Salesforce is outsourcing its AI roadmap – to customers

Artificial intelligence continues to advance at breakneck speed, forcing companies to develop and release new products faster than ever before or risk becoming irrelevant to a fast-moving competitor.

Salesforce believes it has found a strategy that allows it to keep up even if it’s not clear where AI is going next. The customer management software giant is outsourcing its AI roadmap in real time.

Salesforce certainly isn’t the only company that works closely with its customers to get feedback on its products. However, it is noteworthy given the sheer size of the company, the pace of new product launches or overhauls of existing products, and the granular level of these relationships. These are not annual or even quarterly discussions. Salesforce meets with some customers once a week.

“Our 18,000 customers are a source of information and a wealth of information that is really needed to achieve customer success,” Jayesh Govindarajan, executive vice president of Salesforce AI, told TechCrunch in a recent interview. “The suite we built resonated with these agents. Over time, we can make the context better, and as it improves, and the LLMs improve, the agent systems do more and more fully autonomous behaviors. This is a long-term innovation path that we will invest in.”

Salesforce was one of the first companies to launch AI agent management software in late 2024 before agent AI began dominating headlines the following year. Since then, the company has doubled down on its efforts and continues to launch new Voice AI and Slack products at a rapid pace.

Salesforce credits its customers with the rate of its product releases. The company told TechCrunch that by letting its customers lead the way, it is able to build an AI product roadmap that can quickly react to where AI technology is headed.

When large language models were introduced, companies naturally wanted to jump on the technology but didn’t have the last-mile technology needed to fully utilize LLMs, Muralidhar Krishnaprasad, president and CTO of Salesforce Engineering, told TechCrunch.

The need for last-mile technology is what prompted Salesforce to launch its agent management platform Agentforce, said Jayesh Govindarajan, executive vice president of Salesforce AI, in a recent interview.

Hence, the company developed a bottom-up strategy driven by themes – including agent context, observability, and deterministic controls, among others – rather than specific timelines for a product. This approach uses direct feedback from rotating customer groups to build products with the assumption that other organizations will have similar needs.

Customers are in the driver’s seat

“The innovation we have introduced is a direct result of our work with a large number of these customers and then profiling the problems they see in the real world,” Govindarajan said. ‘then [we break] Come down and say, which of these can be solved in the LLM layer, and which can’t? And for things that we can’t solve in the LLM layer, we need to build these kind of agent OS components around the LLM so we can do that.

Working closely with customers’ engineering teams allows Salesforce to quickly fix issues before the technology evolves beyond them.

“We can’t wait three or six months to get feedback and then start thinking about another six months of work,” Krishnaprasad said. “We’re literally interacting with it, week after week, month after month. This has been a huge change. Now we’re pushing the code, very quickly, and we have different kinds of gateways to try out new features, and we get early feedback before we release it broadly as well. So, these are all changes we had to make to accommodate this rapid change in this environment.”

Engine, a travel management platform, is one of the companies in Salesforce’s customer feedback loop. It is not a casual relationship. The company’s operations team meets with Salesforce weekly, according to Engine founder and CEO Elia Wallen.

Through the partnership, Engine has access to AI tools before they are released. The access helps Engine remain competitive and get more value from these tools than it would have otherwise, Whalen said.

The relationship goes both ways.

Whalen said he saw feedback from Engine implemented into Salesforce tools. For example, Wallen said he instructed an AI voice agent to book him a hotel in Chicago. He thought the audio and interaction were a bit unnatural and shared that with Salesforce. Soon after, the agent was changed and the company’s A/B tests started showing better results.

“If someone is willing to actually help organize and build the products we need, they can help us better and really understand our problem and how they can solve it,” Whalen said. “For us, it’s great to be invited to something like this, because we can influence the product.”

This strategy also allows the company to roll out user-generated solutions and workflows to its broader customer base as well.

PenFed Federal Credit Union was able to shrink its technology stack by working closely with Salesforce, Shree Reddy, the company’s chief innovation officer and executive vice president, told TechCrunch.

“We invest our time and energy in the most strategic platforms, and we obviously spend a lot of time in that relationship,” Reddy said of Salesforce. “This investment has yielded good results in terms of strengthening that partnership that influences each other, and what we see is the best mutual value-add for both organizations.”

PenFed developed an IT service management (ITSM) workflow on its own using existing tools and agents in Agentforce that have worked well for the company, Reddy said. Salesforce was able to see this success and spread the tool into the broader platform for other organizations to use as well.

The downside of this approach is that it relies on the classic service sense that the customer is always right. Salesforce hopes to do this even though many companies are still discovering the role AI will play in their businesses, and many have yet to find value from the technology. As a result, they may not be the best source for long-term product development.

Additionally, being willing to test and preview technology in beta now doesn’t necessarily translate into long-term usage habits or future software contracts either.

Be your own biggest user

The company also takes this bottom-up approach internally. Salesforce employees are the biggest users of its AI tools, Govindarajan said.

The company also shifted labor and resources at the beginning of the AI ​​boom. When ChatGPT was released, Salesforce moved teams and resources to create a new AI team — a strategy the company has found successful during various waves of innovation in the past, Krishnaprasad said.

“As technology changes, we never know what will happen a month from now,” Krishnaprasad said. “We’ll adapt to it. That’s what we’ve done for the past year. If you think about it, agents weren’t even in the terms when you look back a year and a half ago. Then we had to react to it. We had to react to all the developments, and we had to react to our customers.”