Ron Glozman of Chisel on what you don’t know about AI and ferociously focusing on the top 5

Ron Glozman is the Founder and CEO of Chisel, an AI driven tool for data aggregation, extraction and concision that uses proprietary algorithms to extract important information from documents in seconds that would otherwise take hours to compile. Ron is a graduate of the NEXT36 business accelerator program and is an emerging authority on Artificial Intelligence who has been featured in AI and Economics publications including the highly regarded recent book, The Economics of Artificial Intelligence.

Looking back five years, where did you think you’d be by this point in your career? How do you think you got here?

I’ve always known two things about my career. The first is that I wanted to go into Computer Science and the second is that I wanted to work for myself. Since I was young, I had the support of my parents to take a break from my education in order to go try and get a startup off the ground; that was a big thing. While admittedly I’m still early along my career path, I wouldn’t have started Chisel if it wasn’t for those few things in my life.

What gave you the big idea to start Chisel and how are you going about building the company?

I founded Chisel about three years ago when I was at the University of Waterloo. It all started because while I enjoyed the program that I was taking (Computer Science and Business), I enjoyed playing video games much more than studying and hated the amount of time I had to spend reading textbooks. To save myself time from school, I had the idea of trying to teach a computer how to read and summarize my textbooks because, as all students know, reading textbooks takes up a lot of unnecessary time that could be spent doing more enjoyable things. That program, once it was finished, went across the globe to 44 schools in 33 countries in a matter of two weeks; I knew I had something there. The problem was that students don’t have a lot of discretionary income, so building a business around that wasn’t the most viable option. That was the point where we pivoted to trying to serve governments in their effort of extracting key information from documents to serve their national security efforts, but dealing with the government also turned out to be a tough nut to crack so we needed to find a new customer.

A year and a half ago, we pivoted again. Now, we provide software that is powered by Natural Language Processing to large insurance brokers and carriers to help them read and automate paperwork to reduce risk. We realized that out of the 250 million knowledge workers around the world who need to do things like read information and process it to do their work, the insurance community would be one of the best areas that we could provide real value to. For the next few years, we want to be an AI leader in the Insurance space but over the long term, we have our sights set on the Mortgage and Financial Services world as well.

What is the biggest misconception out there when it comes to AI?

People think that AI is something that is completely revolutionary, but AI has actually been around for a long time. The biggest advancements have been because of advances in computing power and how cheap that computing power has become. The Algorithms themselves aren’t necessarily that proprietary anymore. The differentiator in AI is the data that you have to feed your Algorithms with.

How do you see AI changing the way that businesses operate?

Having worked with some very smart economists who are doing groundbreaking work in this area, the narrative around how AI is going to change our world falls in terms of judgment and decision making. A computer is much better at reading, extracting and summarizing information than a human is. Having said that, computers are not very good at making informed and smart decisions in context. What AI does, is help people arrive at a decision point faster because they don’t need to spend the time reading and summarizing all of the information that they had to before. That being said, a lot of knowledge worker jobs that are centered on that kind of work will cease to exist, which is quite a large number of jobs. The good news is that new jobs are going to be created that we haven’t seen before and ideally, reskilling will take place whereby people who used to hold those old jobs will be able to move into taking the new jobs. For example, Data Scientist as a profession didn’t exist ten years ago, but now it is one of the most in-demand professions out there.

What are some of the most important business lessons that you’ve had to learn the hard way so far and how have they made you more successful?

The biggest learning for me has been learning the transition from being the lead on everything to being the leader of the company. When I started, I was the lead developer, the lead sales and marketing person and the lead finance person. Now, I don’t code very much and my role is about building the business and sales. That has been a big shift. I am no longer a direct contributor, I spend most of my time in strategy meetings whether those are internal meetings or customer meetings. It is hard to appreciate what a big change that has been and there is more to learn every day.

So what does being a great leader mean to you?

Leadership is very context dependent and comes in many forms. Steve Jobs and Satya Nadella are two very different leaders, but they are both considered to be great leaders in their own right. It really depends on the situation and what you are trying to accomplish.

For me, my goal is to be more strategic and goal focused as opposed to being task oriented. There are many roads that lead to Rome and thus you need to be flexible in your approach. Leadership to me is about inspiring people to bring their best self to their work and to harness their innate passion to go the extra mile.

What is the one piece of advice you would give someone in the workforce today to get ahead and find work that is fulfilling?

Speaking quite practically, I would advise everyone to sit down and write out the top 25 goals that you’d like to accomplish for your career over the next five years. These goals can be anything but they need to be personally important and highly motivating. Once you’ve done that, cross out numbers 6-25 and forget about putting time and energy into those things until you’ve achieved numbers 1-5. If you do this exercise right, the top five goals will be the only ones that you will focus on over that five year period because they should be big enough to keep you focused on achieving them. The top five should also be the most important to you and achieving those should do more to make you feel fulfilled than numbers 6-25. Prioritize and focus your efforts. I can’t take the credit for that exercise though, I learned it from listening to Warren Buffet.

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Aubrey Chapnick