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Let us start with the claim you were probably braced for, so we can get rid of it: agentic work management does not replace project management. Anyone telling you it does is selling something and overselling it. If you run operations or a PMO, you have earned your scepticism. You have survived at least one "revolutionary" tool rollout that produced a licence bill and a graveyard of half-adopted boards. So this article will not ask you to believe in a revolution. It will do s

There's a moment most growing teams in the Netherlands hit with Asana. The tool is live, the projects exist, everyone technically has an account and yet the work still runs the way it always did: in someone's head, in a spreadsheet on the side, in the Thursday meeting where everyone finds out what's actually happening. The scale of that gap is measurable. Asana's own Anatomy of Work research has consistently found that knowledge workers spend around 60% of their time on "work

For twenty years, "work management" meant a place to store work: tasks, owners, due dates, status. A human read the board and did the next thing. Agentic Work Management breaks that assumption. In this model the software doesn't just hold the plan it can also act on it, because AI agents sit inside the same projects as your team, with the same context and the same rules. Asana defines it in one sentence: "Agentic Work Management is how people and agents run critical workflows

Asana's AI platform has three headline products, and teams routinely buy the wrong one first. They share a brand, a data model, and even a billing pool but they solve different jobs. THE 15-SECOND ANSWER AI Teammates = ready-made agents that do the work. Dash = a personal orchestrator that tells you what needs attention and routes work to those agents. AI Studio = a no-code builder for your own custom AI workflows when no prebuilt agent fits. What each one actually is Not sur

Here's something I see constantly: ops managers, agency founders, and team leads who have genuinely talented people sitting right in front of them and still can't figure out why performance keeps plateauing. The team isn't the problem, the absence of a structured learning system is. When there's no training plan, people guess what "good" looks like. They either over-train or coast entirely. And the cost of that ambiguity shows up in missed handoffs, repeated mistakes, and the

Let's be honest about what performance review season actually feels like for most team leaders. It's that sinking feeling the week before reviews are due, suddenly you're digging through six months of Slack threads, emails, and half-remembered project updates trying to piece together a fair picture of what someone actually accomplished. You want to give your team the thoughtful, meaningful feedback they deserve, but the process is so exhausting that you end up rushing it. And

I know what it feels like when content production is running you instead of the other way around. Tasks being built from scratch every single time. Production requirements living in someone's head instead of in the system. Editors spending more time chasing status updates than actually editing. Stories falling through the cracks not because anyone was careless, but because the process had too many gaps for things not to fall. Here's the thing I've learned after watching teams

Let me tell you what having "an AI strategy" actually looked like for us twelve months ago. One person swearing by ChatGPT. Another using Claude. Our SEO specialist was sitting on a goldmine of prompts she'd built over months of prompts that had never made it to the content team, or anyone else. Everyone feels productive. Everyone feeling busy. And somehow the outputs were all over the place. Inconsistent brand voice. Duplicated workflows. Knowledge trapped in individual inbo

I've sat in enough rooms with enough leaders to know exactly what AI conversations look like right now. Executives are genuinely excited. And the people actually doing the work? They're nodding along in the meeting and quietly going back to their desks feeling anxious about what all of it actually means for them. This tension is backed by real data. And once you see it clearly, you know exactly why so many AI rollouts are struggling, and more importantly, what the ones that a

In our last post, we spoke on Why Your Team Isn't Using AI And Five Unconventional Ways to Actually Fix It, today we’d be sharing a practical guide on How to Get Organizational Alignment on AI. Here's something that broke my heart the first time I saw the data: more than half of employees genuinely believe AI will help their organization hit its goals. More than half. The will is there, the hope is there. And yet only 17% have ever received any training on how to actually u

I've watched the same thing happen at organisation after organisation, and it goes like this. Leadership comes back from a conference fired up about AI. Tools get purchased. A company-wide email goes out. There's a kickoff meeting with a slide deck and genuine energy in the room. And then, six months later, barely anyone is actually using them. The tools sit there. The mandate fades. The team carries on exactly as before and leadership is left quietly wondering whether the pr

The campaign went live on a Thursday. Nobody celebrated. We were just relieved it hadn't collapsed. The creative arrived two days late. Someone on the team had been working off a brief that had been updated without anyone telling them. And I found out about a deadline change three days after it had already shifted through a Slack message buried under 20 other notifications. We hit publish. We moved on. And I sat with this quiet, uncomfortable question for days afterward: why

I remember the exact moment I realised our marketing strategy was dead, not because it was a bad strategy, but because we had no system to keep it alive. It was a Wednesday, and we'd just wrapped what felt like our best quarterly planning session ever. Clear goals. Aligned priorities. Everyone in the room nods, I walked out genuinely confident we had something. By Friday, three different team leads were executing three completely different versions of the plan. Nobody was lyi

​ There’s a unique kind of exhaustion that sets in after a campaign doesn’t go as planned. It’s not because people don’t care. It’s the kind that comes when everyone shows up, puts in the effort, and gives their best, but somewhere between the kickoff and the deadline, something quietly falls apart. No one notices until it’s too late. ​ I’ve been in those debriefs where the post-mortem is mostly silent. There’s no one to blame, and everyone knows it. ​ That’s when I stopped a

There's this particular kind of exhaustion that hits when a campaign slips and the maddening part is that everyone tried. Your people showed up, did the work, and cared about the outcome. But somewhere between the kickoff call and the deadline, something quietly unraveled, and nobody caught it until it was already too late. This is not on your team, This is what it actually looks like when smart people are working inside a system that's stopped keeping up with them. What Mark

Have you ever considered asking yourself (or anyone else): Is the way our team is scheduled working with our workflow or are we just using the default arrangement? A bad schedule hinders productivity, silently creates bottlenecks, and wears down your top performers. This is often misunderstood as an issue with motivation. The first step toward the right schedule is to pose the right questions. Understand the Reality of Your Team's Workflow Before you make any changes to a sch

You pop something into an AI tool, hit enter, and… well, it's okay. Sort of. Not quite what you actually wanted, so you try again, and again. By the third or fourth prompt, you're wondering if AI is really all it's cracked up to be. It is. The problem isn’t the tool; it's the conversation you’re having with it. Most people engage with AI as if it were a vending machine: press a button, get a result. Generic output is par for the course because the input was vague. The solutio

If you've ever ended a workday unsure whether your team actually moved anything forward, you're not alone. Collaboration sounds simple but without the right system, it's mostly noise: scattered messages, unclear ownership, and status updates that require a meeting to obtain. Here's what a day of collaborating in Asana actually looks like and why it changes how work gets done. Your morning starts with clarity, not chaos Instead of opening your inbox and triaging what needs att

Most marketing teams are running on empty. Not because the work isn't getting done, but because too much of the day goes to work about the work. Writing first drafts from scratch. Manually auditing SEO gaps. Pulling sprint retrospectives together before a meeting. It's relentless, and it's exactly the kind of output that burns out good teams. Asana's AI teammates are built to absorb that load. Not as a chatbot you query on the side, but as a named, role-specific collaborator

The AI tools market is loud right now. Every platform promises transformation, every vendor wants a meeting, and every leadership team is asking why you haven't moved faster. In the middle of all that noise, marketing leaders are stuck with a genuinely hard question: how do you build AI into your tech stack without putting your budget, your brand, and your outcomes at risk? The answer isn't to move faster but to move smarter. Invest in the stack you already have Before lookin