The promises of AI are unbounded — with the potential to replace and surpass humans in every aspect. With promise however, comes fear. Several technology leaders plead for regulation, stating that we are unaware of the consequences ahead of us. Elon Musk warns that “with artificial intelligence we are summoning the demon,” and Stephen Hawking states that artificial intelligence “could spell the end of the human race.”

The concept of artificial intelligence is far from new. In fact, the idea dates back to the 1950s with Alan Turing’s “Turing Test.” For decades however, AI has gone in and out of favor, as advancements have spiked our expectations only to disappoint when we realize our optimism has exceeded our capabilities. The current wave of AI however, possesses unique characteristics when compared to past hype waves. The underlying technology which enables AI is now widespread. Drastic increases in the availability of compute power, bandwidth, and storage allow for massive data sets to be processed in a very cost-effective manner. Additionally, the ability to generate, collect, and organize data allows companies to solve problems that they were previously incapable of. Open-source libraries and platforms devoted specifically to AI enable unprecedented collaboration, speeding up the development of algorithms and models.

According the Bill Gates, the next 30 years will yield rapid technological progress. As machines gain the ability to see and move independently, the applications of AI will expand, spurring mass adoption and exponential progress. However, we have yet to reach the inflection point in AI. Speaking with many AI startups in the space, enhancing the workforce, not replacing the workforce remains the current goal. While AI is beginning to supplement many white-collar jobs, complete autonomy of a full range of tasks has yet to be achieved. We are still in the age of silo-ed AI, where computers can accomplish a single task but lack the ability to do a wide range of tasks.

When looking at the AI investment landscape, it is clear that AI is a horizontal application that can no longer be classified as a vertical from an investment perspective. Pure AI startups either focus on infrastructure or “AI-as-a-Service.” Within this field, the large technology incumbents have dominated broad horizontal AI-aaS, which include services such as image recognition and natural language processing APIs. These large companies have access to extensive data sets, which allow them to develop robust models that are best positioned for broad generic use cases.

We expect the majority of startup innovation to occur within the Vertical AI-aaS space — solving specific problems within and industry. Startups that can generate unique data sets will be able to solve problems in areas that large technology incumbents cannot or do not wish to enter.

Given our current technological abilities and the needs of various industries, we believe finance, healthcare, retail, and agriculture will serve as the vanguards of applied AI. These industries are especially compelling given the potential of unanalyzed data to improve business outcomes and the size of the respective markets.

Through our research and conversations with industry thought leaders, we remain bullish on AI and the opportunity for startups to create applied solutions. While we may be far from true AI — where machines are as skillful and flexible as humans, corporations can benefit dramatically from productivity gains demonstrated by data science and improved upon with machine learning solutions.

For this reason, we think the AI wave is here to stay. We believe the recent spike in activity is not another false start and we are actively monitoring the market. We will be publishing subsequent research on the space, covering technology developments and VC funding activity. We welcome comments and feedback, and look forward to discussing the future of AI.