landscape of AI: crowdsourcing its AI roadmap in real-time from its extensive customer base.

Salesforce’s approach is notably proactive given its size and the swift pace of product deployments. Unlike traditional feedback cycles that may occur annually or quarterly, Salesforce engages with select customers weekly. This level of interaction enables the company to tailor its offerings more closely to user needs. Jayesh Govindarajan, executive vice president at Salesforce AI, emphasizes the value of insights from their 18,000 customers. He believes these insights are crucial for driving innovation and achieving customer success.

Already a pioneer in AI agent management software, Salesforce launched its Agentforce platform in late 2024, positioning itself ahead of competitors in a rapidly shifting market. The company’s commitment to releasing products—focused on voice AI and collaborative tools like Slack—has only intensified since then. By leveraging customer feedback, Salesforce can swiftly adapt its AI product roadmap to align with the evolving technological landscape.

When large language models (LLMs) gained prominence, many enterprises sought to leverage this technology, yet many lacked the requisite tools for effective implementation. This gap sparked Salesforce’s initiative to enhance its agent management offerings. Govindarajan notes that the company’s strategy is based on identifying and categorizing real-world problems presented by customers, addressing those that can be tackled at the LLM level, and developing complementary components where necessary.

This hands-on collaboration allows Salesforce to resolve issues quickly, adapting to technological advancements without delay. The company is now able to push code and gather feedback continuously, altering its workflow to match the acceleration of AI evolution.

Customer partnerships, like one with Engine, a travel management platform, involve weekly meetings where they discuss AI tool enhancements. Such access affords Engine a competitive edge, letting them maximize the utility of Salesforce’s products while contributing to their development. This reciprocal relationship has demonstrated tangible impacts; for instance, feedback from Engine regarding the AI voice agent led to practical refinements that enhanced performance.

PenFed, a federal credit union, shares a similar narrative. By collaborating closely with Salesforce, PenFed minimized its technological footprint while enhancing operational efficiency through custom-built workflows that Salesforce has subsequently shared with its broader customer network.

However, this strategy isn’t without its challenges. Relying heavily on customer insights assumes that these enterprises are consistently clear about their future needs in AI. Given that many are still grappling with identifying AI’s role, the feedback may not always be a robust compass for long-term product direction. Moreover, what may work in beta tests does not always guarantee enduring adoption.

Internally, Salesforce encourages a culture of innovation by utilizing its own AI tools, ensuring that employees are the primary users. The company adapted its organizational structure at the onset of the AI boom, shifting resources to establish a dedicated AI team—an approach that has proven effective in responding to past technological shifts.

In conclusion, Salesforce’s unique strategy of engaging customers directly in the innovation process exemplifies a dynamic approach to AI development. The ongoing evolution of this field demands flexible and immediate responses, and Salesforce’s commitment to real-time feedback positions it to remain at the forefront of AI advancements.

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