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April 30, 2026 • Rebecca Szkutak

Salesforce Crowdsources AI Roadmap With Weekly Customer Feedback

Salesforce Crowdsources AI Roadmap With Weekly Customer Feedback Salesforce Crowdsources AI Roadmap With Weekly Customer Feedback Salesforce Crowdsources AI Roadmap With Weekly Customer Feedback

Salesforce is Crowdsourcing Its AI Roadmap — With Customers

Artificial intelligence continues to advance at a dizzying clip, forcing enterprises to develop and release new products quicker than ever or risk becoming irrelevant to a faster-moving competitor.

Salesforce believes it has found a strategy that allows it to keep up even if it isn't clear where AI is headed next. The customer management software giant is crowdsourcing its AI roadmap in real time.

A Bottom-Up Strategy Led by Customer Feedback

Salesforce is meeting with some customers as often as once a week, using direct feedback from rotating groups of customers to build products with the assumption that other enterprises will have similar needs.

Key approach elements:

  • Theme-driven development (agent context, observability, deterministic controls) vs. specific product timelines
  • Weekly engineering meetings with select customers
  • Rapid code deployment and iteration cycles
  • Assumption: if one enterprise customer has a problem, others likely do too

"The 18,000 customers are a wellspring of information and a wealth of information that is really needed to get to customer success," said Jayesh Govindarajan, executive vice president at Salesforce AI.

Real-World Implementation Examples

Engine (Travel Management Platform)

  • Meets with Salesforce operations team weekly
  • Gets access to AI tools before public release
  • Provided feedback on AI voice agent that was implemented shortly after
  • Example: Instructed voice agent to book Chicago hotel, noted unnatural interaction, saw improvement in subsequent A/B tests

PenFed (Federal Credit Union)

  • Developed ITSM workflow using Agentforce tools
  • Salesforce observed success and rolled out the tool platform-wide for other enterprises
  • Able to slim down tech stack through close partnership

The Philosophy Behind the Approach

Problem identification: When LLMs were introduced, enterprises wanted to use the technology but lacked the "last-mile tech" needed to fully leverage them. This sparked the launch of Agentforce.

Rapid iteration cycle:

  • "We can't wait three months or six months to get feedback, and then go figure out another six months of work," said Muralidhar Krishnaprasad, president and CTO of Salesforce engineering
  • "We are literally reacting to it, week by week, month by month"
  • Various gates to test new features and get early feedback before broad release

Internal Practices

  • Salesforce employees are the biggest users of its AI tools
  • Company shifted labor and resources at the start of the AI boom
  • Created new AI team by moving around existing teams when ChatGPT was released

Potential Risks

  • Relies on "customer is always right" philosophy
  • Many enterprises still figuring out what role AI will play in their business
  • Many have yet to find value from the tech
  • Customers might not be the best source for long-term product development
  • Beta testing doesn't necessarily translate to long-term usage or future contracts