Where AI Actually Helps Project Managers in Delivery Work

Becca Banyard: Hello everyone and welcome to The Digital Project Manager podcast. My name is Becca Banyard, and I'm actually the producer of this show. But today I'm stepping into the hosting chair for Galen as we have an episode that's a little different from our usual format. This conversation was originally recorded as part of our future of AI in project management live event series where we explore how AI is changing the way that teams plan, deliver, and manage work.

In this session, we're joined by Scoro to dig into how AI is showing up in project delivery today and what PMs and delivery leaders should be paying attention to, next. You won't hear the live product demo in this podcast version since it's kind of hard to follow without the full visual. You can access the full recording by heading to the link in the show notes, but today you will hear the full strategic conversation around using AI in a practical team ready way.

Joined with me are two incredible guests. First up is Tim Fisher, the VP of AI at Black & White Zebra. Tim's actually gonna be co-leading the discussion with me because he has over 20 years of experience in both tech and AI, and he's gonna help us unpack what we're seeing and connect it back to your day-to-day as PMs and leaders.

And joining us from Scoro is Harv Nagra. Harv is a delivery and operations expert and the host of The Handbook: The Ops Podcast. And if you've been around the DPM community for a while, you've probably heard him on the show or speaking at one of our events. He is a friend of the community and we're really excited to have him here.

So Harv, welcome!

Harv Nagra: Pleasure to be here. Thanks for inviting me.

Becca Banyard: So Harv, just before we get into things, I would love to know more about Scoro. Can you give us a 30 second overview of what Scoro does and who it's built for?

Harv Nagra: Absolutely. So Scoro is a professional services automation platform. That term also known as PSA.

It doesn't always resonate with people. It's pretty rare to hear people going around saying PSA. What it really means is it's designed for any kind of professional services business. So that can be an agency, it can be a consulting firm, it can be an IT firm, an accounting firm, a law firm, any kind of business that sells time and expertise.

It differs from a project management system like the ones that we're very familiar with, like the Asanas, the JIRAs, Trello's and so on. In that it goes beyond project and task management, and beyond that, just that collaboration. So, you know, on one end we have tools like that and then you get a little more complex and you have tools like Monday, Clickup, Teamwork, and stuff like that, that allow you to kind of couple together some modules and build something.

Then you have what I call the PSA space, and with these kinds of systems, it's kind of an operating system for your business. So it's like you build your budgets and your quotes in the platform. You can resource and plan your schedules. You can turn those quotes into projects and manage those projects and budgets.

And finally track your time, track your budgets, invoice report on your business, and it plugs into other systems like your accounting tools, your HR platforms, stuff like that. So it really does end to end beyond just project management.

Tim Fisher: Very cool. So you work with project teams and agencies and all those sorts of groups that you just talked about every single day.

So you definitely have a front row seat to what's actually hard about delivering work right now. So let's start there. From your perspective, what is the hardest part about delivering projects successfully today?

Harv Nagra: Tim, I used to be a digital producer many years ago. At some point, I was managing a team of digital producers working in an agency as digital director, and I don't know if this has really changed, right?

From my experience, it was always the changing timelines, which creates the complexity, right? The number of revisions you had are never what the clients end up expecting. There's scope change requests and there's often delays to receiving content or feedback. So the best laid plans at the beginning of the project end up not being reality, right?

So there's a lot of change and staying on top of all of that, all those moving parts, the communications alone with all those stakeholders, updating your budgets every time there's a scope change. Updating your tasks, updating your plans, your timelines, all that kind of stuff ends up being a lot of work.

So I don't think that's new. And that's probably always been the case since the beginning of project management. So that's a challenge for us.

Tim Fisher: Certainly. Yes. What do you think leaders often get wrong about project management that Scoro helps fix?

Harv Nagra: You end up kind of buried in a lot of change. And I think the expectation is always very optimistic At a start of a project, you know that things are gonna go perfectly.

A lot of times we're under pressure to build really lean budgets these days as well just to win a project. So we might do that and then you end up having no slack if anything goes wrong. Right. And then on top of that, like I was saying, when you have a load of different tools that you're coordinating all this stuff with, it ends up being so much admin work rather than doing real value stuff, right?

You're building your budget somewhere else. You're using Harvest, you're using Asana, you're time tracking somewhere else, you're exporting spreadsheets to try to reconcile your budgets, and that ends up taking a lot of time. So there's a few things that crop up.

First of all, there's a huge amount of inefficiency in that if your team is constantly like importing and exporting data or replicating data between systems. It introduces human error into that process whenever you're doing that. And there's a huge slowdown in not only seeing how your business is performing, but how your projects are performing, right?

Like I, I talk to agencies or consulting firms sometimes that are literally your logging time somewhere. They export it once a week, and then they put it in a Google sheet to try to add up what they've accumulated in that week between that gap. And if you're busy and you don't do that process for two weeks, anything could have happened. You could be way over budget and have no idea. So there's a lot of admin work and there's a lack of visibility, and that's where something like a PSA, like Scoro comes in. 'Cause it's a single source of truth, everything's in one place, you're not exporting and importing, you're not copying data from one place another.

It just exists. Right? So, like I said, it's that consolidation piece from the quoting to the project management, resourcing, time tracking, invoicing, all of that stuff in one place. And the last thing I'll say, Tim, it is something I think businesses graduate to at some point as well. There will be a point where you're using all the different systems, but there does come a point in a growth journey where you're like, okay, this is now chaotic.

We're too big to be operating like this, or Our projects are too complex and we need to grow up a little maybe.

Tim Fisher: Yeah. That'll make sense. It is amazing. I've seen this many times how normal the craziness of connecting all those different systems often through copy and pasting and spreadsheets that we all just sort of accept as fact.

So AI, given all of that, where do you see AI fitting into these challenges that you're talking about right now?

Harv Nagra: I was a producer, like I said. Project managers, we end up having to orchestrate a lot of work. But that orchestration is done manually. And the other thing I see with a lot of businesses using AI, they use it in quite a spotty way to accelerate something.

Sometimes that's accelerating a broken process. So instead of fixing it, we're just saying, okay, it's good enough that we can do it faster because we're using an LLM. But I think right now we're on the cusp of doing something much more transformational, which really kind of hopefully is gonna make PMs, producers, project teams feel like that one project manager has a team of people behind them virtual team like AI that helps them do all the grunt work. So that they can step away, they can give a prompt and, you know, the AI does all the boring stuff so they can do the more high value work. And I think that's what's really exciting.

Tim Fisher: If you could zoom in just a little bit, like what's like one specific pain point or friction point that AI's helped your customers with so far?

Harv Nagra: Going back to that example I was giving you a few minutes ago, right? Projects never go to plan, right? Timelines slip, scope changes, all that kind of stuff.

Approvals get delayed and then you're using the multiple systems and stuff like that, so the insights you need aren't available. I think that's where we're getting to with the tech. We're building that the insights are available. Traditionally, we've had products including ours, that produce reports.

Right. But the problem is then you rely on the human to have to go and interpret that, which is fine. It's useful. But sometimes it's quite helpful to be given that information proactively. So you're not hunting for it. You're not trying to analyze it yourself, but someone's telling you, okay, this is the issue and you need to sort it out.

Our customers have been beta testing our MCP and giving us lots of ideas and feedback on what they want to be able to do, and it's really exciting hearing some of those ideas. Right? Some of it right now it's not possible, but I think we're gonna be getting to that point where more and more of this stuff is possible.

You tell AI what's changed or what needs to change or what you want it to do, and it goes and executes that work.

Tim Fisher: I have another question before we go on. You dropped an acronym that I thought would be worthy of a quick definition. So MCP, what exactly is that? I think a lot of people on the call today probably have heard about it. Worthy of maybe a little explanation.

Harv Nagra: So I think everyone on the call will definitely have heard of API, right, Application Programming Interface, which just means a way for two apps to talk to each other, share data, share functionality. But that typically requires the developer to code that connection, to share that data and do whatever it needs to do.

So the way I explain MCP in the simplest terms is it's like an API layer for AI platforms like ChatGPT, or Claude to connect with other systems. And the cool thing is that like not only does the information flow so you can get it to read give you answers based on your systems or whatever, you can ask it to take actions in those systems.

So go do this thing, right? So it becomes like a command center for your other tools. Where it gets even better, first of all, is that unlike an API, you don't need a developer to code this. It's a prompt in your favorite LLM, right? So that's quite powerful. The other thing is the multi-tool ability of MCP.

So it's not just taking actions or re giving you information from one system, but it can do this stuff across multiple systems at the same time. And I think that's what's really cool.

Tim Fisher: So, everyone's putting AI and everything. You know, you can't get through any sort of Instagram ad, you can't get through any advertisement at all, any conversation without someone saying, Hey, look at how we put AI into our software.

So it's sort of table stakes these days. Like there's some integration of artificial intelligence and everything. What is Scoro's like different take here, like how are you guys doing this differently? What is unique about how you're using AI in your platform versus people in like your area?

Harv Nagra: We've just celebrated ChatGPT's third birthday a couple weeks ago.

As soon as that came out, I think a lot of systems and products rushed to jam text generator into their product so they can claim that they had AI, right? At this point, we all have our favorite text generators, our favorite LLMs, and they're best in class and doing the most innovative thing. So do we really need a text generator in every product?

I don't think so. And that was never our approach. I think we almost saw that as cheating. Like, yeah, we could do that, but why would somebody want to use a text generator in Scoro? Or what's the logic there? Right? So we didn't take that approach. We already acknowledged that we are kind of an operating system for a business, right?

Because we're, like I said, you got your budgets, you got your projects, you got your invoices, you got all your reporting and stuff. So we wanted to create an AI layer that sits on top of that and says, you already have this amazing product that automates all this data and workflow, but now we're gonna give you insights on top or help you run work and execute work, and stuff like that.

So it's like, our vision was to create basically like a coworker that can do everything you do in the product, but it can do it for you. So that full workflow orchestration, like I was saying a few minutes ago, is a big part of our approach.

Tim Fisher: So I want to move out now a little bit and talk about where all headed. What's on the horizon? I'll just ask you straight up, where do you think Scoro's AI journey is headed?

Harv Nagra: Yeah I think we've been really investing in Eli and MCP this year. Like I was saying, that was our big focus. We didn't wanna stick an language generator or text generator into our product.

It was really about saying we already have all this brilliant data on our projects and our clients and all that, not our clients, but your clients like if you're a user, for example. And we were the first product PSA platform to launch MCP support this autumn as well. So I think that's something we're really proud of. But I think what we really wanna do is build out Eli's capabilities so it can do anything a user can do.

Like I was saying earlier, we're already expanding the capability week by week literally. But on top of that, just getting it to be so capable that you could ask it to do anything, and it could do that as long as you could do that. And so some of that stuff might include doing the voice capability, for example, and things like that.

But a lot of our customers, like I said, are also giving us inspiration for things that they want to see because they've been testing this. One thing, I think if I'm giving you a real preview about what we're looking at, a little bit down the road. It's hopefully not too far down the road, is to give it even more capability so you can tell it more about your business and your industry and your niche, and so it has that additional context.

So I think that's even more powerful because it's not just looking at your dataset, but it knows the kind of business. And your specific nuances that you like your, you know, your quotes built out this way, or your clients need this and that kind of thing. So I think that's where it's gonna become super tailored to your business and be even more indispensable.

Tim Fisher: That would be amazing. Yes. So I think you answered this question just now, so maybe I'll like push you a little harder for one other example. But if you think about all the things that your customers do, you know, within all of their organizations, like if there's one really specific thing, like one feature, something that Scoro doesn't do right now.

As specific as you can think of, which again, might be like asking you to dig into your roadmap, which might not be appropriate, but what might that be? Just, I'm trying to get people excited about what might be coming next in like a very specific way.

Harv Nagra: Maybe I'll tell you what I would love to see as a former producer, but also what I will say is some of the stuff that like, you know, people have been prompting us on is like things like automating quote creation based on similar projects in the past.

Or the fact that this client has a bad habit and they're a pain in the butt. So analyzing that, giving you information on that kind of project. It's great to have quote templates, but those are again, just templates. So say, you know, use this quote template as a base, but based on this client and historic data, like update the pricing based on the scope and that kind of stuff.

All that kind of tedious work, like health checks on projects, setting up invoicing on your projects, creating summaries, and also effectively potentially replacing the API with just the MCP. So that's some of the stuff that's like tedious that is either possible or just about possible right now. But in my view, as a former producer, what I'd love to see is helping me manage my clients better, triaging those incoming client requests.

And telling me if this is in scope or not in scope, and coaching, how to kind of push back on the client, for example, so that we can keep things on track. Guiding that communication and negotiation perhaps, that kind of stuff. So I don't know if even that is kind of a boring answer, but that's the kind of stuff that's not super fun to do.

And I think humans struggle with it because it's awkward to say no to a client and emotions come into it and stuff like that. So if somebody could prompt me on handling all those incoming inquiries and say, okay, yeah, you need to execute that one. So it's been assigned to the task already. This stuff is really new scope, so you should ask for more budget and this is how you should go about it.

And maybe here's the email. Are you ready to send it? I think that would be super cool to see.

Tim Fisher: It would be. I, you know, these unsexy things I think are actually by far the most interesting ones. I'll take this over any sort of crazy AI video any day. And it's funny hearing you talk about all this, like the way that you're describing these cool things that you'd like to see are things that we all know LLMs are really great at because we have interactions like that with ChatGPT or Claude all the time.

The missing piece is all of that business data that is inside of Scoro or unfortunately for most people in 15 different systems. So this is a really cool way to bring it all together and maybe do something a little more productive than some of the silly things we use AI for most of the time. Okay, so I, this is a good transition to a nice big last question that I like to ask people in different ways.

So like, how do you see the role of the project manager evolving as all of this happens? Because a lot of the things that you're describing are parts of a project manager's job as parts of people's jobs. Right now that they do every day. So I know when I answer that question for myself in lots of different areas of the economy I think about all the, you know, the advantages and the leveling up that we all get to do and like strategy and all that sort of thing.

But in your world and the folks you work with, how will this help evolve the, Yeah, the project manager?

Harv Nagra: Yeah. I think, i've said the word orchestrate quite a few times today because that is how I see the tools we've demoed today helping people orchestrate work. And like I was saying earlier, we're already orchestrating work as project managers, but it's very manual. And I posted on LinkedIn today, I think something about a project manager's job is not like an expensive admin person, but that's what it ends up being when you're just buried in copying information and trying to update like a hundred systems all day.

That is not something we need to be doing or being super proud of or passionate about, 'cause nobody really is. Right. So I think the way this is gonna evolve is allowing our systems and our tools like Eli, like MCP to do that stuff so we can do more interesting strategic work or more higher value tasks that we actually enjoy.

Because I don't know anybody that enjoys like just updating Gantt charts and stuff like that. That is a part of the role right now, but it's not the fun part of the role. I think I'm not particularly worried about like AI and these kinds of tools replacing our roles. I think humans always bring nuance and judgment and value and context, and that's always gonna be required.

So these tools are just kind of giving you a more powerful, it's like having a team behind you to do all that stuff. So I think it just, it's gonna be super cool about how much more interesting work we're gonna be able to do and how much more productive as a result of this.

Tim Fisher: Agree. Thank you, Harv.

Becca Banyard: Amazing.

Harv, this has been fantastic. Thank you so much for joining us today and giving us a look at Scoro's AI features. If folks are wanting to explore Scoro a little bit more, where should they go?

Harv Nagra: Yeah, please go to scoro.com. I host a podcast as well, so please subscribe to that. It's an operations podcast called The Handbook. And of course, connect with me on LinkedIn where I talk about kind of operational business maturity, business efficiency, that kind of stuff. It's BLY slash score demo and you can sign up for a trial there.

Becca Banyard: Well, thanks again. And Tim, thank you for being such a great co-host with me today. We're gonna wrap things up, but have a great rest of your day and we will see you at the next future of AI in project management session. Take care!