Attention all machine learning founders: Why do you need ML for your business?

As most investors will tell you, buzzwords like “AI” and “machine learning” are sprinkled throughout company pitches these days.

In all honesty, while some companies are doing real cutting edge work that has only been enabled by recent advancements in compute and deep learning, others feel compelled to use these terms given the hype.

In fact, their overuse can make it difficult to get to the heart of what the company is doing, why it is different, and what is defensible about their approach.

For these reasons, two questions I often ask founders are (1) why do you need to use AI to solve the problem you’re focused on and (2) why specifically did you select the approach you’re using?”

When founders have clear, compelling answers to these two questions, not only does it provide clarity on the value being created, but also gives me confidence that the founders have assessed their options.

They are not over complicating the problem by using fancy techniques, and that they have identified a real opportunity to improve processes or enable new ones.

Machine learning is a technology that will transform industries. This is reflected in the flood of investment dollars into companies using this technology.

According to PitchBook via Axios, in 2016 there were 322 deals worth a total of $3.6 billion in investment into AI and machine learning companies. However, these statistics and categorizations miss the important distinction that machine learning is not a solution in and of itself, but an important enabler to optimize a desired outcome.

It will transform industries by streamlining decision making, reducing costs, and improving user experiences.

As a founder I would focus my pitch on what problem I am solving by building my company, instead of on the technology. I would talk about how I am doing that and how my approach is technically differentiated from my competitors as necessary.

This focus helps investors better understand what is unique about my company because they can understand what the use cases are and what value I provide.

For example, Venmo would never say they are a mobile company — they would say they are a social payments application enabled by mobile. This concept also applies here.