Teams | Collaboration | Customer Service | Project Management

Scaling agentic AI across an enterprise requires more than great technology. It requires trust. This final post in the series explores how governance turns AI from an experiment into a reliable operating model, and what it looks like when operations teams are finally free to focus on the work that actually moves the business forward. At some point in every AI rollout, the same question comes up: how do you help everyone move faster without creating a mess? Operations leaders have seen this story before.

For most operations teams, managing incoming requests is itself a full-time job. This post explores how multiplayer AI helps teams move out of reactive mode, automating intake, keeping portfolios on course, and giving leaders the real-time visibility they need to make better decisions, faster. Every operations team knows the feeling. Requests arrive faster than anyone can review them.

An agent pulls information from your other systems to finish a job, like gathering project updates and drafting a status report for someone to approve. Its permissions determine which actions it can take. This 10-minute guide goes over different types of agents and how they work. It also explores workplace examples and how agents support AI work management.

At ARM Creative, a single campaign can span broadcast TV, over-the-top (OTT) ads, radio, Spotify, paid social, display, and retargeting—all running at once, each with its own deadlines, specs, and approvals. It used to be that campaign updates lived in email threads, while feedback was scattered across Slack and inboxes. Without a shared system, it was difficult to see whether a deliverable was approved, in progress, or falling behind.

Operations teams are spending more time managing work than doing it. Agentic AI changes that, not by replacing people, but by taking on the coordination that slows them down. This post explores what multiplayer AI actually is, why it's different from the AI tools you've used before, and what it means for how operations teams can finally move at the speed of the business.

When Andrew King, who heads up competitive intelligence at Asana, needs to help a sales representative win a deal, the information has to be exactly right. This means sourcing specific, current details customized for each individual rep. King supports a 400-person sales team. Each rep is working different deals, facing different competitors, and at different stages of the sales cycle.

As AI accelerates work, leaders need to be more deliberate about what technology takes off people’s minds and where human attention can create the most value. AI promises to help organisations move faster. But at two Asana executive dinners held in Sydney and Melbourne in August, a different leadership question emerged: what should we choose not to accelerate? The challenge is not finding more hours in the day, but creating better conditions for the hours people already spend.

I’m TJ Power, a neuroscientist, no.1 bestselling author of The DOSE Effect, and the founder of DOSE Lab. Over the last 12 months, my team and I have been laser focused on a new question: how can we help society build successful brains that are ready for the AI future? Recently, with Asana, I hosted a series of dinners in Sydney and Melbourne for C-suite executives.

When Jerry Weltsch, Head of Analyst Relations at Asana, receives a new industry report, he doesn't read it cover to cover. He assigns it to a custom AI research assistant to analyze. Jerry is responsible for managing relationships with industry analysts who specialize in software markets. That means constantly reading research, making sense of it, and communicating what it means for the business. Before customizing his teammate, Jerry used to process four or five analyst reports a week.

Knowledge workers spend more than half their time on work that isn't their actual work. Sorting requests. Writing status updates. Following up on things that were supposed to be done last Tuesday. According to Asana's State of AI at Work 2025, that number is 55% of the workday — busywork that AI can now absorb, if you set it up right. Download the report.