Episode 759 02.22.22
Nick McQuire, director of enterprise AI and innovation, Microsoft, joins Peggy to talk about what led to the creation of the AI Business School and the importance of helping leaders succeed with artificial intelligence. The duo also delve in the three initial core pillars and a new learning path in the AI Business School.
Below is an excerpt from the interview. To listen to the conversation from the Peggy Smedley Show, click here or go to https://peggysmedleyshow.com to access the entire show.
Peggy Smedley: I’m excited to have you here because AI (artificial intelligence) is such an important advancement today. And I think there’s so many things we could talk about. Before I really get into all the things we could talk about, I know I had this intro about you, but tell us about your role right now, because I think so many things are happening and what you do is leading to so many exciting things that Microsoft is engaging in right now.
Nick McQuire: Yeah. It is really an interesting and exciting time without question. So, our team, we’re a very unique team actually at Microsoft in some senses. We focus entirely on thought leadership around the complementary fields of AI and innovation. What that means is in the context of our customers, both AI and innovation, they’re coming together in many respects, but they’re ultimately really important priorities now across the globe. AI has become a lot more operationalized in many companies over the past 18 months. We’re starting to see more firms, not only think strategically about AI, but more importantly, how you operationalize innovation more broadly as well.
So really our job is to share learnings both from within Microsoft, within our research organization, but also with many customers out there as well is to help companies succeed in both domains. A big part of what we do as well is to help the business community better understand and leverage the really fascinating work and fantastic work that Microsoft Research is doing at the moment around many fields of innovation from advanced technology science through to several important fields of AI. It’s a really fun team that we’re in. It’s a really fun job. But also, it’s a really significant area where we’re starting to see our customers gravitate to as well.
Smedley: And to hear you talk, I can hear the excitement in your voice because I think there’s so much going on and I guess I want to talk more about what led to the development now of this new AI Business School…I think it’s so needed in industry.
McQuire: Yeah. You’re absolutely right, Peggy…. I think the AI Business School, maybe I’m a little bit biased here, but coming into Microsoft historically as a technology analyst, looking across the world around best practices for AI, I always felt the AI Business School was such a superb set of resources for enterprises. Microsoft designed this going back to 2019 and it continues to expand, but it was designed entirely around helping business leaders succeed with AI. Back in 2019, we launched the school and the learning environment with basically three core pillars. We looked at strategy for AI, how do you cultivate a culture, and, ultimately, how do you do it responsibly? And we did this as well through six different specific learning paths for industries as well, because what we’ve observed is whilst there’s a lot of commonalities, many customers actually want to better understand how you apply it to specific industries that they operate in as well. So, I think since that period of time, so we’re now looking at what three years, we’ve had over 2 million executives explore the program online. And as I say, we continue to expand the content. So, we’re now focusing, not only just in terms of how you kind of scale AI in many of these areas, but we’re also looking at the innovation process as well. Probably one good example it, that I think brings a lot of this to life is one of our customers, State Farm, a really good partner of ours very much got in early with AI Business School, used the content to develop their AI practice, but also fundamentally built their governance model around AI, which is a really important thing for companies now as well. So, we’ve just seen such a range of different organizations embracing the program.
Smedley: It’s interesting to hear you talk, Nick, because when we talk about AI and strategy, and you’re now talking about the different industries, it’s interesting to hear you talk about an organization like State Farm and governance, because we’re all looking at, how do we apply AI in different ways? Is it knowledge? Is it expertise? I guess we’ve gone through, like we’re in our third year of getting past COVID and how do we apply this knowledge, this information. So, is there a real need for it right now? Is it because we have to be better, faster? You talk about two million executives. To me, it sounds like the business, the executives are the one. We innovate and we get better, and we look at sustainability and all these things happening in our world. Executives are the one that have to apply AI in an entirely different way. So, it seems to me the need for it is stronger and more powerful than ever before.
McQuire: You’re absolutely right. The focus of AI Business School from its inception has been to focus on the executive community. And what we see now is there continues to be a real thirst for best practice around AI that ultimately dates back a large number of years, three, four, five years ago now. If you think about it in the context of before COVID, we felt that there was a lot of interest from customers on, how can they understand about moving beyond this kind of experimentation phase with AI, what we used to call pilot purgatory. How do you shift AI models from experiment into production? How do you get experience with running applications based on AI in the real world, and ultimately use this as a platform to become part of your digital transformation, strategies, and efforts?
Then came the pandemic and the world changed. What we found there was that companies just couldn’t wait for some of these longer-term projects to yield results. So, what we saw during the pandemic, particularly in the first early kind of year was much more of a focus on how you create rapid value from the projects and equally, how do you scale it beyond just, say, one or two specific projects and getting it out to a wider set of stakeholders inside the organization?
Now, fast forward to today, and as I said earlier, there’s still a real thirst out there because execs need to consider AI from many different angles now. I mean from strategy, like I highlighted earlier, to results, but now also in terms of risk, and this is what you highlighted as well and compliance, right? We’ve got new regulation coming across the board in many geographies across the world. So, discussions are now evolving slightly, and this is where the AI Business School is really playing a role, from how you create value to how you create value with AI in a responsible and ethical way. And we’ve seen significant traction now with governments, for example, all over the world. We’re running workshops in places like Kuwait, Qatar, and Egypt who are obviously rightly conscious of the role that AI is playing to help them recover and accelerate their recovery. But they’re also looking at it much more from how do you do it in a much more responsible way.
So, ultimately what we’re seeing is a lot of the thirst for information from the executive community coming into AI Business School is beyond really the technology itself. It’s really about getting to the heart of how you apply responsible innovation to the core of your business operation and processes. And these are really the kind of trends that we’re seeing from the executive community around the school now.
Smedley: I really love the way you’re talking about this, because this idea of pilot purgatory, we all understand that. I think every manufacturer that’s hearing you talk feels that and represents that, and they understand. You talk about how the pandemic changes. It changed everybody, every industry. And this idea of rapid value, scaling, the things what you just said resonates so well with me, because we look at results and risk and compliance and value. It’s all right now, leading to that responsible innovation. So that leads me to ask you, how can it help leaders be an innovative organization? And you said, it’s not about technology. So, now we have to understand what does that mean? And I think it has to start at the top and you just said, leaders need to understand it. It goes back to what we thought about years ago when the top executive management team really needs to understand. And that’s what it seems to me you’re driving at. And that Microsoft is now leading the charge with AI to say, look, you have to be an innovative organization to drive change in a very responsible way. What does that actually mean?
McQuire: Yeah. And it’s a great point. Just this week, we’re launching a new learning path in the AI Business School that focuses exactly on this question. We’re calling this Becoming an Innovative Organization and it really is designed to help business leaders ultimately create a platform for innovation in their companies. As I’ve alluded to, and you’re connecting this as well, is we’ve observed that actually through our experiences with AI and obviously many of the learnings of our customers as well, that actually the learnings and the success factors for AI also can apply to innovation more widely within an organization as well, particularly when it comes to getting over some of the big blockers that we’ve seen in the past around AI, such as getting senior executives on board, how do you show value? These are points you made. How do you create a culture that supports every employee? How do you overcome difficult processes within your organization as well? At the heart of it is that, at Microsoft, we believe that every organization has the capacity to foster innovation, and it doesn’t exist in a vacuum, meaning that it can come from anywhere in the organization. So, what we wanted to do was build on our heritage with the AI Business School and share a little bit more of what we’ve learned on the process and the topic of innovation itself. Now, the learnings come in kind of three important areas as well. I can break these down for you. I mean, they’re really, really important in terms of the context and the trends that we’re seeing. The first is how you organize for innovation, what we’re calling organizing for adaptability. And here we look at, how do you set a company-wide vision? How do you set the right practices in place within the organization to help foster innovation more widely? The second area looks at culture. So how do you cultivate an innovation mindset? (That) is what we’re calling it. And this looks at ways in which you can establish a culture of collaboration, which really supports innovation. Now that collaboration piece is absolutely crucial. We have one customer, a partner of ours, WPP, for instance, they’re training an astonishing 50,000 people in AI at the moment. The big drive for them, to accelerate what they call a culture of creative collaboration inside WPP. That culture is a real drive for innovation, but it’s also an element, as I alluded to, when it comes to AI. And then I think-
Smedley: May I interrupt? I’m sorry. I didn’t mean to be rude.
McQuire: Yeah, of course.
Smedley: What does WPP do?
McQuire: Yeah. They’re a big global media company with many different agencies as part of their umbrella. They’re very information rich, very information intensive organization as well. But this goes back a couple of years where they were just getting going with AI and obviously used a lot of the tools and the frameworks we have within AI Business School to help them get moving fast. I think the other aspect as well, when we think about culture is actually the inner workings of Microsoft as well. So, we actually, as part our new learning path, we also shed light on some of the internal cultural elements inside Microsoft that can help leaders understand a little bit more about how this can work. I’ve recently been interviewing the Microsoft Viva team. They’re the product team that are responsible for Microsoft Viva, which is our employee experience platform, which is part of Microsoft 365 and part of the team’s capability as well. What’s interesting about that product is the level of collaboration that existed within Microsoft to get that product from idea through to product, through a lifecycle. And in there, they’ve got some very complex innovation as well, where they’re bringing in some of our largest natural language models in there. The combination of the complexity of the innovation with the collaboration that spans a number of different groups within Microsoft, Research, Bing. The Bing team, for example, as well is quite remarkable. So, what we do there is we kind of shed light a little bit upon how the one Microsoft approach works to drive this culture of collaboration. And the final piece in the learning path that we’re looking at here around innovation is what we call co-innovation as well. So, what we’re saying is that successful organizations need to think beyond just the four walls of the organization. Think about how you work with external partners, how you work with customers, how do you bring in institutions and ultimately the communities that you serve as well to address some of the big societal and industry challenges that many companies are facing as well. It’s these three areas, culture, the organization, and the co-innovation piece that are really the core aspects of what we’re looking at now, when it comes to sharing some of our learnings in AI Business School around innovation.
Smedley: Help me understand then, because the way you just described it, it then can be any vertical, any segment. And it really sounds exciting … because you started out the conversation telling me that there’s two million execs that have already gone through or experienced the AI Business School. So, this implies to me then that any vertical can really take advantage of this. Are there verticals that stand out to benefit from this one more than the other, or it really doesn’t matter? Because as you talk about co-innovation or organization, or any of these, that culture that you described, the sky’s the limit.
McQuire: Yeah. Great question. We think a lot about this. Of course, we’re hoping that the content will be valuable for any business leader regardless of sector, but we do recognize that this may look different in different industries, but we do think the components are going to be the same. So, what’s interesting though, is that we do see a level of prioritization around innovation, pre and post pandemic, that is slightly nuanced by sector. So, for example, we see healthcare and retail industry customers, for example, who were hit quite hard, obviously by COVID. We’re starting to see them prioritize innovation more today, comparative to where they were prioritizing it, say back in 2019. I think collectively more aggressively perhaps than, say, other industry verticals at this moment of time.
And actually one of the stories that we look at inside our AI Business School and this new innovation learning path is a really interesting one from UCB, which is the global pharmaceutical giant, longstanding organization. In there, it’s done a lot of innovation around drug discovery and delivering new drugs and testing during the pandemic. But actually what’s fascinating, I talked to you a little bit about the co-innovation piece earlier, their story, during the pandemic is ultimately about co-innovation. They’ve set up a Moonshot project, what they’re calling an open science consortium, which is very much dedicated to creating new antiviral drugs for COVID-19. But the level of collaboration and co-innovation that UCB is fostering with its partners, public sector, private sector, large and small organizations is really inspiring. We think this is a great set of learnings, yes, for those in the healthcare industry, but for all industries as well, given the focus that they’re having in that arena.
Smedley: When I hear you talk, Nick, what comes to mind to me right now, when you talk about co-innovation and organization and culture, that it now implies to me that we see this blockchain, these smaller organizations, like you just said, the open science drugs, those vertical markets that can communicate and collaborate and innovate. It seems like we’re going to see more of this becoming more tightly, interchanged and connected in ways as a result of, and I don’t know that people are thinking it, but my mind is going to innovation that we’re going to see those communities come together and being able to develop new things in a sense of collaboration because of AI. Is that where Microsoft is seeing it? Because I think Microsoft leads the charge when it comes to innovation. You do things first. Is any of that a part of this, or am I just thinking way outside the box?
McQuire: No, I think you’re getting to the heart of it. There’s kind of two ways to look at that. The first is, I think the sea change in how companies think of innovation today. And the second piece is specific to Microsoft in terms of how we think about innovation internally. If we think about the first piece first, I think it’s really important to say like, we really do see a distinction between historically what was invention, so the focus on the idea, to innovation, which is very much the focus on how you scale the idea. That distinction is really important because I think historically, a number of, maybe say, two or three decades ago, what we’re seeing is that invention and innovation historically could have happened in a vacuum, whereas it does not happen in a vacuum anymore. So, we’re kind of moving away from this thought that innovation or invention happens in this old-school type of inventor type of genius that comes up with this great idea, think of like Doc (Emmett) Brown in Back to the Future, for example, to today, which is much more of a collaboration approach, like much more collaboration of understanding of how it should work and how it can work. So, it’s that process of collaboration internally within the organization across different groups, but also externally that I think is very different to how we thought of innovation or indeed invention, say, a number of decades ago. And I think that’s why you’re starting to see a lot of these aspects and these case studies like UCB, for example, that are very much in that co-innovation space. And that’s an area that we’re just starting to explore from a learning perspective. We’re going to go deeper on that in the future for companies, because we’re getting a lot of questions and a lot of pull into that arena considering as well that through COVID there was so much collaboration happening at industry level. There are a lot of consortiums formed. There’s a lot of public sector in academia-based collaboration with private sector as well. We do think that’s obviously going to continue.
Smedley: And then in Microsoft and how does Microsoft innovate? How does it teach other companies the way it’s learned to innovate internally itself?
McQuire: Yeah. This is a really big topic. Maybe it’s probably good to break it down just a little bit, because it’s really interesting.
Smedley: It’s big, right? It’s super large.
McQuire: It’s super large, but in fairness, we’re getting a lot of requests from companies to better understand some our processes and how we approach it. It kind of breaks down in two core domains. It’s kind of how we think about innovation and then how do we structurally approach it within the company. So, how we think about it really spans what we call three core anchors, and you’ve heard Satya talk a lot about this in the past. So those three anchors are first that innovation, it has to be meaningful. So, it has to be available for customers to innovate on top of. I may have mentioned to this earlier, but breakthrough innovations in the future we think will come from companies and industries, not just the technology providers. So, that innovation has to be for companies as well. The second area is that it has to be applicable, obviously. It has to be put into action and made real for companies so it doesn’t exist in this vacuum as I highlighted earlier. And then the third piece is about responsibility. It’s about the innovation that earns trust. So, it’s not just about what the technology can do to support innovation, but asking the question, what it should do as well. So, these three anchors more or less drive how we think about innovation, and they ultimately manifest themselves structurally within Microsoft in three key ways. And I could break those down for you real quick, but they’re super important.
The first is that Microsoft, in terms of our approach, we take a full spectrum approach, meaning that we invest our research, we invest our projects and our time across both visionary areas, maybe longer-term areas, as well as practical, more short-term areas. And that spectrum is very balanced across both long-term and short-term horizons. So, it won’t be a surprise, for example, that we apply the McKinsey Horizon framework (McKinsey Three Horizons of Growth), and we operate a balance of projects across Horizon 1, 2, and 3. For those of you who aren’t familiar with the McKinsey Horizon framework, it’s very much about risk, but it’s also very much about certainty of market opportunity. And it’s very important for companies to have innovation projects that combine those types of horizons within their organization.
(At) Microsoft, it’s really important though, we say is that it’s also important that these horizons don’t exist in isolation. You ultimately want to have projects and technologies and research areas that span all the areas. So, our large-scale natural language models in Microsoft, which I highlighted earlier, what we call AI at Scale that exist in Microsoft Research, they’re a prime example of this. In the long term, they’re probably going to become platforms for companies to innovate upon. But in the short term, we see them in our products. We see them in Bing, we see them in Azure, we see them in Office, et cetera. So that horizon model is really, really important.
The second piece is around our platform. We take a platform approach to innovation and that comes back to the processes to enable everyone in the company to participate as well as the external process as well, which I highlighted. And then the last piece is around the architecture for innovation. So that means that our leaders are very focused on guiding a very structured incubation program for the types of innovation projects that we’re focusing on. And we’ve got a number of these different projects in Microsoft. I can go into a huge detail on them, but really the bottom line is that we see that those three areas in terms of our approach really factoring in, and ultimately our core philosophies factor around them being meaningful, responsible, and applicable as well.
Smedley: You just described these three things. It’s really exciting to have you drill down. Is there more that you think is worthwhile sharing with our audience? Because I loved hearing how Microsoft thinks, because I think it’s that innovation that drives companies forward. So, they can mimic or see how they can replicate what they do. Maybe not at the scale of Microsoft, but everybody learns and says, well, if Microsoft’s doing it, maybe we could do it because it’s not them telling us. It’s they’re doing it themselves.
McQuire: Yeah. I think where we can double-click, I’m sure, because we get lots of questions on, is some examples. And obviously we have the ability, we go into detail into a number of these different areas within our new learning path in AI Business Schools. So absolutely, please check those out in detail. But some examples, we think about perhaps the structural approach to innovation and innovation as a platform, for example, where we bring external parties into the mix. The work we’re doing under Project Origin, which is an internal project term name, but it’s a public name outside of Microsoft as well, where we’re aligning with some of the world’s major media companies, the BBC, the Canadian Broadcasting Corp., in Canada, New York Times. Collectively, we’re trying to tackle disinformation and the rise of deepfakes, for example. I think that’s a really good approach for how you bring co-innovation into the mix, but also how you take that platform approach to innovation.
The other example that is way above my pay grade, but ultimately really a fascinating area because it’s involved in some really deep areas of science, but it’s a great example of some of the kind of careful incubation and what we call innovation architecture approach that we take towards innovation. Project Premonition is a Microsoft Research project that for the past five years, the teams within Research have been seeking to recreate the biome and they’ve built a cloud and AI-connected lab environment where they can monitor in fine grain detail and collect a ton of data around mosquito behavior. And this is ultimately to get to a place where they can predict better the spread of pathogens.
That project itself, again, way above what I’m capable of understanding in terms of my scientific background, but what’s fascinating there for our discussion is the level of careful incubation that we’ve taken for that project since the beginning. So, collaborating with a number of external, as well as our internal research teams and external parties, as well as the levels of investments that have gone into it. I think it shows the importance of that architectural approach as well. So, we have the ability to go a little bit more deeper into the AI Business School. So absolutely encourage you to check those out.
Smedley: Nick, it’s really exciting. We just have a couple minutes left and I know I can’t end a conversation without talking about societal or organizational resilience right now. We have to think about that. It’s so important today and how do we apply technology or AI or whatever we’re talking about. Can we wrap this up with your views on what we need to be thinking about?
McQuire: Yeah, sure. Obviously, a huge topic, the challenges of the pandemic have really brought to light the issues that we’re facing. I think what’s different though, within organizations that we’re talking to now is that we’re starting to see a slightly different approach to research and innovation, right? Meaning that I think organizations are rethinking, not only the systems and expertise they need to react to crises that have arisen as a result of COVID, but also I think the thought is how do we emerge stronger from them as well? And that’s what the core of what our discussions around societal resilience kind of play to. And actually technology, to your question, is playing a really important role. If you look at even just coming back to AI, I mean, the progression of AI over the past 12 to 18 months has been pretty remarkable and that’s come in the light of the pandemic, right? The way in which companies were able to, not only react and respond, but also transform their companies through having to move fast around deploying AI, whether it was in the contact center, whether it was in the supply chain, whether it was detecting fraud, for example, these are some of the areas where we’ve seen AI really add value. And I think what that has done is it has built a foundation for many of these companies now, as we move into this next phase of really success for them. And so coming back to this point on driving more resilience into companies to not only just survive, but to thrive, we’re starting to see technology really play that important role. That’s the core of why we believe that societal resilience is such an important theme and why at Microsoft, we’re really talking about it and we’re really having deep and helpful conversations with our customers as well around it.
For more information on the Microsoft AI Business School go to http://aka.ms/AAfv1m2. Or you can just check more information online as well at the Microsoft AI Business School.