Where AI Actually Fits on a Project Team

Tim Fisher: Hello, and welcome to The Future of AI in Project Management, a series where we go beyond the pitch deck and dig into how AI is actually changing the way teams plan, deliver, and manage work. Today, we're featuring Productive. If you're an agency, consultancy, or professional services business and trying to figure out where AI can actually improve delivery, utilization, forecasting, and operations, and not just generate content, then this is the conversation to be in.

We're gonna hear how Productive is using AI to automate the busywork that slows teams down, surface risks before they become problems, and help professional services businesses make better decisions faster. My name is Tim Fisher, and I'm VP of AI at The Digital Project Manager. My job is to figure out where AI actually works and where it's still just marketing slides.

So I'm gonna be asking the questions your team would ask. So joining us today is Bernie Vrbat from Productive. Over the past three years, Bernie has worked closely with agencies, consultancies, and professional services businesses of all sizes, helping them solve operational challenges and get more value from their tools.

Today, she's focused on AI transformation, just like me, bringing together technical expertise and real-world agency experience to help teams understand not just what's possible with AI, but what's actually worth doing.

Bernie, it is really great to have you here.

Bernarda Vrbat: Thank you, Tim. It's good to be here.

Tim Fisher: Can you give us the 30 second version of Productive for those who don't know?

What does it do, and who's it built for?

Bernarda Vrbat: Yes, of course. So Productive is an all-in-one platform designed specifically for professional services businesses. So if you're tracking time for a client project, this would be the perfect platform for you. Basically covers the entire operational workflow, from managing a deal to projects, budgets, resourcing, and then all the way to invoicing.

And now with AI built in, most of the operational work involved in all these steps happens in the background, and we're taking it one step further with our agentic features, where it happens on its own, so you can spend less time on admin and more time on the work that actually matters.

Tim Fisher: So kind of a silly question in 2026, but, like, why is AI such a big focus for you all right now?

Bernarda Vrbat: Yeah, I don't think it's silly at all. I think we've had our own AI features for a while. We've had things like autofill on expenses and using AI to write and structure text in docs. And we found that those features were genuinely useful to our customers. We wanted to look at where AI could make a real difference.

Because technology is advancing so rapidly, AI can now assist with work that has real complexity, so we're not just automating one-off tasks, but helping you manage and analyze business workflows. So we wanted to bring that into what Productive has already done well, and that's being an all-in-one solution for professional services businesses.

Tim Fisher: Cool. What do you think has been, like, the biggest challenge for your customers that you think AI helps them solve?

Bernarda Vrbat: Well, I think instead of solving a single challenge, we like to say that AI and Productive addresses many challenges you deal throughout the day, things like blocked tasks you... that have been forgotten or timelines that you need to shift, scattered data that you don't have time to analyze.

We wanted to move all that mental load off people so, AI can do it in the background, and we found that when you do that, it opens a new way of working. You no longer have to keep a dozen of small issues in your head, and you can show up fully to the work that actually matters.

Tim Fisher: That makes sense.

Look, everybody's putting AI in everything. There's a chatbot over here or something else over there. What's unique about how Productive is approaching AI compared to others in the market, do you think?

Bernarda Vrbat: I'd say what's unique about how we're approaching the AI is the platform itself. You all know that AI tools need to pull data from somewhere, so you end up having to connect them to four or five different tools, and still it not be, might be exactly what you need.

So with Productive, you have all that data built in. Productive is a specialized platform that covers everything, as I've mentioned, from sales to invoicing, so it knows how your people are allocated, how your projects are performing, and how your client relationships are actually going. I feel like that combination of operational, financial, and relationship data is incredibly f- powerful for AI, and I'd say that's unique to Productive.

Tim Fisher: I know we're gonna see AI in several forms, say, like conversation and skills and agents. Can you talk a little bit about the difference between skills and agents? I'm not sure everybody fully understands all that.

Bernarda Vrbat: Yeah, right. I completely agree, and I think that's an important question to address. So of course, you have your chatbots.

We are all familiar with them, and this is the type of AI people are now very used to. You basically ask it something, you get a result back. With skills and agents, they're still kind of new, so it might be worth getting into a bit more detail what they are. So with skills, I think they're pretty simple to understand, and you've all probably seen them in tools like Claude or ChatGPT, right?

So skills are essentially structured knowledge you give to AI. You tell it how to carry out tasks so it's in line with what you actually need. Now, when we move on to agents, if we compare skills, if skills are about teaching your AI how to do something, agents are about letting it actually go and do it.

An agent doesn't just answer a question or follows instructions, it's completely autonomous. It can work through multiple steps, make decisions along the way, use different tools, and you don't have to be involved at every stage. I think this is where the complexity really starts to ramp up. With the chatbot, you chat with AI and get it to do things.

With skills, you're shaping how it behaves. And with agents, you're not only shaping the behavior, but delegating truly complex workflows to AI. You're basically setting a goal, and agent figures out how to get there.

Tim Fisher: Very good description, by the way. That's very similar to how I talk about it, too. Just thinking about all this, like, how do you see the role of the project manager evolving as AI just becomes part of the day-to-day work?

Bernarda Vrbat: Yeah, I think the best project managers have always been the ones that can see the full picture, and what AI does is actually make that easier thing to do. So because when you take all of the repetitive work that project managers do, it actually frees up their day-to-day so they can do more of what they do best, and that's making decisions that have big impact on project progress and success.

I think we'll start to see something interesting happen here. So when you free up that time and mental energy, people naturally start to grow. So project managers will be able to get into maybe design process more or get closer to the code. So I think we'll be seeing the project manager become more of a, if I may say, jack of all trades, like someone who doesn't just manage work, but truly understands it from every angle.

Tim Fisher: I think you're exactly right. I think especially roles like project managers, they've turned into something they were never really intended to be with so many tasks, you know, sort of sitting in that responsibility matrix, and this this sort of technology is exactly what you said. Hopefully it will allow folks to become, you know, what they...

You know, spend time doing the things they really want to be doing, and they can really move the business forward. So that's great. Okay, so I was digging around, and you recently released some research looking at how teams are using AI and the types of work they're comfortable delegating to it. What stood out to you the most about that, and how has that influenced the way Productive thinks about building with AI?

Bernarda Vrbat: Okay, you've done really deep dive into what Productive did. But yeah, that's right. So before we've implemented our agents and advanced AI features, we conducted a survey with our users to actually see what they think and feel about AI. So what we found is that what people actually want agents to handle is a...

it's a very specific thing. So tasks that came up most consistently share a common profile, things like scheduling tasks, tracking time that I've tackled in our AI assistant project planning, project estimation. These are all repetitive and time-consuming tasks. For example, client communication came up as a task that businesses were least likely to solve with AI, which I think makes a lot of sense, and I think this is exactly what we took as our guiding principle.

Rather than chasing the broadest possible version of AI, we built features that help teams handle their busy work.

Tim Fisher: Yeah. I think that makes sense. One thing that definitely comes through in both the research and the demos today is that AI works best when it's removing operational friction rather than replacing human judgment.

Do you think generally that's where organizations should be focusing their AI efforts?

Bernarda Vrbat: Honestly, yes, and I think it's the more honest starting point, too. So busy work is where AI delivers value without introducing the actual risk You're not asking AI to make complicating judgment calls. You're asking it to handle repetitive work with expected outcomes.

Tim Fisher: Your research also paints a picture of an industry that's definitely still experimenting. So agencies are seeing benefits from AI, of course, but many are still trying to figure out the pricing and the ROI and the operating models and all of that. What's the question agency leaders should be asking about AI that you don't think they're asking enough of?

Bernarda Vrbat: I think the question most leaders aren't asking enough is, "What do I want my team to do with all of the time that AI frees up?" Because AI is already handling a big chunk of existing work, and it's only going to happen more and more, and finding the most productive, no pun intended, way to use that extra time, the initiatives that create the most value, that's, I think, what's going to make the biggest difference.

And there is a human side to this, too. I-- For a lot of people, their job descriptions will evolve either a bit or a lot. It doesn't matter. But supporting your existing talent through that transition is just as important for ensuring that you're getting the most out of AI.

Tim Fisher: You said something extremely smart.

It comes up Actually, it doesn't come up very often, the conversation of what people do with the time they are now freed to do. And so I'm glad that you're thinking about that from the beginning as you do all these things. Another question, so just seeing all this, it's pretty clear you're thinking about agents almost like employees to the end, like having humans responsible for the actions and all of that.

In a world where this becomes more common, how does the role of a project manager shift from doing the work to managing the agents who do the work? That's pretty fundamental.

Bernarda Vrbat: Well, I think the project managers will actually just starting to delegate the work that's repetitive to agents, to skills, to AI itself, and they will be involved more in client relationships.

As I mentioned, they won't delegate that part to the AI. They're gonna build relationships, deliver better projects. Clients will be more satisfied with the work they've done. So I think this will be the biggest impact that the AI gives the project manager.

Tim Fisher: Okay, let's do a little crystal ball exercise. So fast-forward three years, five years what's the biggest shift that you expect AI to bring to the way that the teams work?

Bernarda Vrbat: Oof. I think three to five years is a very long horizon to speak confidently about-

Tim Fisher: It is.

Bernarda Vrbat: You know, with the pace of development that's happening. But let's say for the short-term picture, we can see that AI is taking on more and more of the execution layers in areas like coding and writing, and I think that operational work will come next.

Project management is probably where you feel it first, you know, managing tasks, timelines, time sheets, all of these coordination overheads that project managers have. And I think looking further out, the fundamental shift will be the way teams are structured around AI. So rather than using AI as a tool you pick up and you put it down, people will likely manage a suite of agents, you know, configuring them and managing output And as I've mentioned throughout this whole chat with you, the human role becomes less about doing the work and more about making value decisions.

You know, what matters, what we need to prioritize, what quality looks like.

Tim Fisher: So leave AI things to AI and human things to humans. Yes. Last but very not least, without giving away any secrets, I would love a little bit of glimpse into what's next on Productive's AI roadmap.

Bernarda Vrbat: We won't spoil this too much, but I can share with you what's coming next.

So we've recently released artifacts, which will let you turn prompts into visual outputs. So for example, by asking for data, you can ask for a full dashboard, or you can even ask for it to be downloaded as a PDF or HTML. So that will be really cool to see. On the agent side, we're working on event-triggered agents, so they kick off automatically when something changes.

You know, you're managing a budget, and something changes, that could be a trigger that an agent is looking for and makes a change. And we're building towards making agents more proactive, reaching out to you when they hit the roadblock so you can step in and keep things moving.

Tim Fisher: Fantastic. Makes a lot of sense in the world. That was an awesome conversation and look into the future. Really appreciate it. To wrap up, Bernie, if people want to learn more about Productive what do they do now?

Bernarda Vrbat: First of all, thank you, Tim, for the great conversation. If anyone wants to dig deeper, the best place to start is our Productive 5.0 page.

That's where you get the full picture of everything we've built around AI and what this whole release is about. And from there, I'd point you to our roadmap and product updates pages where we share what's coming next and keep you in the loop as we continue to ship. We're moving fast, so there's always something new worth keeping an eye on.

Tim Fisher: Great. Very cool. That's all the time we have for today. Bernie, thank you so much for joining us.

Bernarda Vrbat: Thank you, Tim.