Ep 37: Empowering Your Enterprise Through Generative AI with Asana CIO Saket Srivastava

Saam: Hi there, and welcome to Enterprise Software Innovators, a show where top tech executives share how they innovate at scale. In each episode, enterprise CIOs share how they've applied exciting new technologies, and what they've learned along the way. I'm Saam Motamedi, a general partner at Greylock Partners.

 Evan: And I'm Evan Reiser, the CEO and founder of Abnormal Security.

Today on the show, we’re bringing you a conversation with Saket Srivastava, CIO of Asana. Asana is a leader in project management platforms, allowing teams to stay organized, communicate effectively, and achieve their project goals efficiently. Asana has more than 130,000 customers in over 200 countries across the globe.

In this conversation, Saket reflects on the dynamic role of AI in business, strategic considerations informing technology adoption, and how enterprises can best embrace the digital frontier.

So again, first of all, thank you so much for joining us today. As Saam mentioned, we've been really looking forward to this episode. Maybe to start, do you mind giving our audience a little bit of a background on kind of your career and how you ended up, you know, where you are today? 

Saket: Sure. First off, uh, thanks for having me. Looking forward to this conversation.

So when I grew up in India, in New Delhi, the capital of India, I did my undergrad and post grad in computer science. Worked for a few years in India and then moved to Netherlands for a bit and came to the U. S. and I've been in U. S. now for 20 plus years. And I've dabbled my career between consulting and I.T. leadership kind of roles. And through that experience, I've been fortunate enough to have had experiences across companies at different phases of their growth and across multiple industries as well. 

The last few companies that I've been at, um, I was at Guidewire Software, which is an enterprise software company for, uh, an insurance property and casualty vertical, and I was leading, um, their IT teams there. After that, I went to a FinTech company, Square slash now called Block, and I was leading all of their technology data teams. I was. playing the role of a CIO there. And over the last almost two years now, I have, I am with Asana, again, an enterprise software company leading enterprise collaborative work management platform.

Evan: And I'm sure most people working in technology are familiar with Asana, if not actual customers and daily users, but maybe for those in our audience that are not familiar with Asana, do you mind sharing a little bit about what you guys do and how you work with customers? 

Saket: Yeah, absolutely, so it, it operates in a space called collaborative work management, it's all about enabling teams to work more effortlessly, uh, and achieve their goals more efficiently.

So it's a platform which is used by over 140, 000 customers. And essentially it does a few things, right? As a CIO, as a practitioner, I can say that it's, it's a platform that helps creating better accountability and achieve greater velocity of work, when increasingly work is becoming more and more cross functional.

Rarely do you find yourself doing work which just sits within your teams and within your functions. And anytime work sort of crosses over to other functions and teams, it becomes harder. To be in control of the outcome of that work, right? And that's where in a platform like Asana comes in, wherein it helps sort of create that accountability and better predictability for work.

And that's very important and meaningful to us as CIOs who are responsible for running larger cross functional programs. So that's one. The other thing that Asana does particularly well is anytime there's a body of work, understanding as leaders, we need to understand what's the work that's contributing towards moving my company forward.

And similarly for people who do actually doing the work, it's equally motivating for them to know how their work ladders up and is contributing to the company goals, right? So Asana as a platform helps making those connections, top to bottom and bottom, top and across. So that's essentially what Asana does.

Evan: You know, so you, you've been at the company for nearly two years. You know, we're at a pretty exciting time. I'm sure you guys are perpetuating an exciting time, right? Just, it's a notable company, but also the technology and how people are working, you know, has changed a lot in the last two years. Like, what do you find to be the most exciting part about being Sayo today?

Saket: Oh, I say this and I think a lot of my peers say this, uh, this is perhaps the best time to be the CIO, uh, of a company. I say that primarily because in the past, our function used to be a little bit more on the backend, right? We would be the technologists who would be told, go do this and we'd go and and implement those technologies and be very happy being in our world, right?

But increasingly as CIOs, our work is more about being a business leader, being that business strategist, being that business architect who's able to connect the dots across the company. And it's important that we're able to sort of drive conversations and drive strategy for the company. 

There's no other function that works so cross functionally across and sees everything that's happening across a marketing, sales, security, product, HR, finance, right? It's us. So it's incumbent on us to, to make those connections and drive directions for the company. So that's, that's one part of what makes the CIO role exciting. 

Obviously we had this sort of unfortunate journey through COVID where we had all kind of take our workforces, make them remote and that, uh, Brought us to the forefront as well as leaders who were able to make that pivot happen overnight.

Right. We didn't necessarily know going into this, that this was something that we could do well, but, uh, across the board, I can confidently say that all CIOs were able to make that flip. Right. And, um, no conversation over the last year is ever complete without talking about Gen AI. And I'm sure we're going to talk a lot more about Gen AI as well.

But, uh, as CIOs, I see the CEOs looking at the CIOs and asking them to drive direction for their companies, leveraging, uh, all things Gen AI. 

Saam: As you mentioned, it's hard to be talking about technology right now and not, not focusing a large part of the conversation on AI given the breakthroughs we've seen over the last, uh, four to six quarters.

What are your thoughts on where we are in the overall AI hype cycle? And how do you at Asana approach thoughtful AI adoption? 

Saket: It's interesting how much Gen AI gets discussed, and it sort of gets discussed as if it's a very new thing, wherein our company and several other companies have been working on all things AI for a long time.

I think the pivotal moment last, or 20, 22 November, when OpenAI came up with this, uh, chat GPT 3, 3. 5, when it became a lot easier for everyone to engage with AI, right? No longer did you necessarily need to be a data scientist to leverage the power of Gen AI, right?

I believe it's still early on. And more broadly, I do feel that It does feel like Gen AI might be overhyped in the shorter term, but I also feel that in the longer term also it might be a little underhyped because truly I don't know if everyone understands or anyone understands the possibilities with Gen AI.

We're still sort of scratching the surface. While it's taken a whole lot of air time and it might feel that we've been talking about this and this is prime time, I think this is still the preview that we're seeing. Still early days. Uh, and then when it's so fascinating, even in this early days, just imagine if you just fast forward a few years out, the kind of great possibilities that we can unlock with Gen AI.

Evan: I know that, you know, Asana has been a leader in AI in different ways, right? But a lot of those ways are you know, hidden or maybe somewhat invisible right to the outside. Do you mind sharing a couple examples about how Asana is using AI that maybe, you know, most people from the outside would not expect?

Saket: When I look at Asana and the foundational data model that Asana has built around, we call, we internally call that the work graph data model.

It's really. sets us up for greater success to tap into this gen AI growth. Uh, what this really means is, um, around atomicity of the unit of work. We've talked about what Asana does around as a, as a work management platform, but when You have to kind of have multiple teams work on a unit of work, invariably, you'll see that you duplicate that body of work. You'd copy it and make multiple copies of that and stuff. What Asana does well is Asana helps you retain that atomicity of work, which means that the data fidelity and data quality that you get on the, on the work that your organization is managing on a platform like Asana, um, you'll get better results from Gen AI as well, right?

So I think that's the foundation. That aside, the way I think we think of Asana and Gen AI, I categorize this in two ways. One is we often hear this phrase co pilot.

This is something that can help you in your day to day, increase your productivity and efficiency and Asana does that beautifully well as well. If you've got your, all your work being managed on a platform like Asana, you can use Asana, ask Asana anything. It can summarize for you. It can create smart answers for you.

It can, it can help you with all of that. But that's just one part of it, right? Besides that, we also think of Asana as sort of an air traffic controller, which goes beyond your sort of personal productivity and individual productivity. Now when an organization's work being managed on Asana, and this is more game changing.

This is where Asana is now able to leverage Gen AI and be able to recommend to you, what are your SMART goals for the company? Because we know what's the work and what are the people working on within Asana, we can recommend what are your goals for the company that you should be thinking of, or we can be doing SMART planning for you, or we can help you resource plan better.

Right? We can, we can take a look at the skill set and the capability of people and the kind of work that they've been doing. And maybe we can make recommendations around that for you. So more broader than individual productivity, we can now talk about organizational productivity as well. 

There's one more thing that, uh, that Asana sort of uniquely sort of equipped to do well, we've got a think tank that we, we call it work innovation lab. So in partnership with academia, And our product, we are able to tell our customers, give them a collaborative score. Let's call it, we call it collaborative intelligence. And we give them opportunities and ideas and recommendations. Hey, this is how you're performing in collaboration, say on accountability or velocity and stuff.

And this is how you compare against your benchmark companies and industries. And these are some recommendations on how you can do better at that. And that's compelling stuff as a CIO. When I talk to other CIOs about how they can think on and leverage a capability like this, invariably the reaction is their eyes are popped open.

Evan: It seems like most, you know, CIOs we talk to when we ask about how is AI being applied, they kind of bifurcate the world in terms of how are we using AI to improve our product, our service, our offering to customers. Their half is like, how are we using AI internally to improve how we operate and run the business?

Do you mind sharing kind of any examples of, you know, novel, unique ways where you've seen improvement or impact and kind of how you run the business by using some of these technologies, whether things you've built in house or even from other enterprise software partners. 

Saket: So we've talked a little bit about how Asana as a product is leveraging Gen AI and kind of going deep and giving value to our customers. Internally, we're sort of doing similarly, wherein I'm trying to understand me and my teams are trying to understand what our vendors, the partners that we engage with, what are they doing around Gen AI, right? Having a perspective around that. 

Secondly, as CIOs, it's important for us to Enable our workforce and prepare our workforce to understand the nuances around Gen AI and be prepared to leverage this, right? As a company, we have decided that we're going to be an AI first company. What that means is that an average worker, every asana should be able to leverage the power of Gen AI from capabilities that we're rolling out within our product and everything that's around us as well.

So we obviously at the start, we rolled out policy and some guidance and some enablement for our people. But then beyond that, we started to think about internal enablement through two vectors as well. One was identifying some lofty not star opportunities. And, and go after those. And I'll talk about a couple of those specifics that we're pursuing at this point in time.

And beyond that, also looking at some tactical incremental capabilities that we might need to build or we might need to buy as well. And for that, we did some surveys and identified some opportunities that our people were telling us, hey, this is, these are things that would help us in a, in a few ways. 

One was this notion again around a co pilot for our go to market teams. For our sales teams and our customer experience teams who, who need to do a ton of research around our prospects and customers who need to be better informed around, around our customers and how they leverage our products before going into a conversation with the customer.

There's a ton of that research and Gen AI is perfect to kind of do that on their behalf. So, so Gen AI could create a cheat sheet for them. Hey, this is what you need to know, going into a conversation or research enough about a lead and then create a few options of messaging that the account executive can then go and evaluate and then make a decision around. Right. 

We also, as a company, started with some first principles around, uh, gen AI. We felt, we believe, and we've say that AI is in the service of humans. So, so the accountability should still sit with the human. So these use cases that I'm talking about around talking about around gen AI, AI would do the work, but at the end of the day, the human should take accountability and make decisions around that.

AI can be that sort of muscle and the human can be that brain and that heart. That's sort of the way I think about this. So that's one use case. The second customer support is a classic use case. Even before all of this gen AI, right? Uh, IT support and customer support. Uh, there was a ton of AI already being leveraged around chatbots and stuff, right? I believe that up to 40, 50 percent of that interaction can be deflected or auto resolve without before hitting a human, right? If you're able to do that, just imagine the amount of money that you're able to save and you're able to redirect that, that investment elsewhere.

The third is around as companies grow, your knowledge and content gets so distributed and fragmented. How can we sort of layer in and, and, and make that search and answering two questions easier for people where they no longer need to know that they don't necessarily need to have years of tenure within the company. And only then they know where the knowledge resides. They can just sort of search and they can, their questions get answered. 

A lot of our salespeople reach out to our R& D organizations when they have questions around a product and there's a ton of content already out there.

And so we've got a Slack channel wherein these account execs and customer facing teams can ask questions around, uh, around a product to our R& D teams. One off questions are fine, but then what ends up happening is this breaks their deep work, the R& D team's deep work. And This is where Gen AI can be hugely beneficial, wherein we have a use case where what we're doing now within Slack, instead of asking someone directly in R& D, you ask a bot and this bot can research against all of the sources that we have and give that answer.

And, and, and there's valuable time that you're now saving on the R& D team who can then go build great product for our customers. 

So great, great opportunities that exist today. 

Evan: Is there any particular projects, right? That had like a surprising impact, right? Where you, you kind of deployed some, one of these new technologies and was able to augment or automate or improve kind of how the business is working today. She's looking for some sort of anecdote where, you know, listeners could be like, Oh, interesting.

Like we should try doing that as well. Right. Anything that would, anything where you've kind of seen good results. 

Saket: So one, one area that I am spending a lot of time on is. How do we increase our go to market teams productivity, efficiency, uh, effectiveness in the conversations, right? And, uh, we started again, not not saying that Gen AI is going to solve this problem, but we started with understanding their day in a life off or that customer's journey from start to end. And doing that sort of experience exercise, discovery exercise, we were able to sort of identify opportunities along that workflow, that journey, where, where automation could be helpful or where, uh, Gen AI, I could be helpful, right? 

So while this, again, this journey is not complete. We're already seeing benefits of that exercise now where we were able to baseline that this is our rep productivity today, in terms of the time that they lose because of navigating systems and processes, or even a dollar that's assigned to a rep to close for the year, right? That's rep productivity in some ways, right? 

How can automation And how can Gen AI along that workflow be able to improve that quota for a rep or be able to save time so that the reps able to kind of talk, be more in front of the customer as well. So, so those are, those are the ways we're thinking about some of these use cases.

Saam: What are some of the things that you think will be possible three years from now, five years from now with AI that if we knew about today, we would say, hey, it is really underhyped that let's say the average person listening to this podcast may not be thinking about.

Saket: That's a hard one, though, right? Thinking three, five years out, it almost feels like in the past you would have said decades out. That's the pace of change and innovation that we're seeing with uh, specifically with Gen AI.

I do feel, though, that the way I and I've seen others use Gen AI is more on invoking Gen AI to be a co pilot and be able to help. Right? As opposed, so, so in a, in a Uh, pull sort of manner. I need something and I'm going to invoke Gen AI. Changing that experience to more of a proactive sort of push versus pull might be a good way to kind of think about the progress of Gen AI, wherein it's context aware and it's It's, it's proactively making recommendations to you as opposed to you having to, can you summarize this for me or can you do X for me or Y for me, uh, that might be good sort of progress.

That's sort of more broad getting those specifics. I'm sure there are examples that I can't think of, but, uh, uh, that there are ones out there as well. 

Saam: One thing I want to touch on as it relates to building these AI products is kind of the question arournd build versus buy, and even, you know, if you, or partner, right? And even if you think about build in AI, it's moving so quickly, even the form factors of build seem to be evolving, right? There's, there's build in the terms of going to one of the major vendors like OpenAI or Anthropic and building on their AI stack. There's build in terms of Rolling one's own infrastructure and leveraging open source models. And, you know, when we talk to different people, I think there are different schools of thoughts on the pros and cons of, of each of these approaches. And then there's of course, just buying or, or partnering and consuming kind of end to end products.

And so, you know, if you think about an example, like the sales co pilot you were describing earlier, right? What's your philosophy around build versus partner for these AI products? 

Saket: I think it's use case by use case, um, and, and it also depends on the kind of company and the industry and the industry you serve, right?

If you're more regulated, I think you've got more restrictions. At Asana, I do believe that we leverage open AI and Anthropic, the, the, the, the variety out there, right? We're not necessarily restricting ourselves to one. We also don't believe that we should be creating our own foundational models. 

Um, there was some report that I read from Gartner that by 2028 X, and this was a high percentage of companies that are creating their own sort of foundational models will perish, right? It's going to get better with the larger ones as well, right? So that's all around the foundational models. I, we don't want to create our own. We want to leverage what's out there now, more specifically around partners or building those use cases, I think that's use case by use case. 

I want to stay close to what my vendor partners are doing. I want to make sure that, uh, we tap into their innovation as well, right? So what a Salesforce or a Workday or an Oracle and the likes are doing, I want to make sure that our people understand that and tap into that.

But I also don't want to be it. waiting for them to just create a path for us. I want us to be exploring and experimenting. So the sales use copilot that we're talking about, uh, this certainly something that we've decided to go build ourselves, right? So leverage, um, uh, one of the, um, LLMs out there and, uh, build these use cases, these GPTs more specifically for Asana's use case. 

Evan: Can you share a little bit more about kind of how you kind of learn new things, um, you know, with. Do with generally like how people work changing, I. T. architecture changing out of the security landscape, changing with a new A. I. technology every week. And how do you stay up to date on the latest technologies and how do you kind of evaluate what is what's got substance and what is, you know, smoke and mirrors?

Saket: It's very, very important that as leaders, we are not fully consumed with our initiatives and priorities that we've signed up to deliver for our business teams. Very important to go deliver them, but it's important that you have the right team and the right priorities and the right scope and the right understanding of how those would get delivered and when.

But it's important that you're creating capacity for yourself to understand what's happening around you, which, which might come in the shape of, uh, networking with your peers, spending some time with the VCs community, right? But that's primarily the way that you stay close to the innovation that's happening and then building a point of view.

Important to build a point of view around what's working, what's going to work, what's not going to work. What are the problems X is solving and where there's just all smoke and no substance. 

Evan: So again, we'd like to, um, end our episodes with a bit of a lightning round, right? And we're looking for kind of the shorter, almost like one tweet answers.

Um, so I know we got, we don't have a lot of time left, so we'll have to go through, we'll only have time for like four or five of these, but Saam, do you want to kick it off for us? 

Saam: Absolutely. So maybe to start, how do you think companies should measure the success of a CIO? 

Saket: Business value, business outcome, uh, how are the CIOs, uh, impacting the strategic outcomes of the company?

Evan: What's one piece of advice you wish someone told you when you first became a CIO? 

Saket: Take on harder challenges, be bold, be a business leader first, and then a technologist. 

Saam: How should CIOs position themselves to best collaborate with the rest of the C suite? 

Saket: Oh, you're not, you need a short answer, right? I was going to go on my, uh, 

Evan: We'll, we'll, we'll give this one to, you get two tweets worth or maybe 280 characters.

Saket: 280 characters. Uh, understand the business of the business and be a partner who has a point of view, build credibility, um, and have a seat at the table, not just a fly on the wall, but have a seat at the table where you're influencing outcomes. 

Evan: So maybe switching gears more to the personal side. Is there a book you've read that's had a big influence on you?

And if so, love to hear which one and why. 

Saket: There's one that I read recently. Um, it's by this gentleman, Patrick Lencioni. Um, he's, he's written a couple of books. The earlier one was, uh, five dysfunctions of our teams when he talks about, and as leaders, it's important that we lean in on our teams, right? It's through the teams that we'll, we'll achieve success for our organizations.

So it talks about how, or what are the factors that can help you make teams more successful or, or, or less successful. But the more recent one, uh, was around, um, uh, again, teams, the book name was ideal team player. It talked about some qualities around, uh, humility around being sharp and, and, and it also talked about being hungry for success.

And it talked about Needing all three of this for an individual and a team to be successful as opposed to just being hungry and not being smart or not being humble, having all three ingredients. Um, uh, take a look. I think, I think you'd, you'd, you'd enjoy the read. 

Saam: Maybe sticking on the personal side.

What's an upcoming new technology, and it doesn't have to be related to AI, that you're personally most excited about? 

Saket: I dream of a world where, um, the robotics and Gen AI comes together. I'm sure you've sort of been close to the Boston Dynamics kind of robotics, right? Almost human like. robots here. And then you sort of combine Gen AI magic to that, and these could be your assistants, right? You, you're, they can, something as small as, can you check if there are eggs in our refrigerator? If not, then go, go to the grocery store, get it or order and get it, right? So much beyond a virtual co pilot, uh, and real life, uh, assistant or a co pilot. 

Evan: What do you think will be true about technology's future impact on the world that most people would consider to be science fiction today?

Saket: Interesting. Maybe, um, intergalactic travel. Uh, we're already talking about travel to Mars. Uh, but, but beyond that, uh, who knows? 

Evan: What about like the kind of 10 year timeframe? Like, you know, technology, I think if we look back on our last 10 years, technology affects us in 2024 in ways, you know, we, we would have totally, we couldn't have dreamed about, you know, 10 years ago. And without a doubt, we're on this exponential curve of technol, technological advancement.

I'm sure if all three of us wrote down our predictions about, you know, what the world's going to be like. We're going to underestimate a bunch of things. What do you think we're going to underestimate about, you know, the technology, the world we live in, in 2034? 

Saket: With all the advancement of technology, our lives continue to be very busy.

And, uh, a whole lot of our lives are consumed by the work that we do, right? Being able to truly have a, better work life balance. Because of what technology can do better and more of, is perhaps what I see in the future. Perhaps not the answer that you were expecting, but I think that would be a good dream world for me, wherein people are living more fulfilling lives, more holistic and complete lives, than just doing the work.

Evan: Thanks so much for taking time to join us today. Uh, great to speak with you and hopefully get a chance to chat again soon. 

Saam: Thanks a lot for joining us. 

Saket: Thank you for having me. I'd have had fun through this conversation.

Evan: That was Saket Srivastava, CIO of Asana.

‍Saam: Thanks for listening to the Enterprise Software Innovators podcast. I’m Saam Motamedi, a general partner at Greylock Partners.

‍Evan: And I’m Evan Reiser, the CEO and founder of Abnormal Security. Please be sure to subscribe, so you never miss an episode. You can find more great lessons from technology leaders and other enterprise software experts at enterprisesoftware.blog.

‍Saam: This show is produced by Luke Reiser and Josh Meer.

See you next time!