One thing was clear: investors want to see a product that solves a specific problem or improves a specific process—not just a standalone innovation. Leaders all discussed how it’s not only about the technology but also what you do with the technology to solve pain points, optimize workflows, augment talent, structure data, and more. “AI is a tool bag of tools for a bag of problems,” explains Ganesh Padmanabhan, the CEO of Autonomize AI, a trusted generative AI company helping healthcare and life sciences organizations unlock value from data.
How can you make your AI company appeal to investors? Discover an insider’s take on what sparks investors’ interest, from highlighting workflow to differentiating with data.
- Be clear about the problem you solve
“We have a lot of people come to us without knowing the problems they’re trying to solve, but just with the intention of using AI to do something,” says Neil Alliston, the EVP of product & commercial at Ravin AI, an AI company that’s reimagining vehicle condition reports. “That inevitably leads to lots of conversations and not any tangible impact because AI shouldn’t change how you look to generate value.” His take? Start with the fundamentals: Look at what problems you’re trying to solve, what use cases are, and what products and services solve those problems. “And if those products use AI then that’s fantastic, and if they don’t, that’s totally ok too,” he adds.
- Highlight your infrastructure and workflow
The first thing Jackie DiMonte, the co-founder of Grid Capital, a venture capital firm investing in industrial technology companies, looks at is whether the infrastructure exists. Even though you might have a problem solvable with AI, she wants to know if you can run an AI model, feed the correct data into those models, and then apply it to solve said problem. The next question DiMonte asks is, what’s the workflow? “The solution must be part of something and not the result itself…We have to figure out how to integrate solutions with day-to-day workflow that customers and consumers are excited to adopt,” she says.
- Focus on low-risk for starters
Alliston suggests focusing your AI product or service on something that isn’t a high risk, whether a safety, commercial, or legal risk. (At least at the start.) Yasir Motiwala, head of sales at Americas at DeepL, a global AI communications and translation company, agrees, noting how many companies are scared of adopting AI. “It’s important for companies to test the waters with a solution that will not cause panic and will not cause risk to the business,” says Motiwala. Once you show you can deliver business value in a particular area, people will gain confidence, and then you can expand your impact.
- Examine how you can augment talent
Consider how AI can unlock existing talent and help people up the learning curve faster, says DiMonte. Take a mechanic, for example, “What if we could get superstar mechanics and allocate or direct them to the most important work at any point in time so they’re not working on replacing a track when they could be working on an engine?” asks DiMonte. Another opportunity she delivers is for folks new to an industry and how they might leverage AI to bump up their experience level. “It’s all about better use of people and talent in our workforce,” says DiMonte (which is especially important during labor shortages).
- Differentiate your solutions with data
For DiMonte’s view at Grid Capital, she’s most excited about the collection of data that allows us to make more predictive maintenance decisions. From Padmanabhan’s view at Autonomize AI, he sees a significant opportunity to automate the structuring and normalization of data so it’s less of a bottleneck for customers. But context will remain critical. “It won’t move the needle if you lack context to activate what’s in the data,” says Padmanabhan. Motiwala gave the example of how the word “stock” in finance means something completely different on farms to put not having context into perspective.
As a use case that shows how context supports solutions, Motiwala points to a friend who developed a smart device for stethoscopes (nicknamed “the Shazam of heartbeats”). The AI-powered company has a repository of data with millions of data points that can tell you have a heart murmur, explains Motiwala, “and the doctor who’s tired or probably hungover will probably have a harder time doing that,” he joked.
- Showcase a well-rounded team
The biggest pushback Padmanabhan got for his healthcare and life sciences startup was that he had no background in healthcare. Part of his process was getting industry executives to join his team on a cap table and as angels. They also hired a chief medical officer who was previously the CMO at a major healthcare organization. DiMonte agrees with his approach, emphasizing a well-rounded team. “[As investors] we want to look at why you for this, not just why this,” says DiMonte, adding that it’s particularly imperative in the age of AI when companies can get a product off the ground fairly quickly.
Quickfire tips from our experts:
- Economic opportunity exists to solve problems in big, unsexy industries. (Alliston, Ravin AI)
- Make it easy for investors to find out that you’re the winner. (Padmanabhan, Autonomize AI)
- Tackle a big ocean or market and make it very, very easy for people to adopt. (Motiwala, DeepL)
- Being able to say we can run this better than you would ever be able to internally is a powerful entry point. (DiMonte, Grid Capital)
What’s on the horizon for AI, according to these experts?
At a time when everyone needs to either become profitable or grow profitably, Motiwala is excited about what use cases companies will come up with. “It’s a struggle right now, and so people are getting creative, and AI is enabling companies to augment themselves…and anything can happen in the next few years.”
Alliston doesn’t think we’ll talk about AI as a standalone innovation for long, though. Instead, we’ll talk about its function. For example, take PowerPoint. There won’t be a button that says, “Use AI to do this;” it will just be a button that performs a specific action. “You won’t think of it as Generative AI…You’ll just think about it as a button,” says Alliston.
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