Keynote for the 2020 Licensing Executives Society event, "Licensing in the Age of AI." By Vinay Iyengar (Bessemer Venture Partners).

1. Implementing AI in the Age of COVID19
Vinay Iyengar
Investor, Bessemer Venture Partners
Licensing Executives Society, May 2020
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2. 2
A Recent History of AI

3. 3
Moore’s Law +
The Hype is Real
Data
Source: http://pointsandfigures.com/2015/04/18/moores-law/ and
https://www.promptcloud.com/blog/want-to-ensure-business-growth-via-big-data-augment-enterprise-data-with-web-data/

4. 4
APIs++ = ?
The Hype is Real
Cloud
Source: http://ecsnamagazine.arrow.com/solving-the-mysteries-of-cloud-computing/ and
https://www.programmableweb.com/news/research-shows-interest-providing-apis-still-high/research/2018/02/23

5. 5
Machines Beat Humans!
Source: https://www.entrepreneur.com/article/283990 and http://www.businessinsider.com/microsoft-beats-humans-at-speech-recognition-2016-10

6. 6
What was significant about 2019/2020?

7. 7
Private funding growing rapidly
Source: Venture Scanner

8. Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
China emerges as a global leader in AI
Source: Venture Scanner

9. 9
AI is infiltrating every field
Source: Shivon Zilis, Bloomberg Beta

10. 10
Yet we’re in the midst of a global crisis…
Source: NBC News

11. 11
Opportunity Abounds!
COVID19 presents new opportunities to apply
AI in healthcare (diagnostics, telemedicine, etc.)
Teams are increasingly distributed + remote ->
enterprise productivity/collaboration-related
software
AI leads to labor cost-savings

12. The “6 Laws” for
Implementing AI
12 Source: http://fortune.com/2016/09/21/startup-unicorn-exits/

13. 1. Have a data moat
• Algorithms that learn from proprietary, actionable, and growing datasets
• Only 0.5% of the world’s data is being used or analyzed1 ➔ massive opportunities
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Helps HR departments manage and analyze
employee feedback
1. Proprietary company feedback data
2. Informs actionable ways to improve
employee and business performance
3. Growing datasets that makes the product
stickier over time!
Source: [1] https://www.emc.com/about/news/press/2012/20121211-01.htm

14. 2. Leverage existing tools
• Basic machine learning is commoditized
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Cloud-based image and video management
platform for developers
• Takes advantage of Google, Amazon, Imagga
APIs for auto-tagging
• Adds a higher value layer on top of existing tools

15. 3. Do one thing and do it well
• Focus on a specific vertical or problem ➔ avoid the giants!
‒ Agriculture, manufacturing, niche functions of the enterprise (e.g. HR)
• Allows you to follow laws #1 and #2 effectively
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Using computer vision to help farmers better
monitor crops
• Focuses on a niche vertical and problem
• Building a proprietary dataset around crop
images
• Builds off existing tools from tech giants

16. 4. Enablement > Replacement
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Automating away low-hanging tickets for
customer service reps
• Fits into existing workflow for an agent
• Allows them to focus on higher-value work
Remove Friction Predictive Insights Full Automation
Transportation Cruise Control Tesla Autopilot L5 Self-Driving Car
Call Center Auto-Dialer Real-Time Call Guidance Virtual Agent

17. 5. Clear ROI and value-based pricing
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• Have very clear messaging around the benefits for the end user, data to support
an ROI – labor/cost savings or performance optimization
• Pricing that is derived from this ROI metric and directly tied to value for customer
– leaves room for expansion!
Cloud cost optimization software
• Alters specific cloud parameters to
boost infrastructure performance,
often up to 2x
• Take a 10-30% cut of savings provided
to customer

18. 6. Domain expertise matters
• The race for AI talent is more
intense than ever
‒ AI PhD salaries $300-500k
‒ Uber and FB poaching entire
research departments
• What we look for:
‒ Technical founding team
AND/OR
‒ Deep expertise in area of
application
18 Source: CB Insights

19. The laws for building AI systems…
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Have a data
moat
Leverage existing
tools
Do one thing
and do it well
Enablement
>
Replacement
Clear ROI / value-
based pricing
Expertise
matters
1 2 3 4 5 6

20. ... but laws are meant to be broken
Some of our best historic investments have been our most controversial!
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And we’ve missed a lot of BIG winners… check out our anti-portfolio!

21. 21
What’s ahead?

22. 22
Explainability/model monitoring
• AI should no longer be a black box –
understanding why + when to trust
• Monitoring models and pipelines the way we
monitor software
Privacy-preserving AI
• Tailwinds from GDPR, CCPA, and major data
breaches
• Various approaches including federated learning,
differential privacy, homomorphic encryption, etc.
Source: https://www.datanami.com/2018/05/30/opening-up-black-boxes-with-explainable-ai/ and https://blog.openmined.org/upgrade-to-federated-learning-in-10-lines/

23. Thank you!
Follow me on Twitter @VinIyengar
vinayiyengar.com
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