How the Covid-19 Pandemic is Requiring Companies to Establish AI Skills Rapidly

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0:57okay who's gonna start this The age of AI is really defined by the emergence of a different kind of company, which is kind of a big deal because that doesn't happen in business very often. Traditionally, we've built companies around individual units and silos. So you have a silo around marketing, you have a silo around product development, you have a silo around manufacturing, because the silos are necessary to optimize how people work. But as more and more of the company is made up of digital technology, then gradually what happens is the companies need to be built differently. Modern organizations are really built around a data-centric architecture that integrates the data across as many different parts of the firm as you can and then efficiently deploys technology based on that data to power as many different processes as it can reach.

1:54So can I just put something in here? What I can say is like the age of AI is not some distant thing that's going to happen. The future is happening now. It is happening to us today. Even actually at this moment, if you're watching us on a website, you're watching us on your mobile phone, this has been enabled by companies that are squarely innovating in the age of AI. And the challenge for the rest of us who are not in organizations that are AI-centric, that are AI-first, is how do we adapt? How do we change so that we can also be competitive with both the giants, but also the newly emerging firms that are trying to make a difference?

2:31We thought we had time. We thought lots of industries had time to make the adjustment. Of course, now that is no longer the choice. So the COVID pandemic pretty much changed everything. And all of a sudden, every company had to cope with this. And one of the most amazing things was that companies actually did that. You know, my favorite example of this is actually like your local restaurant. Remember how crappy the websites were for local restaurants? If you wanted to go look at menus or what's on the special today, you'd be like stuck in PDF world on your little browser, on your phone. And overnight, just for sheer survival purposes, all these restaurants became digital.

3:10They started to work with the Uber Eats of the world, the Postmates of the world to make delivery happen. and the whole restaurant experience became overnight, got digitized. And so - You know what, Kareem? You know what? Like the QR codes, all of a sudden they're everywhere in the US. Exactly. Because nobody wants to go into the restaurants and you want to go and figure out what the menu is. So you kind of grab the QR code from the door and there you get to the website. I was like, I was so stunned by the rapidity. And you know, it's like a survival, like it's a survival instinct. And this to us is the big accelerant.

3:45Look, I mean, it's real simple, right? If you walk down the street and you notice that your local Chinese restaurants are using QR codes to point to their menu, your typical multi-billion dollar enterprise should be able to do it as well.

4:01People transformed literally overnight. One classic example is Medestrano Hospital in Boston, which is a 215-year-old institution that overnight in January really re-architected its own operating side to deal with what they were pretty sure was going to be this terrible pandemic and terrible strain on their traditional resources. And so they integrated the data assets that pulled in this large data lake, essentially this infrastructure that would enable you to very quickly create predictive models around how many ventilators they might need, how many N95 masks they might need. All that had to be predicted.

4:45This requires a degree of centralization around the data. You can't have the cardiology unit have its own database away from the nephrology unit, away from the ER department, right? And not only do you want all the data, you want to be able to look across all of these and then make predictions about where capacity is needed, where do you expect patients to come through, and provide this view globally across the enterprise. And this view of data integration, analytics and software as the core is the big shift. It's almost like the pandemic was an accelerator, really, of things that people had wanted to do before and the necessity of the deployment of certain systems that on the fly were re-architecting how the organization actually worked.

5:37Another really cool example that we have featured in the book is a company called Moderna. The big aha for the CEO, Stefan Benzel, around AI and digitization was he had walked into one of his scientists' offices in the early days. And the scientist was basically, you know, doing some complicated set of calculations, moving genes from one side to their side. and he had five screens all around him and was basically copy-pasting stuff from Excel in one cell to the other cell. That he saw as a nightmare because in the biotech world, you have a copy-paste error. That's going to put you back six months, nine months if something by accident got transposed or through some careless mistake.

6:20And he basically freaked out. He said, we can't have these large investments in our technology be driven by manual processes. And so he decided to build Moderna with the digital foundation and invested in digital capabilities across the enterprise from manufacturing to R &D to clinical to HR, you name it. All of those had to be digitized and put together. This transformation actually helped with the COVID pandemic as well because they were able to within 42 days, once the virus was sequenced, to then be able to submit to the FDA a vaccine application. There's still a startup with 1200 employees, right, competing with trying to create a vaccine with large organizations in the pharmaceutical world.

7:11And if you sort of think about the scale of what they've been able to accomplish, it tells you the differences in processes that can be put into place if you have digital data analytics at the core of your operation.