Meet Your New Teammate, AI: Asana’s Saket Srivastava

Stay tuned after today's episode as Shervin and I talk about the changing role of the CIO.

How would project management and collaboration be done in the future? Find out on today's episode.

I'm Saket Srivastava from Asana, and you're listening to me, myself and AI.

Welcome to Me, Myself and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, professor of analytics at Boston College. I'm also the AI and business strategy guest editor at MIT Sloan Management Review.

And I'm Shervin Khodabandeh, senior partner with BCG and one of the leaders of our AI business. Together, MIT Sloan Management Review and BCG have been researching and publishing on AI since 2017, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate. Hi everyone, welcome to season ten of Me, myself and AI. Today, Sam and I are super happy to be joined by Saket Srivastava, Chief Information Officer at Asana.

Saket, welcome to the show. Thank you, Maybe I start by asking you to describe Asana as a company and then your role within that.

absolutely, and nice to be here and great to meet you both. Asana is an enterprise work management platform. We help over 150,000 customers globally. 85% of the Fortune hundred companies manage and automate everything from company level goal setting and tracking, all of that work, execution, capacity planning, product launches, all on our platform. We believe that increasingly work is becoming more cross-functional, and cross-functional work, managing that is hard. Asana works towards bringing greater clarity and accountability on who is gonna do what by when, and then that really helps with greater predictability and better outcomes for the work.

And then your role within that as a chief information officer, I've gotta believe AI plays a significant role in what you do and what Asana does.

Yes, the way I think of my role at Asana, there are really two parts to it. One is I lead the internal technology organization at, uh, Asana, get to work with some very talented people and teams. AI is a big charter of ours. At a company level, we have identified a goal which will move AI and the impact of AI for our workforce. I also spend a ton of time with customers, really looking to learn from customers, be an advocate for our platform, and also bring in the needs and the voice of our customers into our product and go to market strategy as well.

Wonderful. So AI has been around at some scale at over a decade now. But I would imagine, particularly in the last couple of years, with generative AI and all this sort of extra focus and buzz around it, what are you seeing in the marketplace and what is different now versus, let's say, five years ago?

Asana started on AI very early on, I'd say closer to eight, ten years back, and the fundamentals of our platform, the architecture on which our platform's built on, we call it the Work graph data model. And it shows up as what we call a pyramid of clarity, really lends itself well to benefit from AI and generative AI. Obviously, over the last couple of years, in fact, not even two years, there's just been so much conversation and buzz around generative AI.

We felt that with the context that our platform carries around the work that customers manage through our platform, we are really well placed to leverage the gen AI movement and bring some real good wins for our customers. We thought about it from a principles first perspective on how does AI coexist with humans, and how do humans eventually take accountability for the decisions and think of AI as a teammate? If you will, we're starting to see our customers benefit from the AI launches that we are making in service of them.

Well, I'd love to hear some of those examples. What kind of AI initiatives are showing up in your products?

It could, at the most fundamental level, be the tasks that contribute to the projects that contribute to the portfolios and initiatives and goals. And so this just going up and down the organization and across the organization. All of that context is what Asana carries for any customer. So with that context, think of AI as a program manager or a PMO person who's in charge of, say, writing status reports, and AI can automate all of that. Just imagine if you're a program manager spending couple of hours a week on each program, writing those status reports that no one ends up reading.

Perhaps all of that is is now automated, right? And then the AI can generate that for you. And then eventually, the human takes uh, a decision whether they want to modify it or they want to take it. That's just one example. Similarly, because we can track capacity management, we track all the important initiatives around that. Now, AI can also make recommendations on what are the risks that are ahead of us for the most important initiatives that we have.

How are we best placed to resource a particular initiative to help make sure that that initiative is going to be successful? On top of that, we think of AI as AI teammates, which is really about how does AI get integrated into the core workflows of a company? Think of any function and the kind of core workflows that they utilize, and how can AI not just assist, but also take action on behalf of humans in those core workflows.

So those are some of the things that we've done around our product from an AI perspective.

The theme I'm hearing, by which I'm quite enthused, is you're talking about AI as a coworker, as a teammate, as a pseudo person, and you're talking about it. Taking a fair amount of not just predictive work, which is what AI used to do, and it still does quite well, but really cognitive work. And, you know, Sam, contrasting this with, like, you know, how this conversation would have gone two, three years ago, is

We would have gone right down the graphs.

we have a lot of data. It's so much for any human to be able to understand it. We need to predict who will do what, when, et cetera. And I'm not saying those kinds of problems have gone away. I mean, they're quite relevant, and we need to calculate risks and probabilities and propensities and all that kind of stuff, which predictive AI does well. But this notion of AI, not just as a tool to optimize, but as a coworker, as a pseudo entity with which you can have conversations and adapt and get recommendations, and maybe even clarity, as you were talking about, that's actually, I think, is quite refreshing.

And, you know, Sam, we talked about this, I would say, in twenty two, back back with our report back then, where we were just suggesting that organizations should think of AI in terms of the roles it would play, not just what it would automate and how fast. But, you know, maybe AI as an illuminator or as a recommender. And and it's really refreshing to see how generative AI is making that possible, that AI is not just an optimizer, but also a coworker.

That's so true, right? We've got a think tank, we call it Work Innovation Lab. It's a think tank that brings industry and academia together, and academia from Stanford, Harvard, NCIA, the top universities across the globe, and institutions like Anthropic and OpenAI. And through research, through surveys and interviews, we publish multiple reports, a couple that are relevant around this AI space. That really highlight the journey that every customer is sort of navigating at this point. And there's a state of AI report that we launched more recently, which showed that there is a disconnect in how leaders are thinking about AI and where the organization and their people are right.

And increasingly, people like me in in our customers, the CIOs and the IT leaders who've now been tasked to sort of make this journey happen. Take it to a place where companies are starting to truly benefit and see. It's no longer an experiment or no longer a tinkering project.

Well, anecdotally, I could share that in my work, at least over the last sort of ten years, I've seen a gradual evolution of CIO role from running IT services and IT processes to much more a sort of driving the company through innovation, being a partner to the business in terms of that. But I would assume you, maybe you've seen this in also your work and the report that probably, maybe even in the last couple of years, there's been really a an inflection point, even in what CIOs are being asked to do.

With all of this sort of new technology that's becoming so prevalent, and how to control it, how to de-risk it, how to get value from it, what are you seeing?

A lot of my peers would totally agree with that that in the past, maybe ten, fifteen years back, IT and CIOs were maybe more in the back end, right in the back room, doing our own system stuff. But more recently, CIOs certainly are, I feel, more business leaders than technology leaders. Yes, absolutely, there's an important aspect of technology in everything that we do. But because we sit at such an interesting place within any organization, wherein we can see every function and what are their priorities, it's incumbent on us to be able to connect those dots so well.

And so, while in the past we might have been happy in our back office, in some ways, COVID put us into the limelight. We were responsible to make sure that overnight companies were now functioning effectively in a remote setup. And similarly, from this gen AI perspective as well, increasingly, CEOs are looking at CIOs to be driving this strategy. What's the vision? What is our strategy around AI, and how do we sort of go on this path?

And there's no other function than the CIO function to kind of drive this change.

Yeah, Shervin. In our research three years ago, we found that people who organized AI functions underneath the CIO tend to underperform places that organized it at a higher level. We should ask that question again, because I bet what you're saying is that some of that has changed over those years. Now, all this seems like a pressure to do AI things. But one of the things from your state of the IT leader report was that one in four people felt like they were investing in AI too early.

What's behind that? Everything I hear is, oh my gosh, oh my gosh, we got to do much more AI. What's the regret?

I think it might be similar to some of the earlier cycles, wherein everything starts with this hype, and then people don't start seeing the results that they were hoping for. So it comes into that trough of disillusionment for a little bit. But across the board, I think at this stage, a year and a half or almost two years, every CIO that I engage with would agree that there's great potential here. But I think there's more realism into the conversation.

There's less of whether gen AI is real or not, whether it's a fad or whether it's not. We all realize that there's great promise in this. It's how do we go about this? How do we learn from what's happening around us? And then then create our own journey for our own companies to make the most out of it.

Yeah, and I think also part of this, and maybe part of that twenty five that are saying, maybe we went too soon and too fast, is the fact that this journey that you're talking about, Saket, is not just a technology journey, right? I mean, organizations have to change and have to adapt, and roles have to change. And going back to your comment earlier about, you know, AI as a teammate and a coworker, I think that's the big change, right?

Whereas in the past, if AI is going to be able to do risk scoring better, or propensity calculations better, or, you know, personalization of offers and optimization, those kinds of things better, then that just that is super precise, um, prediction or optimization. That basically allows better decision making and does that which humans cannot do, cannot do effectively. Now you're talking about AI and gen AI as a teammate and a coworker, which means I have a new apprentice next to me and I have to work with it.

And if if I work well with it, then my job will improve and the apprentice's job will improve too. Yeah, you know, Sam, this actually reminds me of our work back in 2019, which we talked about the producers of AI and the consumers of AI, right? And so the point back then was, look, part of the reason why I mean, this is five years ago, right? But, like, part of the reason companies aren't getting value is because the production and the consumption are not aligned.

Because, like, people make tools, and then the consumption of it requires a fair amount of process reengineering and training and change, and it doesn't happen. Back then, that consumption wasn't being done on mass, that consumption was by few people in the organization, super users, the inventory management group, or like the pricing team, but it wasn't every employee. And I think what Saket is saying is in today's paradigm, it is actually most employees. They will have some version of AI in their day-to-day life, whether it is to improve their own proficiency and effectiveness, or productivity on their daily activities, or even to come up with new ideas and innovation.

You said that there's a gap between, like, the ambition and reality. I would imagine that's also a cause for inaction, or maybe some level of paralysis as to like, well, what are we gonna do about all this?

and that's where I think leadership has such an important role to play to guide direction and show the path, right? We certainly believe that the future is about people who will succeed, are people who are investing in learning AI as well. You can't just live under a rock and feel that this is something that's just going to pass by. For you to be relevant, you've got to know how this generational transformation and movement around gen AI.

How can this be relevant to the work, work that you do? How can this make you focus on things that are mundane and rote and repetitive that you can have an AI teammate do on your behalf? Whereas you can spend your time being more strategic, more thoughtful, building relationships and guiding AI to do the heavy lifting of the work as well. You can be a platform where you're taking large sets of data and then passing it to LLMs, and it's just giving you general advice.

Or when you think of a platform like Asana, which carries all the organizational context of work, it knows what are your priorities, it knows what are your resources, it knows what's the work and how people interact with each other. And when you have all of that context, the recommendations, obviously, that's coming back, or the actions that AI is going to take on your behalf are going to be a lot more compelling as well.

Shervin, I like the idea you're bringing up that, you know, in 2019, we thought about this consumption production. I think one thing that Saket's talking about is the diversity in the people consuming. You know, this survey was about trying to understand where individual people are. And, you know, if I look back on what we did before, maybe we were too too broad in saying, oh yeah, there's production and consumption, when in fact, there's lots of different types of consumption going on.

And it looks like the work that you're doing, Saket, is getting at where people are and where they need to be, and understanding that that's gosh, different for all sorts of people. Maybe I just switch a little bit here, you know, and go back in my life. I used to work for the Atomic Energy Agency, and we wanted to share information about how people screwed up nuclear reactors so that everybody wouldn't screw them up. That's a long-winded way of saying, you have other CIOs that you're working with.

And, Saket, one of the things I thought was most interesting about your story was how active you were in trying to work with other people and understand how other CIOs are learning, doing things right, doing things wrong. Tell us more about that. How does that work?

Yeah, the CIO community is such a blessing for, I think, every CIO. It's a very tight-knit community. This is where we truly learn. This is where we learn without having to do everything and fail ourselves, right? You learn from others' experiences, whether we're across different industries, different sizes. There's a lot of similarity in the kind of problems and challenges as well, right? It's a community of peers who are always willing to share, because when you share, you learn through that as well.

So whether it's talking about, uh, what are some of the new platforms that people are looking at, what have been their experiences? It's a great way to learn and then bring those learnings into your organization so that your journey is just more impactful. And you're not having to go through the same gotchas and failures that some of the other people have. So I certainly tap into that a ton, hopefully contribute enough for others to benefit from it as well.

But that certainly is a blessing in my opinion.

In some sense, that's, I think, what we think about this show is, you know, we sure not think about, hey, what would everybody like to know? What are some people doing that other people can learn from? And it sounds like your CIO community is doing a lot of that.

Oh, absolutely, and this is one of the things that I personally do a lot. Listen to a lot of podcasts. Because, yes, there's some communities that we have in our own geographies, wherein people actually still meet and talk through those problems. But yeah, listening to podcasts and learning from others is absolutely the way to go. There's just so much richness there.

I wanted to ask you your opinion. What do you think is the reason for the gap you talked about in the early part of the conversation, right? The gap between sort of ambition, aspiration and and reality, like, what's fundamental about that gap?

I think in some ways, it's sort of expected. It's a new technology, not fully understood. There's some nervousness around what would this mean for individuals and people as well. So, while leadership sees this as a strong enabler of growth, there are individuals who might feel that their work might get impacted as well through this. So that's wherein having leadership lean in is just so much more important than letting people just do their own thing. So that's when I feel that having a strategy and a vision and a roadmap set by leadership and bring in the voice of your employees and your functions.

And it can't just be a technology movement, it's a company movement wherein, uh, you can really unleash this power when you're bringing the technology and the business and functions all together and co-creating this roadmap on what's the most impactful thing for the company.

Don't you feel that there is also a double-edged sword here? That is because there is so much hype around generative AI, a lot of it is true, and a lot of it isn't, or that a lot of other steps are taken or or needed to get to that value potential that people might be underestimating. But because of all of this, do you feel like some of the more garden variety use cases and opportunities with predictive AI?

That's been tried and true for for over a decade are also put on hold? Because people are saying, well, let's see, let's just wait, because maybe there's a silver bullet that's gonna come and, like, fix everything.

I don't necessarily endorse with that mindset now. Obviously, there's gonna be some difference in the kind of industry you operate in and the regulation and everything around that, which will dictate your steps or your how much you can lean into generative AI. As I mentioned earlier on, and we'd all agree that we're still in the first innings, I certainly feel that this is not something wherein you can sit on the passenger seat or you can just hope that everything's gonna come into place one day and then we're gonna jump on.

It's an organizational movement in many ways, right? So while I would recommend that you don't straight away jump into the deep end of the pool, you should certainly tread the shallow waters, right?

because the learning curve isn't getting easier, the learning curve

And actually, on top of that, the price could be that you might not be relevant.

Actually, I want to get a little bit of your background. I mean, how did you get interested in this? I know you have a background at GE and IBM and Fujitsu and Square. How did you get interested in all this?

My journey was pretty straightforward. I did my undergrad and postgrad in computer science, started working in technology, started with maybe more services, and then at some point in time pivoted to the enterprise side of IT. One thing that kept disturbing me in my early days was how back-end was IT operating in, where IT was only being called upon when things were broken or not working. To me, it felt we were doing some very important stuff that acknowledgement of our work was certainly not there.

I think you'll all, perhaps it would resonate with you. The only times we were called upon was when there was some shipment that had gone missing, or finance was not able to close their books. Or, um, things around that, right, networks down and stuff like that, crowd strike, as it happened

Yeah, we're, yeah, we're. It's interesting you're saying this in the context. We're recording, right? This in the middle of the the CrowdStrike mess.

exactly. So that gave me a lot of concern, felt that I needed to be closer to the business. And that took me through an MBA program. Not necessarily saying that anyone and everyone needs to do that, but for me, it was certainly important because that gave me a better appreciation for what the business is solving for. How could I, in my role, then connect the dots better across all of those business? Be looked at as a business leader who's able to guide and advise on strategy.

Then you have things that come in your way, especially with generative AI, where the business is really looking at the CIO and the IT leadership to guide the way. There's just so much noise that someone needs to guide through that noise for the rest of the organization.

Saket, we like to end our episodes with a series of rapid-fire questions. So these are intended to be just the first thing that comes to your mind. You can answer quickly, short answers are fine, preferred even. What do you see as the biggest opportunity for AI right now?

to really make it more mainstream, have it become that teammate that we're talking about, be someone that a human can naturally look at as a a teammate and lean on for advice and for action.

What's the biggest misconception that people have about AI?

That's gonna solve our problems. Wait, it's not And then we're going to be drinking beer and

watching the machines work.

watching machines work.

What was the first career you wanted?

Interesting. A doctor I want to be a doctor. I don't know why now, but I would have probably sucked at it. But I thought I wanted to be a doctor, and maybe it was my parents thinking that I wanted to be a doctor.

When do we have too much AI?

I think we've gone past that hype cycle when everything seemed to be. There's a little bit of fatigue in my world of everyone just talking about AI. I think we've gone past it. It's what AI can do in service of humans is what I think where we are at this stage.

What's one thing you wish that AI could do that it can't currently do?

More peace and more balance for humans. It certainly feels in my world, and I live in San Francisco Bay, in the heart of Silicon Valley, that we're all working real hard and doing some great work. Yet it's day after day, just work, work, work. How do we sort of find that balance? And that's the promise of AI. That's the most interesting piece, right? That AI can do things for you. And then, yeah, hopefully you don't just completely, uh, don't do anything, but do things that matter and use AI as a teammate, as an advisor, and make your lives better.

Hey, Shervin, it was pretty interesting talking to Saket. I mean, one thing he kept talking about was the evolving role of the CIO. I'm thinking back on the days of the mainframe printers with green screen computers and overnight reports. This is a very different world for a CIO from thirty, forty years ago, but even a different world from just two or three years ago, with the transition to remote work or whatever. You talk to a lot of CIOs, what are you seeing?

today, what I'm seeing in many companies is leading CIOs are taking a much more forceful and vocal ownership of the technology agenda, and they're doing this in a number of ways. One is with AI and now generative AI, they're becoming the leaders in the organization that helps everyone make sense of this, right? With the proliferation of all the tools and technologies and all that, and all of the safety and cybersecurity and responsible AI concerns that go around that, right?

That's one role we've seen CIOs play. But even thinking beyond that, I think what CIOs are increasingly doing and should be doing is taking the view of evolving technology landscape and helping align that with the corporate vision of the company and bringing all these things together. A role I see a lot of CIOs play is become really almost a fiduciary in sort of figuring out in this soup of technology. What are some of the no regret moves you make now, what do you wait for, and how do you still advance the business agenda without having a hundred different solutions in a hundred different places and a massive amount of tech debt that then down the line they need to bring

together?

Yeah, that seems like a huge problem, because, and I think we see that with the advent of generative too, that everybody is looking to do something, do something quickly, it's changing quickly. And if you're not careful, you get a dozen different standards that evolve over the last two years, and then suddenly you've got dozens of standards out there, and that that's not a standard.

Yeah, that's that's for sure. The other thing that resonated with me was how they're using AI and this notion of, you know, he called it a teammate in the context of the platform. And how AI and generative AI are working to take a fair amount of thinking and cognitive work load away from humans, right? Cause when I think about AI ten years ago, five years ago, even when we wrote our first paper together back in 2019, it was a tool.

It was a tool that would predict better or optimize better, and do things that humans could not do, right? I mean, the argument was billions of data points, all this complexity, all these variables.

Too much for people.

How in the world is a human able to do that? Enter AI can do it. That's still going on, and that's still very valuable. We're now talking about, and that's what Saket was talking about, and we're seeing this theme come up in a lot of our conversations. Is that, look, AI is actually beginning to do that which humans are doing as well, or sometimes better. And that is some things with reasoning, some things with scheduling and organizing, some things with just cognitive functions in terms of writing and summarizing and editing and those kinds of things.

And of course, that's great. It's still a tool, but the profound implications on workforce, if you think about it, like three, four, five years from now, what skills are you gonna need to hire, how many, and for what kind of roles, and how would those roles evolve? I I think that's a profound decision that many companies are beginning to tackle and across all functions, right? Like whether it's customer servicing or marketing or underwriting or whatever. It's, of course, a question of, okay, how can AI help you do stuff better and with more accuracy and more efficiency?

But then if you fast forward three, four, five years from now, there is no future where generative AI is not playing a very significant role in all of those functions. So then who do you hire, how many, in what roles, and how does the nature of work change? Next time, we'll speak with Alessandra Sala, Senior Director of Artificial Intelligence and Data Science at Shutterstock. Please join us.

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