By Bob Johnston
June 6, 2023

AI in the Enterprise – with Scale Venture Partners' Barak Turovsky

Barak Turovsky is Executive in Residence at Scale Venture Partners, a leading Enterprise venture capital firm. Barak spent 10 years at Google as Head of Product and User Experience for Languages AI and the Google Translate teams, focused on applying cutting edge Artificial Intelligence and Machine Learning technologies to deliver experiences across Google Search, Assistant, Cloud, Chrome, Ads and other products.

Prior to joining Google in 2011, Barak was Director of Product in Microsoft’s Mobile Advertising team, Head of Mobile Commerce at PayPal and Chief Technical Officer in an Israeli start up. Most recently, Barak served as Chief Product Officer – responsible for product management and engineering at Trax – a leading provider of Computer Vision AI solutions for the Retail and Commerce industries.

He lived for more than 10 years in Russia, Israel and the US and speaks three languages fluently. Barak earned a Bachelor’s of Law degree from Tel Aviv University and a Master’s of Business Administration from the University of California, Berkeley.

You’ll also see some of his recent work in the podcast links

Think on 'processes, skills, and tools' use cases
Barak's prediction on best enterprise use cases for AI
Productivity isn't necessarily the golden metric
Barak's view on AI ROI

Barak and I cover the following topics:

  • As a society, how are we currently absorbing the AI juggernaut?
  • What are the most promising advancements with AI from the view of Silicon Valley insiders, whether investors or corporates?
  • Why language matters
  • What are enterprise AI use cases? Practical and pragmatic use cases that you can embrace
  • Why ‘processes, skills and tools’ will be the three of the main focal points for use cases
  • Language – AI mapping and mirroring the language and knowledge level of an enterprise customer
  • Risks with AI in the enterprise such as: privacy, security, bias in data, efficacy of models, and ethics
  • How to navigate use cases for your industry and why AI in Customer Service is likely the place for you to start (hint: Productivity isn’t necessarily the measurement stick)
  • Good use cases of AI in Education (we’ve all been reading about the bad ones…)
  • AI as “co-pilot” in your company’s workflows
  • ChatGPT 4 and sensing human emotions
  • The competitive advantage to AI when every enterprise has access to it
  • Software development use cases will be BIG
  • How does a VC, PE or corporate investor team cut through the noise and identify the best investment opportunities?
  • What Barak is seeing that isn’t yet covered in the media or industry press

Barak’s recent work on AI:

Cool investment thesis resource:

Y Combinator Investment Thesis Map for AI (Note: once again, “Productivity” hardly a big theme)