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We cut out all the intros and other small talks from our podcasts but I should begin by thanking Max Yankelevich for his time. Max is the founder, CEO and Chief Architect of WorkFusion and one of the pioneers in applying Artificial Intelligence to enterprise processes. Though I had a very high-level idea of cognitive robots at the beginning of the talk, Max explained everything a knowledge company executive needs to know about automation: the concept, the industry, automation potential for enterprises, pricing, ROI and how enterprises should implement automation solutions. We also had a quick discussion on how this all affects future of work. Below you can find our podcast edited for clarity and brevity.
We started off with the founding story of WorkFusion:
Max: I was part of the research team at MIT CSAIL Lab that was studying Artificial Intelligence and we came up with machine learning technology that could watch people perform knowledge work and mimic that work and over time learn it and become much better than humans. This is sort of like how self-driving cars work.
Then I took a sabbatical from the research and I went out to India, just to travel, and I found there are many firms in India that offer outsourcing services for knowledge processes. They call them Business Process Outsourcers (BPO) and I went to visit them like Wipro and Infosys and Cognizant. I went to visit them and I saw that these were pretty laborious operations. A lot of people working in almost like on sweatshop conditions I would say, working 24/7 doing mortgage processes, back office processing for these companies and all of them were smart people but they were wasting their talents doing this repetitive labor.
And that’s how we came up with the idea to take the research out of MIT and apply it to automating repetitive knowledge labor. So instead of outsourcing to humans across the globe and sort of taking away their humanity if you will, you can outsource it to AI robots. That’s the genesis and we started the company in 2011, so I was in research from 2009 to 2011.
Listen to the podcast or read the full transcript here.

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