How To Sell AI

Companies like and Palantir have shown that selling AI technology can be quite lucrative. After all, these companies command significant market caps and are growing quickly.

Yet selling AI technology remains difficult. Customers often want customized solutions that are based on their unique data sets. There are also the issues of adoption. The fact is that many AI projects fail to go beyond the proof-of-concept phase.

Then what are some ways to sell AI technologies? Let’s take a look:

It’s Not About Platforms: Many AI vendors extol their “platforms” that can seemingly solve any problems. But this approach is usually off the mark. Let’s face it, there are already top platforms that have solid features and powerful ecosystems.

“Businesses should sell a solution to a problem,” said Muddu Sudhakar, who is the CEO and founder of Aisera. “Customers will buy a platform when multiple solutions are acquired and there are the right integrations. Customers don’t have free money sitting on the side just to invest in platforms.”

Sudhakar believes that an AI solution needs to show value within three to six months and there must be a return on investment within the first year.

Insights: It is often fuzzy as to what an AI system does. But for businesses, one of the most compelling aspects of this technology is about getting insights on tough questions. 

Take the example of Founded in 2016, the company is focused on leveraging AI for the talent management category.

“A lot of the problems that organizations are looking to solve are intimidating because they don’t always have a clear answer,” said Kamal Ahluwalia, who is the President of “There’s no one second solution to ‘why can’t I hire the right people’ or ‘what skills do I need to be teaching my team so we’re ahead of the game in a few years?’ But the data is there, and it’s usually just not being looked at correctly, or it’s not feasible to do so for thousands or millions of times over. AI is all about applying that data, at scale.”

Avoid AI-Speak: AI is a complex topic. There are a myriad of terms like machine learning, hidden layers, deep learning, backpropagation and so on. Even people in the industry can have a difficult time explaining the concepts.

This is why it is critical to avoid the jargon when selling AI. “Rather than explaining the wonders of AI, it’s better to provide practical steps that you can take together with a customer to achieve the desired business results,” said Thomas Hansen, who is UiPath’s Chief Revenue Officer.

The Buyer Persona: AI is still in the early stages and many of the potential buyers are early adopters. This means that they have a strong understanding of their needs and a good sense of what’s available on the market. They are also more willing to use software that is 90% finished and then find ways to fill the gap, such as with custom coding or configuration. 

True, executives will still write the checks. But they will still rely heavily on the AI practitioners within the organization. 

“The AI buyer persona prefers a self-service and hands-on approach,” said Omed Habib, who is the Vice President of Marketing at “They don’t need to speak to a sales person and would rather sign up for an account immediately. They’re curious. They’re self learners. They love to tinker. So, the companies that have figured this out have created flawless self-service sign up for their software. They have excellent documentation. They have a vast library of videos to help enable their customers. They host a community forum for other users to share knowledge. In other words, they’re not just teaching you how to fish but they’re putting the best fishers in the same room to learn from each other.”

Data: Customers are understandably sensitive when providing access to their data to a third-party. This is why an AI vendor needs to have strong data policies.  

“It’s important that sales teams are educated on these features and understand the compliance and certifications that the software or organization holds,” said Sid Mistry, who is Appen’s Vice President of Marketing. “Company data is gold; you need to value and respect that.”

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