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Q&A with Asana AI Leaders Paige Costello & Eric Pelz
What will organizations that don't adopt AI miss out on?
Paige: AI is a competitive advantage. Teams that harness AI effectively will be able to move faster, make smarter decisions, and deliver better results than those that don't. As AI becomes central to how work gets done, organizations that lag in adoption will find it increasingly difficult to keep up. And for younger workers, there's a growing expectation that AI will be a core part of their work experience. Companies that embrace AI will have an edge in attracting and retaining top talent.
We're already seeing this at Asana - AI literacy is a competency we actively cultivate and reward. It's helping teams get higher quality work done faster. The power of AI lies in its ability to augment and sharpen human ingenuity. And we're hearing from customers that Asana's AI capabilities are a true differentiator. It empowers them to get higher quality work done faster. At Asana, we envision AI like a teammate helping people achieve their goals more rapidly, and with less drama. This human-AI collaboration model, with AI embedded into teams' workflows and moving work forward, is the future.
What does the future of business look like with AI?
Eric: In the future we're building, AI will become akin to a teammate for knowledge workers, seamlessly integrated into how they collaborate and create value every day. Similar to how managers think about hiring and onboarding for new teammates, they’ll be thinking about what ways they can leverage AI to help them achieve their objectives. This will empower the people they hire to spend less time on mundane coordination and more time on deeper work that moves the needle for their organizations.
Various types of business processes will use AI differently. Analogous to how some companies operate with different levels of employee autonomy, or operate with top-down versus bottoms-up management, companies will configure AI to have different levels of guardrails. I don’t expect this will look like “some teams use no AI at all”. Instead, they’ll operate on a spectrum of how that AI is used. For example, one side of the spectrum may be to help employees think through difficult problems (similar to “rubber duck debugging”). The other side of the spectrum may be for employees to use AI to triage requests or draft entire artifacts. We’re working with customers to explore ways to leverage AI across this entire spectrum, so that Asana can proactively help customers navigate the right way to use AI for their use case.
What is the biggest challenge to educating teams about AI?
Paige: There's a lot of confusion and even fear about AI. People worry about being replaced by machines or AI going rogue. But it’s important to focus the conversation on how AI and humans can partner to achieve more together. AI fluency is a journey. Encourage teams to take a task they were planning to complete “the old way” and budget ten minutes for trying to complete it first with the help of AI. This will help them build understanding and confidence.
It's also critical to be transparent and apply AI responsibly - demonstrate what data is used, whether models are being trained (for Asana features, we don’t allow training on any data, period), how bias is avoided, and what safeguards are in place. Building trust is essential. We're committed to being open with our employees and customers as we navigate this new frontier.
What is the most important thing leaders must understand about AI today?
Eric: The pace of AI progress is unlike anything we've seen in computing history, and organizations need to adapt quickly and continuously to harness its potential. Adopting AI is not just a tool implementation, but fundamentally a change management challenge. This is a multi-faceted strategic shift for organizations, encompassing everything from upskilling employees to reimagining processes and reshaping how work gets done.
At Asana, we're investing heavily in education and training to build AI fluency across our organization. We want every employee to feel equipped and empowered to leverage AI in their role, and to adapt it to their exact workflows and way of working. And we're baking best practices for human-AI collaboration right into our product. Platforms like Asana play a key part by providing the scaffolding for AI to plug into existing workflows. We make it easy for teams to tap into AI's potential without a steep learning curve.
What has been the most surprising thing you've learned since leading a team focused on AI innovation?
Eric: The pace of change in the AI space is staggering. Capabilities that seemed impossible just months ago are now viable, and the industry hasn’t seen signs that progress is going to slow down. As a leader, you have to get comfortable with ambiguity and be ready to adapt. That’s why we've had to reimagine our product roadmaps and planning processes to be much more agile. We're learning as we go, leveraging our networks and strategic partners to keep at the forefront of what’s possible. Focusing on top-level strategic alignment and clear goals has been more important than ever, along with updating teams around strategic context and empowering fast decision making. AI can drive step-change improvements in how we manage work - streamlining processes, delivering predictive insights, and maintaining clarity despite a fast-moving team.
But, there’s so much jargon in the industry. In the engineering space, as an example, there are many “new” concepts being invented that are actually just applying existing best practices. But because these concepts are “named” and mentioned as if they’re novel, it makes it easy to feel imposter syndrome when trying to stay up-to-date in the industry. I expect (and hope) that we’ll see the industry moving to use more analogies and examples to “show, not tell” to combat this.
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