What’s it really like to hand over the reins of project management to an AI-powered
system? To find out, I sat down (virtually) with Mark Davis, a Project Management Office
(PMO) director at a Fortune 500 tech company based in North America. Mark’s team
participated in our early adopter program for ActionBoard. He has 15+ years of project
leadership experience and has used everything from Excel trackers to high-end enterprise tools. I
couldn’t think of a better person to evaluate how ActionBoard stacks up and how it changes team
dynamics. Here are key excerpts from our conversation, which turned into an honest discussion
about initial skepticism, surprising wins, and lessons learned.
Q: You’ve managed projects with many tools. What was your first reaction when you heard about ActionBoard’s AI approach?
A: (Mark Davis): “Honestly? Skeptical. I’ve seen so many ‘revolutionary’ tools come and go.
Every few years someone promises AI that will magically manage your projects. My gut reaction
was: ‘Alright, show me.’ I wasn’t against it, but I had healthy doubt. The turning point for me
was the pilot demo with our own data. We fed ActionBoard one of our active project plans –
something my team was already working on manually – and the AI immediately pointed out two
high-risk tasks that I hadn’t flagged yet. It identified that those tasks were upstream dependencies
for multiple work streams and that based on our usual pace, they were likely to cause delays.
That blew my mind. It’s not that we wouldn’t have caught it, but ActionBoard caught it in
minutes, whereas we might have stumbled on it in a status meeting a week or two later. That’s
when I thought, ‘Okay, this is different.’”
Mark’s initial skepticism is something we encountered a lot: experienced managers
understandably asking, “Is this AI just hype or will it actually help?” His experience highlights a
common theme – seeing is believing. Once he saw the AI in ActionBoard deliver a non-obvious
insight, it earned credibility.
Q: How did your team adapt to using ActionBoard? Was there resistance?
A: “There’s always some change management. At first, a few project managers on my team were wary – they thought the AI might be a ‘boss’ that would second-guess their work or even replace parts of their job. We addressed that head-on. I explained that we’d use ActionBoard as a decision-support tool, not an autocratic decision-maker. In practice, within the first month people realized it wasn’t here to catch them making mistakes; it was catching the stuff all of us collectively could miss. One PM joked that ActionBoard was like having an extra team member who never sleeps. For example, we had a junior coordinator who was still learning the ropes – ActionBoard would gently prompt them with things like, ‘Have you considered Task Z? It’s approaching its deadline and depends on Task Y being done.’ It was like a built-in mentor for them. Far from resenting it, they loved it because it made them look good – they were on top of things.
I also noticed the team started to trust the AI’s suggestions as they saw them pan out. Early on, someone might say, ‘ActionBoard is suggesting we re-prioritize these tasks, do we agree?’ We’d discuss it, maybe adjust slightly, and follow the plan. After a few cycles where the AI’s calls proved right – like avoiding a crunch or hitting a milestone smoothly – the questions turned into, ‘ActionBoard suggests X, let’s do that.’ It earned authority by being usually correct. I’d say the adaptation period was maybe 4-6 weeks for us. After that, it became second nature.”
What Mark describes is a progression from skepticism to reliance. Importantly, he positioned
ActionBoard as a helper, not a micromanager. That set the tone for positive adoption. We’ve
heard similar stories elsewhere: once teams see that the AI reduces their grunt work and helps
them shine, they embrace it rather than feel threatened by it.
Q: Can you share a specific outcome or metric that improved after using ActionBoard?
A: “Sure. One of the biggest measurable changes was our planning overhead time. We used to
spend, on average, about 4 hours per week per project just in meetings for planning and status
updates – going over who’s doing what, what’s late, what to focus on. With ActionBoard, a lot of
that became automated or just visually clear on the board. In Q1 this year, we cut down our
weekly status meeting from one hour to 30 minutes because there were fewer surprises to
discuss; everyone could see the real-time status and AI warnings on their own. Across 10
projects, that freed up maybe 20 staff-hours a week. We reinvested that time into actual project
work and brainstorming solutions to problems (instead of just identifying problems). Also, our
on-time delivery rate went up. Last year, roughly 60% of our projects hit all key milestones on
schedule. In the first half of this year, we’re at about 85%. That’s a huge jump. Granted, some of
that is due to other factors (better estimation, some easier projects), but I credit ActionBoard for
a lot of it. The AI kept us ahead of issues. We were firefighting less and executing more
smoothly.”
Hearing those numbers was gratifying. An 85% on-time milestone hit rate is world-class in
many industries, and while ActionBoard isn’t solely responsible, it clearly played a role. Mark
also mentioned something important – by cutting status meeting time, they actually freed
capacity for value-added discussions. This is a subtle win: not only did efficiency improve, but
collaboration quality did too (because meetings could focus on solving issues, not just finding
them).
Q: How does ActionBoard compare to other tools you’ve used, like Asana or Monday?
A: “I’ve been an Asana user, and we tried Monday.com for a while. They’re good tools, don’t get me wrong. But they always felt like a repository rather than a partner. With those, I’d joke that the tool is as smart as the person operating it – it won’t do any thinking for you. ActionBoard is the first time I felt the software was almost like a team member. For instance, Asana can show you tasks and you can set deadlines, but it won’t say, ‘Hey, based on past data this deadline is unrealistic’ or ‘These two tasks are interdependent, watch out.’ We had to manually catch all that. ActionBoard surfaces these insights. Another difference is the knowledge accumulation. In Monday, we would finish a project, archive the board, and that was it – the next project we start is blank, no memory of what we learned last time except what’s in people’s heads. ActionBoard kind of flips that: it gets smarter with each project. It will actually remind you “last project similar to this had an extra testing phase, consider adding that.” No one else does that as far as I know. It feels like moving from a static checklist app to a dynamic, learning system.
One more thing: the ActionGraph technology underlying ActionBoard (I know your readers will learn about it in upcoming posts) – from my perspective, that’s the secret sauce. It’s why the AI can be so context-aware. Traditional tools don’t have that graph of connections under the hood, so they can’t reason about the ripple effects of a change. ActionBoard can. And boy, once you’ve experienced that, you can’t go back. I remember recently we were discussing if we could afford to fast-track a certain feature in a software project. In the meeting, someone said, ‘Let’s ask ActionBoard what happens if we do.’ We went to the board, made a quick change (marked that task higher priority and sooner deadline) and the system re-flowed the schedule, immediately highlighting that doing so would likely delay two other items or require more resources. It was like having a simulator for our project. That kind of real-time scenario planning was not possible in our old tools, at least not without hours of manually rejiggering and checking everything.”
Mark’s comparison sums it up nicely: the legacy tools are passive and forgetful; ActionBoard is
active and accumulative in intelligence. Also, his anecdote of teams literally consulting
ActionBoard for decision support (“let’s ask ActionBoard”) is exactly the sort of changed
behavior we hoped to see – the tool is no longer just an after-the-fact log, it’s part of the
decision-making process.
Q: Any advice for teams considering making the leap to an AI-driven system like ActionBoard?
A: “My advice is: embrace it, but stay engaged. The worst thing you could do is think ‘oh, the AI will handle everything, I can be hands-off.’ It’s not autopilot where you fall asleep at the wheel. It’s more like a really advanced driver-assist – it will make you a better driver if you work with it. So be prepared to train the AI a bit (give it good data, correct it when it suggests something off), especially in the early days. Tailor the settings to your needs – the system has a lot of knobs you can turn. For example, we tweaked how sensitive the urgency scoring was because initially it was over-alerting us on small tasks. Small adjustments made it fit our style better. Also, communicate with your team about why you’re using it and encourage them to give feedback. In our case, a few frontline users pointed out ways to improve our workflow with ActionBoard that I didn’t foresee.
Lastly, I’d say measure something before and after. Whether it’s meeting hours, on-time task completion, team satisfaction – have a baseline and see if the tool moves the needle. In our experience it did, and having those numbers helps build long-term buy-in (and justify the investment to upper management!).”
That wraps up our illuminating chat with Mark Davis. His experience reinforces that
ActionBoard isn’t just a cool tech toy – it’s making a tangible difference in how teams operate.
His advice also reminds us that human leadership remains crucial; AI is a force multiplier, not a
replacement. In our next blog, we’ll peel back the curtain on the technology that powers this
“intelligent partner” experience – the ActionGraph and dual retrieval system that Mark alluded
to. If you’re curious about how ActionBoard actually thinks and learns, stay tuned. We’re going
into the engineering marvels that make true intelligence possible in practice.
