Investing in AI and Machine Learning

Julianne Brands – May 2018

Is this the time to invest in artificial intelligence?  With interest in the sector rising, venture capital is flowing into AI startups. At this workshop for our investors and portfolio entrepreneurs, we discussed the technology, its near-term applications and use cases, and where potential investment opportunities await.  

Expert Panelists:  

Geoff Harris, Flying Fish Venture Partners

Preeti Rathi, Ignition Venture Partners

Edd Wilder-James, Google Tensorflow

Takeaways for Investors:

In artificial intelligence & machine learning, look for companies with…

-         Access to unique, abundant data to learn from, with feedback loops for incorporating and processing new data & creating real end user value (otherwise it’s just more data!).

-         Solve one problem for one vertical - Platform technology enabling AI/ML is evolving so fast that technology & IP are seldom a sustainable differentiator for startups. IP might help with downside protection, but won’t create upside value.

-         Create ROI on the bottom AND top line – it’s not enough to increase efficiency through automation.  Fundable startups must also generate value & drive revenue for customers.

-         Target use cases conducive to data network effects and can create a differentiated & sustainable moat with proprietary data – e.g., applications where more data creates stronger models, leading to a winner-take-all opportunity.

Avoid companies that…

-         Target risk-averse industries with lagging technology adoption, like healthcare and utilities, where failure & down time are unacceptable.

-         Compete with established platforms like Facebook, Apple, Amazon, Netflix, Google, and Microsoft.  Instead lever these established tools & platforms to create user friendly, easier to use products, solving real problems for customers.

-         Try to boil the ocean – a ‘general purpose’ AI platform is not feasible…yet.