2958: Inside Asana: The Role of AI in Modern Work Management

[00:00:00] What does the future hold for Asana as it navigates the evolving landscape of AI and IT transformation? Well, today I want to delve into Asana's latest research and some of the product announcements to explore the company's strategic direction. And our discussion today

[00:00:20] will focus on my guest, Paige Costello's pivotal role in steering Asana's AI strategy, the shifting responsibilities of IT leaders in an AI era, and the introduction of Asana's groundbreaking AI teammates. And with 77% of IT leaders feeling the weight of leading

[00:00:42] IT transformation and 90% recognising AI's importance for future business challenges, I want to try and uncover how Asana plans to bridge the gap between AI's potential and practical deployment. So today we'll discuss the key insights from Asana's recent research,

[00:01:01] revealing that while 52% of knowledge workers engage with AI weekly, only a third of organisations actually have a strategic AI plan in place. And we'll also explore the challenges and opportunities that IT leaders are facing right now, and how Asana's unique data model aims

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[00:02:52] show. So buckle up and hold on tight as I beam your ears all the way to San Francisco where Paige Costello is waiting to share her insights. I'm Paige Costello. I lead AI at Asana and my focus is around helping our customers achieve

[00:03:09] their missions. So the biggest thing I'm working on is really our AI strategy and making sure that we employ AI in a responsible way that helps customers achieve their goals more efficiently. Asana is an enterprise work management platform used by 80% of the Fortune 100 to

[00:03:27] drive clarity and accountability at scale and maximize the impact of their teams. Cross-functional teams use Asana to achieve their biggest goals and do the things that are typically quite tricky in a large organization. So if you've been to any given meeting or brainstorm, you

[00:03:45] know that you leave it with a ton of next steps and plans and hopes and dreams. But do you actually know who's on point? Who is doing what by when and why? Asana is a work

[00:03:56] management platform that helps connect strategy to execution so that you can do the things that are important and have a lot of dependencies with more confidence and precision. So Asana supports both process management as well as work management, reporting, resource management

[00:04:14] around all of the key use cases that customers experience every day like creative production, campaign management, just building their companies and have wide ranging use cases that are supported by the platform. And it's so interesting to hear you talk that and the transformational impacts

[00:04:35] AI is already having on the workplace. If we look back just a few years, the world of IT has been on such a journey from bring your own devices, shadow IT, software as a service, now AI. And

[00:04:48] one of the reasons I wanted to invite you on the podcast today is I understand that you've had recent research that shows that the role of the IT leader is changing, particularly with the

[00:04:58] rise of AI. So can you tell me more about this? It seems like the department is evolving almost in real time. It is. 77% of IT leaders believe that they are personally responsible for leading the

[00:05:11] IT transformation at their organization. That's a very intense experience for a lot of these people. They experience stress monthly about this because 90% of them believe that AI is critical to navigating future business challenges. So they feel not just responsible, but aware of how

[00:05:31] important it is to changing their business trajectory and achieving their goals. The biggest thing is that they're being consulted on AI more and more. And that's a new role for them where they're in the strategic conversations, they're at the table, they're figuring out what

[00:05:48] the plan is, and then they know it's business critical. And I would imagine it is incredibly daunting, all the eyes in the room on you as that IT leader is told, can you give me an update on

[00:05:59] the AI implementation, please? Because it is not easy. So I'm curious, does your data show any specific challenges that IT professionals are facing or grappling with at the moment? I would say that the main thing is that they're worried about investing too quickly. And they're

[00:06:15] also have typical fear of like budgets and how to think about their budgets. So when we did this research, 25% of IT leaders believe they move too quickly. But the other ones were the groups that

[00:06:30] say they move too quickly. And of course, this is shifting all the time, because what is great and what is available is changing so fast. And so there's some level of concern about moving too

[00:06:41] fast. But there's also a level of concern about like how to allocate and think about budgets for AI investments. So that's one of the big challenges that IT professionals are facing is how to think

[00:06:53] about this across their organization and by department. Because many solutions have kind of a point AI feature set or kind of serve AI capabilities, a lot of the initial wave of IT leaders thinking about AI, there's kind of like pure play chat apps from the labs and model

[00:07:13] companies themselves. And then there are like small integrations of AI in other platforms and tools. And they're trying to think about like, how do our teams achieve their results using AI? Like what is the

[00:07:26] safe and secure and responsible way to deploy AI? And how do we budget for it to make sure that we're getting the ROI that we put in? And alongside that, of course, we've got the business as usual activities, firefighting, those support

[00:07:40] calls, software updates, project works. What is the reality of AI adoption on the ground there? And what kind of impact is it having on teams? Well, I would say that, like, the main thing is that people are using AI and they're using it a lot. We saw a

[00:07:57] huge growth in the number of people using AI weekly in just nine months because we do regular state of AI trend reports with Anthropic. It's worth noting that like the most productivity gains go to the daily users and

[00:08:12] then to the weekly users, and then the monthly users are far behind that. But 52% of knowledge workers use AI weekly. And that's really quite high. Yeah. And there's also there's still a lot of concerns around AI. I saw more of it last year at a lot of tech

[00:08:31] conferences, people were a lot more cautious. But this year seems to be changing. It's more about solving those real world problems now. But I'm curious from what you're seeing, especially in the reports, etc. What's keeping

[00:08:42] people or business leaders from adopting and being successful in their use of AI in the workplace? Well, I think a small part of it is the ad hoc adoption, where most of the like there really aren't consistent

[00:08:57] organizational strategies for how to deploy AI and how to use it. So only 31% of the people, both executives and ICs we surveyed across the UK and the US we surveyed 5000 people, and only 31% of them said there was any strategic plan

[00:09:16] whatsoever about how to deploy AI in their organizations. Only 64% like 64% of people just say they have no to low familiarity with all of AI. So AI literacy itself is a problem. So we've kind of got this, there's no strategy, and

[00:09:35] there's no literacy. And that's really driving a lack of awareness about how to how to use it, how to get the most from it. And then that's where the fear sets in. Because if you don't know what you're doing, you don't know what it's used for, then you

[00:09:50] have this increasing mistrust of AI and the data that it's using and making decisions from data that you can't trust. And so nearly 50% of people are really concerned about AI accuracy. This is the place where people feel the most uncertain. And

[00:10:07] that's the biggest thing driving concern, I would say in enterprises today around adoption of AI. And I've had a few conversations recently, one was with a worker, his IT guy. And he was talking about how he's passionate

[00:10:22] about AI and implementing differences, etc. But the business was flat out, we don't want anything to do with AI. And I coupled that with a very recent large tech conference in the US and I had eight or nine interviews lined up and one of them

[00:10:34] had to cancel because the leadership team said, this bank doesn't want to be associated with anything AI, which I found quite strange. So do you think sometimes there's a disconnect between employees and executives when it comes to AI adoption?

[00:10:49] I absolutely do. We know this from our data, actually. 70% of executives use AI against only 40, around 40% of ICs. But there's a big enthusiasm gap that's represented in that usage number, as well as just how people feel about AI and its

[00:11:08] opportunity for the business. That example you gave makes me think about just this perception externally around brands and brands wanting to be human and accessible and caring to the customers they serve. And I think that's really

[00:11:25] admirable and understandable and important. It's really easy to get lost in like what AI, AI for what? Like what is AI doing for us? And I think the big thing is that AI is intended to help people do what they're trying to do better. It's worth

[00:11:44] nothing. It's a tool for humans. And I think it's fair for an organization to say like, maybe we don't want to be thought leaders on AI, but I'll bet you that they have a plan to implement AI internally to help their employees be more effective. I

[00:12:00] had this conversation recently with a just friend of mine who works at a university and she's a writer. And she said she's using a transcription platform and her productivity as a writer is three acts what it used to be. And she laughed because she said, I'm

[00:12:16] sure I should be worried about my job as a writer. But right now, I'm so grateful that I get to just dive into writing instead of spending that time transcribing my meetings, and listening to old recordings. And I think that speaks to the practicalities of like

[00:12:35] AI really joining the team, and being a tool that you can delegate to and work with. We actually found that when people use AI

[00:12:45] like a teammate instead of a tool, and they think about it in that way, they give it more strategic context, they expect to tell it what it needs to do explicitly. And then they expect to give it feedback. And they see big productivity gains when they use that

[00:13:02] mental model of AI like a teammate instead of a tool. And I think that that's going to be really a change to how people work, and

[00:13:11] really help them get the most out of AI where it stops being a source of fear or like an absence of information and starts to be

[00:13:19] something that they feel like, oh, yes, I specifically asked AI to join this process and do this job for me. And I know I'm pulled in at the right moments to ask the clarifying questions.

[00:13:31] Such a great example. Love that. And I appreciate this is a million dollar question, we could dedicate an entire episode to this question. But what do you think a good AI strategy looks like? And what should companies be doing? Any advice you could offer around that?

[00:13:46] Yeah, I would say a few things. One is I highly recommend just creating a plan for employee education and training that's continuous. It can't be a one off. At Asana we have an AI council. That's a cross functional group of leaders and representatives from all over the business

[00:14:06] who are responsible for thinking about our AI literacy, and the tools that we deploy to increase our impact. And so I would highly recommend

[00:14:16] saying like this is no one group's job. This is a business problem and an opportunity that we get to apply ourselves to. And so one big piece is just

[00:14:30] like creating a group that is responsible for driving both the vendor strategy as well as the employee strategy for setting norms and expectations about how and when to use AI and how to get the most from it. It's important that they, you know, a good strategy also

[00:14:50] prioritizes reliability and safety and has a system for how to quickly evaluate the tools that you might choose to use. Security and legal teams

[00:15:01] are tapped over and over again for AI reviews. So having your perspective on the principles and the norms, like once you have a few tools approved,

[00:15:10] knowing what you're looking for in a vendor is key. And then I would say really having a human centered approach. It's very important, like I said, to find the

[00:15:21] tools that engage your teams in a way that increases your trust in the quality of the results and in how you're pulled in to make decisions. We at Asana firmly

[00:15:34] believe that people are at the steering wheel. They are the drivers, they are decision makers, they are the accountable parties. AI is just there to fulfill

[00:15:44] their requests and engage with them on their terms. And so we've structured it in such a way that for example, you can say do this research and then create an

[00:15:56] approval task before it moves to the next stage or support me in writing the status update with these headers and emphasize it in this way. And here's a status update I wrote

[00:16:07] before, I would like it to sound and look similar to this. That is just really expediting the work you already do with the information that you need. And I'm really excited

[00:16:19] about what that means for all the individuals who spend a lot of time searching for information, sending emails, trying to find what they need in order to just do the work that they were hired to do. So I'm excited

[00:16:32] about reducing the drudgery and increasing the sort of work that is strategic and creative and rewarding because I think we underestimate how much of a knowledge workers day is the stuff that they would love to partner with AI to simplify.

[00:16:49] And I'm so grateful that you've come on here and talked about some of the trends that you're seeing some of the insights from your reports. And one of the big trends I'm seeing all the tech conferences I'm attending at the moment is AI

[00:16:59] integration into new products with various vendors around the world. And I've got to ask Asana, any big product launches there and AI integrations you could talk about?

[00:17:10] In the last few weeks, we have launched something that we have called AI teammates. And the reason we call it AI teammates is because it helps to think about AI like a teammate instead of a tool in terms of delegating work to it very specifically giving it the right context and expecting to iterate together. And so what this is, is effectively, our customers who use Asana for a wide range of use cases can partner with AI in the context of their

[00:17:40] workflows to do work. And that work could be if there's not enough information in this request, please ask the person who created this request to answer these additional questions. It could be doing some research, it could be filing the state of the work in a particular way. So if it sounds like a P0, please send a slack to this person. If you hear about these three customers, please add

[00:18:09] this group to this customer's information set. And so you can think about AI teammates as a highly customizable way for organizations to point AI to support them with their work and their processes. We have also shipped AI chat, which helps people do work, of course. So if you say, please assign subtasks to this team to read this thing in advance of the meeting on

[00:18:39] Friday, it's very effective for supporting that. As well as just like, what's the status of this thing? Or what are the risks to this given project? Or who knows the most about this topic? And it's able to scan the work of the organization, the people in it, the goals in it, and help answer questions and direct people to the right information as well as supporting them and help with the product broadly. And so we're really excited about just continuing to level up

[00:19:09] the embedded support that happens in Asana to help organizations achieve their goals. And of course, everyone's launching AI integration of some sort now. So to everybody listening, how would you say Asana's new features are unique? Or what makes them unique? And how are they helping enterprises?

[00:19:28] The biggest thing I would say that makes it unique is Asana is a collaboration platform that helps people coordinate work. And it always has been about human teams aligning on what work is required when it's needed, and when it got done. And these relationships about like, who's doing what by when and why are the same pieces of information that you would expect and need when working with AI. So the past was all

[00:19:57] about people working with people. The future is going to be people working with people and people working with AI. And you're going to want to know what you've requested, what it did, how it helped, and have transparency and visibility into that. So the inspectability here is really important. And the transparency into the organization understanding what is AI doing for us? How is it working? And what do we want to do next? What is the ROI of that?

[00:20:25] Asana has a unique data model, we call it the work graph data model that has the context of the relationships between people, departments, work goals, and a lot of the like digital exhaust of how work happens. And this data model creates a lot of context that enables a simple request to have a lot more data in order to yield a much more specific and correct result.

[00:20:52] And so when you think about AI, and you think about a prompt or the context you give it, that's work, right? If I don't, that is work. And what is really exciting about this data model is the right context gets passed in terms of what processes this running in. Oh, this is the production process. And here are the five steps, and like 10 branches and ways we work through our product process.

[00:21:19] Now, AI knows how you like to work, what the steps are, and what it's been asked to do, as well as what's important to your organization. And so the investments we're making in AI are really just trying to capitalize on what organizations do intuitively, the way they have their work set up, the way they have articulated their processes.

[00:21:43] And having AI embed quickly with the right context means less work to set up and more reward in terms of it being right, more often, because it's more precisely directed towards a specific use case and has the right knowledge of your organization.

[00:22:00] And something I'm reading more and more about at the moment is the need to move away from AI versus humans or humans versus AI, leave the ego at the door. And it's all about collective intelligence. But why do you think people are so confident that blending human and AI expertise can yield superior results that either could ever even dream of achieving alone? That seems to be the big point, right?

[00:22:25] I think that is the big point. I think, like I said earlier, there's so much mundane work in work. And we remain a group of people who are hungry to do important and impactful work. And I think people rightly see AI as an opportunity to achieve more.

[00:22:48] And each person's capacity can be increased when they know how to use AI. And we have seen that when people use AI like a teammate, they actually report 33% more productivity gains. And so it's not a future state, it's a present state. But the future of work is going to be one where people regularly rely on AI to improve the quality of their delivery.

[00:24:18] And so the way goals connect to execution, the way strategy and execution connect in Asana is going to be something we continue to invest in, as well as what AI can do to help people with reporting and visibility and just driving the impact.

[00:24:35] Right now, we're really focused on how AI supports individuals in their work and their processes and embedding that into the systems of ways where CAPN, AI will continue to support higher levels of abstraction across groups of work, as well as the way people get visibility into that work.

[00:24:55] Well, a lot to look forward to. Sounds like we'll have to get you back on next year, find out how that continues to evolve. And we covered so much in 30 minutes today from how the role of the IT leader is changing. While there's still some concerns around AI, the disconnect between employees and execs when it comes to AI adoption, this move to collective intelligence, blending human and AI expertise, and the new products that you've talked about.

[00:25:19] At the end of the show, I'm going to add two links, well, three links to the reports that we referenced, the research there, as well as everything to do with the recent product announcements. But more than anything, just thank you for joining me today, Paige, and sharing your insights. Thank you.

[00:25:33] My pleasure, Neil.

[00:25:36] So as we wrap up our deep dive into Asana's AI journey, I think it's clear that the company is not just keeping pace with technological advancements, but helping actively shaping the future of work management. And Paige's leadership in AI strategy, I think underscores the importance of responsible AI deployment and ensuring that technology serves to enhance human capabilities rather than replace them.

[00:26:04] And I think the introduction of AI teammates signifies this bold step towards a more integrated and intelligent workflow, promising a future where AI and human collaboration is more seamless and the results highly productive.

[00:26:20] So the insights from Asana's research highlight a critical juncture for IT leaders right now, who are challenged with navigating this complex terrain of AI adoption with strategic foresight and agility. So as we collectively look forward to Asana's upcoming AI-powered features, including advanced reporting and goal tracking, it is evident that the company's commitment to leveraging AI for superior productivity and innovation

[00:26:51] remains steadfast. But hey, this is just me talking into a microphone in a room on my own. This isn't a monologue, it's a dialogue. So I invite you, what are your thoughts on Asana's AI-powered future? How do you see AI reshaping your own workflows and business strategies? And are you still sat on the fence and unsure about everything that's happening around you?

[00:27:14] Please share your insights and join the conversation as we'll continue to explore the transformative power of AI in the workplace by emailing me techblogwriteroutlook.com, LinkedIn, Instagram, just at Neil C. Hughes. Let's keep this conversation going.

[00:27:31] But that's it for today. So a big thank you to my guest, Paige, for joining me on the podcast today and an even bigger thank you for tuning into this podcast. I cordially invite you to join me again tomorrow. But thank you for listening today. And until next time, don't be a stranger.