5 Go-to-Market Lessons from Selling AI to Conservative Industrial Giants

5 Go-to-Market Lessons from Selling AI to Conservative Industrial Giants

When Berk Birand founded Fero Labs in 2015, AI was still viewed with skepticism in industrial manufacturing. In a recent episode of Category Visionaries, he shared how they won over multinational manufacturers and built a profitable sustainability platform. Here are the key go-to-market lessons from their journey:

1. Never Do Free Work – Even When It Hurts Most startups eagerly offer free pilots to land their first enterprise customers. Fero Labs took the opposite approach. “One of my advisors in the early days told me to never do that, to always, even if it means hurting your chances of getting this customer, don’t do free work,” Berk explained. The reasoning was clear: “If you do that, then companies will see you as kind of an extracurricular activity of sorts. They’ll see as a way to learn from you as much as they could, so that to see if they could build it internally.”
2. Lead with Humility While Owning Your Expertise When selling to experts in traditional industries, acknowledge their domain knowledge while being clear about your unique value. “Being very upfront, being very humble since day one, very clear that we don’t know anything about steel,” Berk shared. “Our value add here is not steel production. It’s not chemicals production. What we bring in is the data science part, and you guys are the experts.”
3. Find and Empower Internal Champions Their first major customer came through a champion who believed so strongly in their solution that he signed the contract before IT security reviews were complete. As Berk recalled, “This champion of ours just signed the contract. And then the IT team was like, wait a second. We’re just going through the IT security steps here. And then he goes, well, I signed the contract. What do you mean?”
4. Make Complex Technology Trustworthy For AI adoption in critical industrial processes, explainability is key. “Our software also tells them why these predictions, what recommendations are made,” Berk noted. “And as a result, there was this human in the loop aspect that actually reduced the off chance of something going wrong. And really making sure that they knew that they were in the loop and they were in control of what was going on was also a key part.”
5. Align with Broader Industry Trends While sustainability wasn’t hot in 2015, Fero Labs positioned their solution as “profitable sustainability” – connecting environmental benefits with bottom-line impact. “Our goal all along was to reduce waste, reduce industrial waste using AI,” Berk explained. “Initially our pitch to our customers was, well, using this, you’ll waste less raw materials, you’ll waste less processing time, and as a result you’ll become more profitable.”

The results validate this approach. At one customer’s steel plant, following Fero’s AI recommendations saved a million pounds of raw materials in a single year. This tangible impact has positioned them to pursue an even bigger vision: “The industrial sector is very much like an organism, where you have factories that produce one thing in one side and then send it to the other. And I really believe that we can go from optimizing a single factory to optimizing the entire organism using AI.”

For technical founders targeting enterprise customers, these lessons show how to overcome initial skepticism and build lasting relationships. By maintaining pricing discipline, respecting customer expertise while being clear about your value, and ensuring your technology empowers rather than threatens users, you can successfully sell innovative solutions even in the most conservative industries.

The key is patience and conviction in your approach. As Berk concludes, “I believe that in 5-10 years, AI machine learning will be a core part of every factory in the world.” By following these principles, technical founders can position themselves to capitalize on similar long-term industry transformations.