State of AI in 2020
I was recently asked to give a keynote on “Licensing in the Age of AI” for the Licensing Executives Society (LES). Doing so gave me the opportunity to brush up a presentation I made a couple years ago about the state of early-stage AI investing. It’s an area I continue to be excited about and the updated slides are embedded below.
What have been some major changes in the world of AI in the past 2 years?
- Private funding continues to grow at an unprecedented pace as AI penetrates nearly every field. The line is starting to blur between cloud software and AI – all companies now are taking their data stored in the cloud and applying a layer of intelligence (slide 9).
- We’re continuing to see large amounts of capital flowing towards AI companies. On average, these rounds appear to be getting larger, which mirrors a broader trend in the venture ecosystem of larger private raises and companies staying private longer (slide 7)
- Many of these large financings are for Chinese companies, and as many experts have noted, China is increasingly a world leader in AI, from commercial financing to patent patent filing to peer-reviewed publications. At all stages of development – research, IP and commercialization – China is no doubt a mover and shaker (slide 8).
What key opportunities has the COVID19 pandemic unlocked? (slide 10/11)
- At a high level, there are more opportunities for automation as companies look to cut costs and stay competitive.
- As teams become more distributed and need to maintain social distance, we will look to robots or computer vision-enabled systems to fulfill important human-facing tasks.
- As eCommerce adoption accelerates, we will require a wide swath of warehouse and logistics automation tools.
- As healthcare moves to a telemedicine-first model, AI-based diagnostics/triage/support will become more widely adopted.
Updates to my “6 Laws”
The one notable change is that “Voice is the new UI” has been replaced by “Clear ROI and value-based pricing” (slide 17). While the proliferation of voice assistants has been significant, there have been very few meaningful applications or use cases, as I discussed previously. The one change I am seeing is that companies are increasingly attempting to prove a clear ROI for their end customers and tying pricing to value. A great example of this is Redwood City-based Opsani which offers cloud infrastructure cost optimization software. By charging their customers only a percentage of the cost savings their software offers, Opsani clearly ties cost and value, making adoption a no-brainer. Cloud cost optimization is a category I continue to be intrigued by as development teams move to a new paradigm of CI/CD/CO (continuous integration, delivery, AND optimization) on multi-cloud architecture.
Overall, as AI has gone from scientific novelty to a core part of the enterprise software stack, buyers rightfully care less about fancy buzzwords and cool tech and more about actual business ROI.