Moving from academia to tech: How easy is it?
Devavrat Shah manages to be prominent in both the academic and the corporate world. The Andrew (1956) and Erna Viterbi professor of artificial intelligence and decisions, he is also co-founder and CEO of Ikigai Labs, a company that is focused on the intersection between generative AI and enterprise data.
He says that there are many similarities between how a professor with a research group operates and how a founder or CEO of a small company works.
“If you have to build your research group, you also have to raise funds to explain to the world why it is important…why what you’re doing is actually important, and not just because you enjoy it,” he says.
Shah likens the part of an academic gig that includes making sure your colleagues and funders see the work of you and your mentees as important to selling. And selling is something Shah has been good at. Ikigai Labs isn’t his first venture – he also founded a company called Celect, an AI tool focused on online shopping which he eventually sold to Nike in 2019. Why did he make the move from a purely academic work life to one littered with startups and business development?
“I was on sabbatical at Stanford, ended up spending time as a consultant at Netflix, and realised that actually, I could do something useful,” Shah says. “And then through that, I realized that real world problems are really, really, really hard. And so if one wants to address them in proper earnest, actually, you have to get out of your lovely, beautiful, cozy, academic environment and do something real.”
While Shah has tenure, some PhD graduates find themselves gravitating towards the technology and IT sector right after school. Rodgers Jeffrey Leo John is the co-founder of no-code AI platform DataChat, as well as the firm’s CTO. He says he also felt the pull to translate his academic work into something tangible. It was an impulse he felt from the start of his doctoral work at the University of Wisconsin-Madison.
“When I started off with machine learning, there were all these interesting technologies that are being developed in the lab, but there was this huge gap between what was there in terms of academic papers and what was out there that people could actually use,” he says.
John believes that, at their core, academia and industry are both about solving problems. One thing he says academic folks looking to jump into an industry job need to be aware of is the differences in motivations between the two workforces.
“Something which I had to get used to is working with a much more diverse set of people, and especially when you’re working in a PhD, everyone kind of has the same goal,” he says. “They want to do research, they want to publish papers and work on some cool technical topics… But when you translate trance transfer to industry, like you have people with diverse backgrounds, you’re trying to work with people in, you know, who have more business understanding, and less of a technical understanding.”
Another difference, according to Fabricio Inocêncio, the head of education and AI at firm Digibee and a former academic sector leader across Brazil, is the pace.
“The problem is, [academics] don’t know that now they have pressure, now they have a limited time to do the things, now they have limited resources. Now the people are going to say, ‘Hey, what’s going wrong?’ Because in academia, the pressure is low pace, it’s a different pace.”
How to Make the Switch
So, how do you make the jump from an academic worker to an industry one? Shah says that one of the key steps is to understand your ego.
“They, individually, are at the top of their small hills,” he says. “People who understand that and have enough humility to realise that there are challenges in the world that are way bigger and more important than just your small hill, [and that] you do have certain perspective and something to offer in that bigger world, is something what I would say so quintessentially defines who are the people who would be able to both make the transition and enjoy it,”
From there, experts who spoke to ITPro for this story agreed that it was about showing your skills in a way that industry can understand, interpret, and implement. For John, one skill gleaned from extensive time spent in academia that he sees translate well into an industry IT environment is the ability to take a look at the broader landscape of a problem.
“One thing that, at least from my experience, the world of academics has taught me is to look at problems differently. And a classic example is [when] working with someone who even [is] a masters student, who knows their coding stuff, they have some industry experience, they see something wrong in the software. And they look at that symptom. And their first instinct is to go and address that symptom. But to me, I need to know if it is just a symptom of a different problem that needs to be addressed.”
“One thing that, at least from my experience, the world of academics has taught me is to look at problems differently. And a classic example is [when] working with someone who even [is] a master’s student, who knows their coding stuff, they have some industry experience, they see something wrong in the software. And they look at that symptom. And their first instinct is to go and address that symptom. But to me, I need to know if it is just a symptom of a different problem that needs to be addressed.”
Inocêncio adds that he finds academics can be incredibly valuable to IT workplaces because of the way they are trained to think.
“With all the data scientists that I’m hiring for the AI team, I value when they have a Master’s or PhD…because I know that they’re going to apply the scientific approach easily. Sometimes this is hard for even some IT professionals to understand. We are dealing with innovation, we are dealing with uncertainty, and we need to validate, and sometimes they [non academics] say, ‘Hey, I know how this works. So let’s assume this.’ And when they assume there’s a risk.”
But he has a second reason why he likes to hire academics.
“While you’re in academia, if you are working with research [it’s] because you want to discover things, you want to understand and shed some light on the darkness of ignorance. So, if you are in the frontier of innovation, this is what we’re doing in Digibee related to AI, for example, we do not have all the answers, so we need to play it out.”
How do you show off that you’re a good fit? Inocêncio says that he asks all of his candidates one question, one that is particularly key for academics who may be used to not having to pivot approaches as fast as those who started their careers in industry settings.
“What are you going to do if we need to just shut down everything that we are doing and change the approach?” He explains this sets a baseline for how responsive they are to the short, iterative process of the tech sector, as opposed to the longer discovery cycle in academia.
Regardless of background, however, Shah says that an academic who succeeds in the industry side of IT is someone who understands collaboration.
“Industries become successful not because of individuals. Industries become successful because it’s the elephants that dance together.”
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