AI in Project Management: Hype vs Reality in 2025
Watch the video below to discover AI's true role and benefits in modern project management.
Introduction
In the fast-paced world of project management, AI claims abound. Emanuela Giangregorio’s webinar cuts through the noise, showing AI’s tangible benefits today. Understand how AI can streamline your project processes and enhance collaboration.
Video
Access the presentation here presentation, tune in to the audio version, or read the full transcript.
About the speaker
With over two decades in project management, Emanuela Giangregorio excels in training and coaching. Her expertise and innovative approaches make complex concepts accessible. Her sessions inspire professionals worldwide to achieve continuous improvement.
Transcript
Here’s the full transcript of the webinar.
00:00:00 Yassin Abbas: Hi Emanuela.
00:00:02 Emanuela Giangregorio: Hello.
00:00:03 Yassin Abbas: Yeah. Welcome everyone, I hope you are well.
00:00:10 Yassin Abbas: Yeah. Hi, James.
00:00:14 Yassin Abbas: Yeah, in facts thanks for joining us today.
00:00:17 Yassin Abbas: So. yeah, it’s really nice to see. Well, that’s a very good number of participants today. Thank you so much for joining us.
00:00:30 Yassin Abbas: So, welcome everyone. Today’s webinar in AI, the specific subject for today is the ‘AI in Project Management: Hype vs Reality’. My name is Yassin and I’m excited to be hosting this session alongside an expert in the field. Our presenter for today, Emmanuel, has over 20 years of experience in project management. She is a trainer, she’s coach, author, thought leader who has helped thousands of professionals worldwide, she has a tonne of making complex topics, simple and practical as well, and today she will help us separate the hype from reality when it comes to AI in Project Management, Emanuela your team.
00:01:30 Emanuela Giangregorio: Thank you, Yassin. Thanks for having me here and also thank you to everybody that’s joined and everyone’s really busy. So, I appreciate you taking your time, hello to those that said hi in the chat box and everyone else. Good morning, good afternoon, and perhaps good evening to some as well. So last year was a bit of a roller coaster ride for many of us into AI things. Up and down of new technologies being sort of arriving, we haven’t get used how to use each time I get used to using a version of ChatGPT there’s a new version or an AI software tool that launched new AI systems and it’s been fantastic. As for some of us, the writers thrilling others, it’s been a little bit scary. I think a lot of people, from what I’ve seen, they’ve decided not to get on the ride. They stay on the cute little carousel, which is maybe not using AI properly in projects, but just playing around with tools like ChatGPT to make recipes or recommend holiday itineraries. And even so, there are still some people that are staying away from AI, believe it or not, in 2025 now yeah. So, 2024 was fantastic, 2025 we arrived with more in AI as well. So, as you know things like AI agents have become really popular. If you look at these companies and I’m showing on the screen here, they span various industries. We have large global blue-chip companies in manufacturing, in pharmaceuticals, in insurance, GlobalPR, and comms agencies down to companies or organisations that are based in the UK and part of the UK Government, and we also have Qatar Foundation.
00:03:15 Emanuela Giangregorio: Now actually these organisations are some of the examples of my clients. So, what I’m going to be sharing with you today in this hour that we have together is my real-world practical experience from what I’ve seen regarding AI adoption in projects specifically. I know there are a lot of stats out there, there’s a lot of stuff on LinkedIn, but really what I want to share with you and then also exchange of your questions and some thoughts with you as well on what is the actual reality here in 2025. So, a little bit about me, in case you’re wondering why my accent doesn’t match my name. I’m South African Italian; I was born in South Africa to a wonderful Italian father and a South African mother. I grew up there and I moved over to the UK more than 20 years ago. I live on the South Coast in a place called East Sussex if anyone knows the UK. I’m a project management consultant and coach and work around the world, have done for many years, as Yassin said, over 20 years. So, my field pretty much is in project management and of course more recently a strong interest in AI. So, if you’re interested in my work, you can find my books on Amazon, the online courses that I run in AI on my website, and feel free to follow me on LinkedIn.
00:04:32 Emanuela Giangregorio: But less about me and more about what we’re doing today. So is AI in project management, hype or is a reality here February 2025. I’m also going to be talking about what you need to do to enable ethical, efficient and effective use of AI in projects. So also letting you know about Q&A, I think it’s dull for you to have to listen to a whole session and wait for the Q&A until the very end. So, what I’m going to do is pause halfway through and take any questions that you have up until then. Yassin will be my copilots today, so you’ll be looking at any of the questions in the chat box and then you can flag up those questions with me when we pause halfway. So please do make a note of any questions you have as we go along and then also, we’ll have some Q&A at the very end as well. Now some of you might have seen this prediction by Gartner. As you may know, Gartner is a research organisation specialising in technology research and their research team have predicted that by 2030, 80% of Project Management tasks will be run by AI, 80%. So those of you that Project Managers, think about everything you do and think that by 2030 there’s a possibility that 80% all your tasks that you do in projects will be run by AI.
00:06:03 Emanuela Giangregorio: Now back to real world and what I’ve seen to date. Certainly, that’s not the evidence I’ve seen right now as in we know we’re close to that, but certainly it is a possibility. But essentially what this prediction is suggesting that within four years. Largely, project management tasks will be done by AI that’s using 20% of the work that what we do, which is actually would be great for me as a Project Manager. It would be fantastic if 80% of the work can be done by AI, because that absolutely frees me to focus more on things like stakeholder management, better communication, relationship building and all the important things that we need to do. Now what I’m going to do with you today is 2 key things. Talk about where are we now? The truth about AI adoption in project currently in my own practical experience with my clients and then I also want to share how to get to where Gartner says we’re going. There are several organisations like these you can see on the screen here you’re familiar with most of these brands, if not all of them. These are examples of early innovators in AI. For more than 10 years, they have actually been at the forefront of AI innovation. All of them use AI in their projects and some of them also have AI-assisted or AI-powered project management tools like Oracle for example. If you are working for one of these organisations or similar organisations, it’s very likely that you are part of a project team then that has high levels of AI adoption in projects.
00:07:44 Emanuela Giangregorio: But not everybody is lucky to be working for these types of organisations where we have high AI adoption, so perhaps now is a good time Yassin to run our pole. I’m interested to see with everyone here. What is your current usage of AI in your project? I’m not talking about AI in general like using ChatGPT to come up with ideas for non-project things. But the questions here are specifically in projects. Thank you.
00:08:32 Emanuela Giangregorio: Right, so I’m seeing quite a lot so, at the moment we have mostly are saying occasionally. Secondly, not yet regularly not applicable. A lot of you are using ChatGPT and Copilot, some of you none at the moment.
00:09:03 Emanuela Giangregorio: OK, I think we have all our results in the poll, Yassin.
00:09:08 Emanuela Giangregorio: Thank you and I can share the results on the screen. So, let’s see if I can share all results, how does this work?
00:09:21 Emanuela Giangregorio: Yassin, can you see the results on your screen as a user?
00:09:25 Emanuela Giangregorio: OK, fantastic. Thank you, just wanted to make, so as you can see, amongst yourselves, are you currently using AI-assistance in your projects, 37 1/2%, not yet, 40% occasionally, so using occasional tools. Do you review regularly, which is great, and then seven of you are not applicable because you’re not working in projects, which is fine. And then the second question is which AI-powered tools are you currently using? And we’ve got ChatGPT, followed by Copilot, some of you are using Gemini. Four of you are using AI-Powered Project Management software tools, which is great, and then again some of you not at the moment. OK, I’m going to finish and close that poll, this is interesting actually, because what I’ve just seen here with the participants in this webinar pretty much mirrors what I’ve experienced in my client base. And actually, if we ran this poll, probably three months’ time, we’ll probably see those numbers in AI adoption and AI usage increasing in projects because again, there’s sort of an increasing interest and more and more information about it.
00:10:30 Emanuela Giangregorio: So where are we now in February 2025? I want to keep this as current as possible. So, what I’ve done is I’ve kind of looked back at my client base and those that I’ve worked with in the last year, I often kind of take these sort of polls and have discussions with them, including one this very week. So, February 2025, where are we now? As you can see in the slide that I’m sharing, I’m going to split my comments looking at project management generally and then AI-Assisted Project Management specifically. So, project management generally, many individuals that I work with or that I’ve worked with at my client base have project management certificates. In fact, some of them have more paperwork than I do, but they still don’t know how to practically plan and manage projects. So, we’re talking about AI adoption and AI usage in projects but just rewind a little bit to be a good user of AI in project. We need to be good at project management and so I’m still finding that a lot of people still don’t know how to practically plan and manage projects. Despite the paperwork that they’ve managed to collect around this not so long ago. One of these large online booking organisations where you can book accommodation and slides through them got in touch with me and said one of our teams has been qualified in Six Sigma. There are Six Sigma black belts, they still are struggling to practically plan and manage projects. And what I discovered was it’s really because they keep lost in the theory of the methodology that don’t actually understand how to apply the spirit of the method, so I’m still seeing evidence of this scenario. Also, there seems to be still low organisation, low to medium organisation-wide project management maturity and what I mean by maturity is at the lowest level of maturity is an ad hoc approach to projects. Everyone’s doing their own thing and as you get to higher levels of maturity, there’s a standard project management framework or process in the organisation. Project management is part of a culture they are using more elegant tools to assist in project management tools that are more time saving and so still more and more particularly you know, even now this year in the last two months, the new engagements that have come along, I always start any engagement with a discovery call to understand what they need. And I’ll talk about sort of, do they have any standard processes, do they have a PMO? Are they using any tools? Never mind AI tools but what tools are they using?
00:13:07 Emanuela Giangregorio: And I’m still finding low levels of organisation, wide project management maturity. Thirdly, talking about tools, many organisations are using very basic tools to help them administratively plan and manage their project. So, a lot are still relying heavily on Excel or Google Sheets. Now Excel has its place, I’m not against Excel at all but when I work with some of these project teams that are using this spreadsheet. I can see that are spending a huge amount of time doing the administration on their project where that could be saved and used instead on more important things like stakeholder management and so on. So, I always ask why? Why are you using these tools? Strangely enough, in some cases they’re not aware that actually you can have some more elegant tools with free versions and also for some of the better versions of the software tools. The organisations don’t have the budget for licences and so in some cases, project individuals and teams have their hands tied in terms of what have access too. OK, so that’s the current status, right until now regarding project management and project management maturity generally. What about AI-assisted project management? Many PMO functions are still not taking the lead in AI adoption and oversight. Every time I engage a PMO function, that’s one of the things I ask them is how are you using AI in your project? Are you kind of overseeing in your project teams? Is it left up to each individual and in most cases it’s up to individuals or individual teams to decide how they want to use it. They’re not getting any leadership from their PMO functions, certainly for those organisations that do have PMO.
00:14:56 Emanuela Giangregorio: Very importantly, the second thing I’m finding is organisations are not keeping project data. What I mean by project data, let’s start with the end lessons learnt, the lessons learnt, or project review discussions are wealth of wisdom about what happened in the project, and we all know the purpose of that discussion is to help future similar projects not make the same mistakes and take advantage of the good things that they did their project. Most of the organisations across my client base don’t keep this information. Some of them don’t even have a lessons learned or project review at the end, and those that do not store this information. So just in project management, generally people don’t start projects with looking at previous lessons learnt reviews and those that do have the access to that don’t actually bring it into their AI tools. So, an AI tool is only as good as the data you’re given, so the type of data that should be available is previous lessons learned reviews, previous risk, log issues logs, scope change logs, baseline project plans, and then what actually transpired in reality. Alright, so the fact that the data doesn’t exist means that even if they are using AI tools, they’re not able to make the best use of those tools.
00:16:14 Emanuela Giangregorio: I also see that people dabble and fail with AI in project and then become AI sceptics. So, what I mean by that is they messed about with tools not having training. They are using tools on their own, so these kind of aren’t used across the team etc. And then when it seems to be too difficult, they just say. It’s not going to work, let’s stick with our old spreadsheets and our old ways of working and then they lost in that sort of process. And then finally, the last point I want to share with you on this slide is that in my client base, less than 5% of people are using AI in project management. So, this is the current state of where we are now, great to see that some of you here are using AI tools in project management. You can tell me later if you feel these are efficient and effective uses of AI tools. But it’s not just about the tools, it’s about how AI is used so that we can drive efficiency and success and allow project managers to focus on other important things that often they don’t have a chance focus on. So, summarising what I’ve just said in the previous. Disparate project management tools and data, disparate meaning all over the place, right? So, some teams are using Excel or Google Sheets, others are using a tool like Asana or the Planner app in teams, etcetera. So, been used and data all over the place, if it exists in fact so, despite project management tools and data. Together work now desperate attempts at AI implementation and this bought looking like is we need to adopt AI. Let’s get a tool, let’s put it and make it work, no strategy in place also, as I alluded to lack of human capability. So, and this is not just at project manager level, project sponsors should know how to strategically oversee AI-assisted projects. People around project manage should know how they can support in the project using AI tool.
00:18:29 Emanuela Giangregorio: And essentially this lack of human capability, along with the fact that we have a lack of a strategy and this disparate attempt at AI implementation and the lack of tools and data, has led to a situation where we have general AI underutilisation in projects. Or inefficient and ineffective AI utilisation, so it is being used but it’s not being used well and it’s actually taking more time than it should be. Now remember our focus here is in projects, those client examples that I shared with you many in fact most of them are using AI in the operation. For example, in the pharmaceutical organisations, they rely heavily on AI tools for early drug discovery and those sorts of things. The insurance industry example I shared with you there, they are using AI tools for fraud detection and for automated underwriting. So, organisations are using AI tools but when it comes to in project management, this is something that we find is certainly lacking. So now the time I’d like to kind of pause with a bit of questions, if there are any. Yassin, I don’t know if we have any questions in the box yet. Can you let me know?
00:19:56 Yassin Abbas: I’m sorry. Yeah, not, not yet, but I’m sure that.
00:20:00 Emanuela Giangregorio: Can you upload that survey for us to download, please? Are you talking about the stats that we did? I think you talking about the survey from the poll that would be fine. Wouldn’t it be Yassin I think because it’s confidential?
00:20:14 Yassin Abbas: We can share, we can share the story of that survey.
00:20:18 Emanuela Giangregorio: Yeah. And you’re going to get access too, you’ll get the webinar after session as well.
00:20:25 Emanuela Giangregorio: So, you’ll get the recording, which you can share with colleagues too.
00:20:27 Yassin Abbas: Actually, Ingrid has a has shared a interesting question. Is there a tool you recommend other than Excel?
00:20:37 Emanuela Giangregorio: You’ll see on the slide that I’m going to share with you soon. Who’s that from, Ingrid?
00:20:42 Yassin Abbas: Yes.
00:20:43 Emanuela Giangregorio: Hi Ingrid. So, you know what? That’s not an uncommon question, Ingrid. People often ask me which tool do you recommend? And soon I’m going to share you a slide with you that shows all the AI-powered tools. There are so many tools out there, I tend to use the tools that my clients use. And also, you can imagine somebody like myself as an external consultant, I couldn’t possibly be an expert in all of and also, couldn’t have licences for all of them. So, for some of them actually I’ve got three different e-mail addresses, just that I can keep on using the free versions. But Ingrid, since you asked me, I will tell you my top tools that I liked, and I enjoy working with these are the AI-powered tools. They have free versions that have limited AI-assistance, and then obviously you have the paid versions of these tools in no particular order. Asana is a tool I really like working with, Notion is great, Wrike, Smartsheet, and Taskade. I’m giving to give you 5 and you’ll see them on the slide that I’m going to share with you as well later on in this talk. But yeah, so those, why do I like them? They’ve got a great interface, reasonable price point, intuitive and easy to use. And certainly, my clients that are using those tools have actually adopted them and you know teams are using them very effectively as well. But you know that’s certainly the expense that I’ve had. There are other tools out there as well, which and I’m going to be talking about tool selection as well soon.
00:22:11 Yassin Abbas: David also has a question.
00:22:16 Yassin Abbas: So, everybody is talking about the problem and how AI can, you know, solve the problem. But what is the solution? What is the tool that you know would be best for me? Which also kind of collates with David’s question about best practises.
00:22:37 Emanuela Giangregorio: So best practice terms of how to get past this current situation?
00:22:45 Yassin Abbas: I think let’s answer David’s question about the solution? Which tools that you may recommend and how to use them?
00:22:55 Emanuela Giangregorio: Yeah. OK. So, I’m going to get past the tools and let’s continue then with the presentation because I’m going to go from here to how do we get closer to what Gartner is suggesting, right? I know people love the tools and it’s all about which software tool, but that’s part of the solution and we can talk more about that. Let’s go from here into the solution in terms of the current situation and then we can pick up any questions that perhaps we have missed out. So, can I leave you with the questions in the in the chat box there, Yassin? Yeah, thank you. I want to make sure that I don’t miss out anybody’s questions at all. And I just want to make sure also keep my eye on the time. So, we’d yeah, we’re doing good. So, we’ve got plenty of time for questions, that’s great. OK, so what are some of the solutions? How do we get to where Gartner says we’re going because I that’s a place to be if that’s where we’re going, get on board or not? Let’s decide. So, working backwards you need the AI-powered software tools to do the 80% if they are saying 80% of what we do is project is going to be done by AI, then it’s going to be tool driven and it could be multiple tools as well right? Bearing in mind if you don’t know about AI agents, I suggest you learn about AI agents quickly. You will discover that AI agents will come more and more into play, and they can do multiple automated tasks. So, this situation where 80% of our work is going to be going to be done through AI will largely be through authentic AI but in the end, we still need the tools right.
00:24:26 Emanuela Giangregorio: For the tools to work, they need data, so it’s all very well going out and getting a great tool. But if they don’t have data to work with then the tool is not going to be as efficient or effective as it could be and won’t deliver the value that we’re hoping for. And then for the above to be in place, we need capable humans to make it happen. So, a simple triangle that I like to use for ethical, efficient and effective human AI project collaboration, we need capable humans. We need the data which is, you know, complete, accurate and available to the tools and we need the AI-powered tools to support us. And so, what I want to do is just step into each of these 3 aspects. If you follow any of the stuff I say on LinkedIn or on my website, you’ll see me say this quite a few times. ‘Success hinges on our ability to masterfully blend our wonderful human expertise, experience, and wisdom with AI capabilities. The key isn’t to be driven by AI, but to drive success with AI as an assistant.’ Terminology is very important, there’s a lot out there about AI-driven project management and AI-driven organisations, but I think we need to be careful when we use terms like this. If certainly there’s no context around that because people, if they have the sense that things are AI-driven, then we run into the difficulty where we’re delegating into AI.
00:25:55 Emanuela Giangregorio: And let’s keep the discussion within project, the project manager’s actually not leading the activity. So really, I like to focus on the term AI-assisted rather than AI-driven. AI-assisted means therefore that project teams and related roles need to have the capabilities to be able to establish what the AI is giving us. Is it accurate? Is it reasonable and to be able to coach the AI tools to improve over time? So yeah, AI-assisted rather than AI-driven. The other thing is I’ve written a framework for AI-assisted Project Management, which is very much about helping project team-related roles. Even governance functions ensure that we can adopt this in our project processes alongside chosen methodologies like PRINCE2 or approaches like Agile and also the Project Management Institute, project processes. So capable humans, first we need some sort of AI-assisted projects strategy. Typically, what would this look like at sort of the top organisational level? We need to see some sort of AI adoption strategy across the organisation. What does it mean for people, process and technology and then part of that we should have an AI-assisted project strategy? It’s useful if it’s top-down. However, if you don’t have that top-down strategy, it doesn’t stop you from being an effective AI-assisted project manager.
00:27:27 Emanuela Giangregorio: The framework governing ethical, efficient and effective human-AI collaboration frameworks are useful. It doesn’t have to be the one that I wrote, but frameworks are useful because it does assist project teams use AI properly in their projects. It helps those that are taking a strategic leadership role provide assurance to the board and to other functions regarding responsible use of AI, as AI adoption continues and as the organisation data becomes available to these AI tools. And also, what we will need therefore is some emerging, you might have noticed the emergence of the Chief AI Officer (CAIO) or the Chief Data and AI Officer. This is a very important role at the C level of the organisation, and they have an important role to play in strategically guiding AI adoption in projects. Projects are the major vehicle for delivering the organisation strategic objectives if you think about it. The organisation has its strategy, its strategic priorities, the execution of those strategic priorities are often through projects. So, a lot of what we do to enable the organisation is through projects and therefore it makes sense that roles like the Chief AI Officer (CAIO) and related roles take a strong interest in providing some sort of strategic guidance around AI-assisted project management. And also, we need roles like the AI project coordinator on bigger projects so they can assist with the usage of AI tools. Data custodians and data coordinators to make the data available to us and then of course, training is important. So, all these roles that are going to help us drive successful projects with AI systems need to know how to strategically guide projects, those that are operationally working on projects. They need to know how to make the best use of the tools with the data that they have at their disposal.
00:29:32 Emanuela Giangregorio: Just looking at this dimension capable humans, you can start to see a lot of work to be done. What about data? So, we need overarching data strategies in the organisation and part of it would include a project data strategy. I mentioned the Chief AI Officer (CAIO) so if you have a look on LinkedIn or on Google you will find job functions for Chief Data and AI Officer and that’s where the data component would be included. In some organisations they split them out and in many organisations the role doesn’t exist yet. But essentially, we need some sort of overarching data strategy including a strategy for project data as well. Therefore, data owners and data custodians and then we need to operationally start collecting, cleaning and securely centralising project data which we can make available to tools. So, for organisations that have already had some sort of discipline around collecting project data we’re talking about lessons learned, blogs and risk logs and all these different things. There should be some sort of effort to collect that data because there’s a lot of wisdom in that data. Clean it up, make it available to AI tools, and then a day forward approach for organisations that don’t have their data, just follow a day forward approach. So, from now on, the projects that we run going forward, this is how we want to start collecting this data so that the AI and use them. And therefore, we can benefit from better predictive analytics and automation and prediction and so on. With their data available, then we need to provide secure access paths for the tools to access the project data.
00:31:21 Emanuela Giangregorio: The tools that many of you are interested in, so this is where things go a bit wrong sometimes, and I always say don’t just go out and buy a random tool. Somebody on a went on a webinar said they like Notion or Taskade or something, let’s go get it. Some of my clients are using tools and I ask them always just last week, in fact they were using Monday.com, which is a great tool by the way. A higher price point than some but it’s an OK tool and I asked them why did you choose Monday.com? Well, we saw, you know, some of the colleagues saw these YouTube ads and it looked great. And so, we looked at the demo and we got it. Now that’s OK and they might be lucky, it might be fit for purpose, but that’s not purposeful tool selection. Really what I would suggest is first do write a requirement specification. Figure out what you need from the tool. What does it need to do? And it will vary across different industries. So, when I share with you soon on the screen these different types of AI tools, some of them are more useful or designed for certain industries. Some of them are tailored for bigger organisations, others for more agile use cases and so on. So be very clear on the requirement specification. What do we need from the tool in terms of features and functionality in terms of your team composition, the scale of the organisation, is it an enterprise solution or just for a small team and also things around data security and also the future proofing capability of the tool. So, write a requirement specification, then do some research, select a short list of tools and test those tools as well.
00:33:04 Emanuela Giangregorio: So finally, I think the slide has changed. Yes, it has I think there’s about 15 tools on this slide that I’m sharing with you now. This is not even all the tools they are, but I’ve chosen 15 tools. These are examples of AI-powered project management software tools. How do you choose one? Do you choose 1 based on a recommendation? Do you choose 1 based on a requirement specification? I would both right and you know, listen to your recommendations, read reviews about these tools, but do be very clear about what your requirements are and some of the constraints that perhaps your organisation has regarding budget and so on and then choose the one that is the best for your organisation. For example, you’ll see on the bottom left there there’s a tool called Forecast, this one here. They are really saying if you look at their website, they’re targeting larger organisations with much higher usage numbers of the tool. The tool actually Forecast is one of the first tools, the first project management tool that was built with AI from scratch. A lot of these other tools like Monday, Asana, Trello, etc. Were a commonplace project management tools and then more recently they’ve built in AI capabilities. Some of these tools that brought in the AI capabilities have kind of brought in OpenAI, GPT models and then they have to sort of modify them. But tools like Forecast for example, is one of the first tools that was actually built from scratch for large complex projects and has the AI capability built in but again, it’s not suitable for all organisations.
00:34:44 Emanuela Giangregorio: Those of you that are interested in finding where you can compare and shortlist tools, these are the two websites I recommend. You might be familiar with them or not, but again Capterra and G2 Crowd. So, let’s just say you want to figure out what tool I should get maybe you’ve listened to what we’ve said on the webinar here and also you might do some of your own research, and perhaps you end up with short list of five. You can go to Capterra and to G2 Crowd and then compare those five tools. Read the reviews and see to what extent they satisfy your needs and maybe from there you can short this that to two tools and then get some demos of those tools and then finally make a decision. I’m well aware that some of the people here has little to no decision authority in your organisation, so you can’t like affect what the organisation does across the team or the broader organisation. So, it’s just for you to choose what works for you and then also some of you here might have decision authority. So, for those of you that do have decision authority and can play a role in selecting the right tool for the enterprise or the department or the team, do it right from the start. Start with a requirement specification, do the research, select and test, then run a pilot, and then finally evaluate if the tool works. And if it does, then roll it out and recommend to the broader organisation that this would be the best one for you.
00:36:14 Emanuela Giangregorio: The reason I’m sharing a screen a slide, at least when we go back here. Where the robots vacuum cleaner on it. This is my Christmas present from my sister, normally we don’t give Christmas presents. She’s basically Brisbane, Australia and in December, this box arrived at my door, and I said to the Amazon person like this is not for me. This is must be a mistake, he said Well, it’s your name I know you by now because he delivers a lot. And he said it’s definitely for you. And I opened this box, and I saw this robot vacuum cleaner. I thought, my God I don’t need this like, my place is not that big. When I started using it, I realised, my gosh absolutely do need and I love it. That reason I’m sharing this with you now is when I first got it, I just get excited about things and I just accepted it and got it going and it was doing an OK job. And I to read the instructions properly and I watched some videos from the manufacturers of the product to see how you can get the most use out of it and actually what I learned was I was using less than 50% of the capability of this amazing robot vacuum cleaner. Once I learned how to use it properly, I was using it to its fullest extent. OK, so this is the key thing when it comes to the tools. It’s not only about getting the tools in place, but also very much about ensuring that we are able to train users to make the best use of the tools.
00:37:37 Emanuela Giangregorio: Now I also know from working across my client base that sometimes organisations are often times organisations are in the habit of making tools available. And not providing training for those tools. So, if your organisation doesn’t provide the training, don’t just hack it and make you know, see if you can figure out, they are a host of useful tutorials on the vendor’s websites, on YouTube, et cetera, on how to make the best use of these tools. I would suggest whatever you’re using, even if you’re using Google Sheets or Excel or Asana or any of these fabulous tools, spend some time on the resources that are available to learn how to make the best use of the tool. One hour invested in learning the tool is going to save you heaps of time and turn you into more of a project management wizard where some of these AI-assisted tools. Let’s move over now to road or ride ahead. Where are we now? If from what I’ve seen, we generally have low AI adoption in projects and low capability to use AI properly. In project management, where do we go? Well, different roads to take. Some can stay, or some will choose to stay where we are and I don’t think the wait and see is a good game to play because the longer organisations leave this, the sooner their competitors will beat them to the market with more efficiently delivered projects. Take this down from the organisation to the individual, the longer individuals leave it to become proficient in AI usage in project management.
00:39:27 Emanuela Giangregorio: The sooner other professionals are going to be competitors to you for the same job and I don’t want this to be scaremongering at all. But I really feel like this option of waits and see is not a good option for most business professionals. The other option is purposeless AI adoption in projects purposeless meaning, let’s just get a tool, put it in place and hopefully it works. We might be lucky, and it might work but it might not be sustainable. And really to truly drive project success with AI-assistance in a way that is explainable that where we can actually give assurance to governance functions that the usage of AI is responsible, the data is secure and protected. We then need to follow a path where we do this properly. So, what do we need to do? Strategic AI adoption’s gonna require us to intelligently select the tools, ensure we have strategies in place for data. That means the data needs to be quality data and most importantly, we need capable project managers and related roles. But as I said earlier, not only project managers, I really feel like roles people that take on the role of a project sponsor support functions like AI coordinators, data owners, et cetera. Chief AI officer (CAIO) would benefit from becoming skilled in this area to know how to properly strategically oversee AI-assisted project and for those that are operationally involved for them to make the best use of these tools.
00:41:17 Emanuela Giangregorio: So, AI and project management is not hype, it’s here and it’s going to continue to be an important aspect to bring into our projects. Also, AI project management is currently underutilised, it’s certainly what I’ve seen and perhaps again I’ll be interested to know from your perspective what you feel there. But I also feel that now is the time if people haven’t done this yet. Now is the time for individuals and organisations to decide, do they wait until they have time or something else changes? Or do they lead? And in fact, now can still be the time to lead because most people haven’t yet adopted it. In other words, AI adoption is still low, anyone that kind of gets into this early will still be leading in the AI revolution. So, it’s a choice and I know it’s not a simple choice because there are constraints like budget constraints in organisations, time constraints, in terms of resources availability and capacity to kind of work on these things. And so, if we can’t do it sort of top-down full scale properly, we then can maybe bring this into our own world. So, if I’m in an organisation that perhaps is way behind in all of this, what can I do for myself? Well, as a person who’s practising in project management, I want to then make sure that I am very familiar with common AI tools, for example what they can do, understand some of the ethical challenges, know about some of the use cases? How AI tools can be used in projects? So, if I don’t have access to one of those cool tools, how can I use some of the freely available tools like Google Gemini and Microsoft Copilot or even the ChatGPT models to help us in projects. So, if we can understand how to use those and build AI literacy in project that’s going to get a long way from just dabbling and talking about it to actually using it and showcasing how we can use it in our projects going forward. So that’s it from me in terms of some of the talk that I want to have here. I think Yassin over to you, you want to do first do a survey and then after this we’re going to spend the rest of the time on some further Q&A but first over to you, Yassin.
00:43:35 Yassin Abbas: Yeah. Thanks so much. I would like to share this feedback with you guys, if you don’t mind take a moment or two to complete it. Thank you so much.
00:46:19 Emanuela Giangregorio: How are we doing Yassin?
00:46:21 Yassin Abbas: Yeah, almost there.
00:46:36 Yassin Abbas: We have some interesting questions.
00:46:39 Emanuela Giangregorio: Right. Oh right, tell me when we’re ready.
00:46:42 Yassin Abbas: We have some interesting questions.
00:46:51 Yassin Abbas: We’ve got events and feedback that we have, a human resources and organisation development specialist, and they are supporting this. So yeah, that’s a very good sign. Thank you.
00:47:27 Emanuela Giangregorio: I’ll start at the bottom looking at some of the comments while you finish up on that poll, if you don’t mind Yassin and then you could just let me when you’re done, right? But I’m just looking here, my job title is associated safety and learning lead at NHS Resolution. I missed this question, I’ll come back to that I’m not sure what you missed the Ingrid. Katrina, I use Copilot for minutes, you know Copilot is a great tool, Katrina. So, you know, one of the biggest time oysters in or time, things that take a lot of time in projects. Any meetings in general is having to kind of record the actions in meetings and Copilot is great to transcribe the entire meeting and then also from there distil the key actions that come out of it. So, it’s kind of saving 80% of your time as you’ll know and of course you still need to have a look at it and kind of add anything that’s missing. So yeah, I think Copilot is fantastic.
00:48:20 Emanuela Giangregorio: And Sam, you are asking about AI tools, so yeah, a lot of the, this for Sam who is asking about, I know Katrina replied but Sam was asking about AI tools for meeting minutes and people’s experience with them. So, thanks for applying about Copilot, most of popular web meeting platforms now have some sort of AI tools embedded that will transcribe the meeting. So, if you guys are using Zoom and Webex for example, they have now tools that will transcribe those, but I would say out of those Copilot is more mature in terms of its ability to not only transcribe the meeting but actually extract the key actions from that.
00:49:13 Yassin Abbas: Yep. Thank you, thanks so much for sharing your feedback.
00:49:18 Yassin Abbas: We have a very interesting question, a question from about the AI integration. So, the question is basically is about. Is there an AI tool that can be integrated into existing software, specifically for the project management software?
00:49:45 Emanuela Giangregorio: You mean say for example, if you have a project management software tool, can you integrate the tool into that existing software? Right so for example, if I’ve got Microsoft Project is in AI tool I can integrate with that.
00:50:02 Yassin Abbas: Yeah, it seems like.
00:50:06 Emanuela Giangregorio: So, most of the popular project management tools have a free version with very little AI integration. Some of them have a few bit of AI-assistance but most of them the free version is fairly basic and then as you go up the paid versions, there’s more and more AI integration. So, for example Asana, you know to the next level upgrade version, the AI system will be able to for example, let’s just say I want to build a website that’s my project. I can tell it that the project is about building a website, it will recommend a list of tasks and dependencies between those tasks, right? So, the point I want to make to answer your question is most of the popular project management tools, certainly the ones that are more mature in the market have actually got the AI systems built into those. Perhaps it would be interesting for you to put in the chat box the of the you’re using. And then I can answer your question better if we have time, Yassin just let me know.
00:51:02 Yassin Abbas: Sure. Another question, what form can AI integration take in a project? So how do you see which tool to support which point in a project in projects? If you have any specific examples?
00:51:19 Emanuela Giangregorio: Right. OK. So, let’s look at the project life cycle. Let’s just talk about the initiate phase or that first phase of the project where we have an idea for the project. Now typically that phase is either just formalised or justified through maybe sometimes it’s just a simple discussion in a meeting, but in some cases, it needs to be formalised or justified through a project mandate or even a full-blown business case right now. Probably wouldn’t a software tool like some of those that drive the planning and monitoring of projects there, you could use a Gen AI type of tool, you could use ChatGPT, your organisations in-house Enterprise GPT. Some of you might have your own in-house GPT that would be a good tool to use for helping you write a comprehensive and compelling business case right. So, let’s move off the initiate phase, let’s go into the planning or define phase of the project. That’s where we need to put some more meat on the bones of the project, plan up the project by setting out the clear objectives, scope of work, the constraints, roles and responsibilities and then also build a project plan. So, some of the things around building your project charter or your project initiation document, again as useful to use a tool like Copilot, Gemini, ChatGPT or your organisations in-house GPT, Enterprise GPT to help you create those documents that can help you then establish the project chart or the project initiation document. When it comes into the planning, meaning the timeline so creating the project timelines and from there on that’s where some of these tools come onto their own. So, tools like those that are shared with you on the screen will be able to then help you set up your project and many of them, like Asana and others right Notion, Taskade. In fact, if you look at some of the demos for Taskade on YouTube, you’ll actually you can see really like a real good example of how these tools can actually automate a lot of things. So, Taskade for example has a lot of AI agents built in, so again you’ll tell the tool the project is about building a website or optimising this business process. And it will then generate a list of tasks and subtasks, it will recommend dependencies between those tasks.
00:53:36 Emanuela Giangregorio: The example I’m sharing with you now is if we don’t even have previous project data, so it’s kind of just flying solo without any previous project data. Then you can obviously go into the tool and make some changes. If you give it a start date or map out the timelines or create some sort of Kanban board for you and recommend the dates and durations. And of course you can then fine-tune it based on the constraints. If these tools have access to pass project data, they will then be able to say OK, we know that these projects with those resources, they overestimated what they could do, things actually slipped as they will build in and more, more realistic time frames. So, these tools can assist with task generation that can assist with resource allocation that can assist with things like risk assessment, so using predictive analytics they can then do the risk assessment for you. And again, the most important thing is these tools are only as good as the users know how to use them, and they’re only as good as the data given to them, right? So, in other words, how you prompt them and how you describe what you need from them and also any data available, we still need the human in the loop. Therefore, my insistence on project managers who are competent to be able to look at what it’s given to say, actually. Yeah, that makes a lot of sense and let’s use that or let’s make some changes to what the tool has given to us. So, long of answer to a very short question, but I hope they give you some flavour for the types of things these tools can do, and also how they’re through the project lifecycle. And then, of course in the delivery phase, the monitoring and control phase of the project, you then have these tools that can, some of them will actually, you know, will summarise your dashboards for you in terms of project status and also give you heads up on potential new risks. Flag up issues that have maybe been outstanding for longer than two weeks, say et cetera, depending on the parameters. And then when you get to the close those of your project whether it’s an agile project or a non-agile project, you still have to do a final review of the project and all those kind of things come into play then. You know in what I call manual project management where we’ve kept everything on a spreadsheet. If we do a review at the end, we then need to go through all the logs, look at the, you know the issues log and the risk log and the scope change log and the baseline plan and from there we can discuss lessons learned.
00:55:50 Emanuela Giangregorio: In addition to that, we’ll also discuss our stakeholder experiences and so on. But again, we can automate a lot of that as well. Now the maturity of these tools varies and that’s why I always said build a requirement specification. And be very clear on what you need from the tool and also then budget comes into play as well. The more elegant, advanced tools will be at a higher price point, the simpler, less elegant tools will obviously be at a more affordable price point as well.
00:56:21 Yassin Abbas: OK, we have a follow-up regarding the software integration for AI tool into a project management software and to be very specific there are things like DevOps and Jira being integrated into Microsoft Teams and whether there was a case like, for example, using Excel for project plan and ChatGPT assisting and assisting. Yeah, if that makes sense.
00:56:59 Emanuela Giangregorio: If Excel is all you have and you know and you have a very good, you know, your knowledge of Excel etcetera. ChatGPT is absolutely fine in fact, now you can actually attach things like Excel spreadsheets to ChatGPT for it to analyse and it can also create Excel sheets for you as well. And as ChatGPT evolves it will be able to do more for you, so I think if feeling that for at least for the foreseeable future, for the next six months or maybe year, Excel is going to be your main tool for project planning and monitoring. And you want to use ChatGPT as an assistant, I think you absolutely can use that it’s not going to be as elegant as maybe some of the others, but given the time, you know the budget constraint that you may have. And the fact that you actually already know Excel really, really well and then ChatGPT for example, can help you with that as an AI-assistant. And again, we’re only out of time but I would strongly recommend that you therefore focus your learning on using ChatGPT as an AI-assistant in project so that’s what you really want to on learning about. So, go and watch YouTube videos and really be skilled at that and in fact. Some people find Excel easier because I know it already these other tools you can have to learn from scratch. So, if you are Power AI sorry Excel user and or you’re already using them in your organisation in your project you absolutely can use ChatGPT to assist you. And that’s where I would focus my learning, if that’s going to be you.
00:58:37 Emanuela Giangregorio: Yassin, you’re on mute.
00:58:38 Yassin Abbas: Oh, sorry, Yeah, we have I think we have room for one more question, which I think it’s perfectly. Would be ask now before you start your next slide. So, the question is, what skills and knowledge are needed to become an AI project coordinator and how one can qualify for that role?
00:59:05 Emanuela Giangregorio: Thank you for asking and I’m pleased that our last question is about skills and capability, because it’s not only about the tools and I’m glad there was a question about Excel as well because sometimes people focus on the tools, they get a tool, but they haven’t addressed the other part too. So, I think the most important thing is, you know, having the skills. So, first of all to the person that asked the question, be satisfied if you are practising in project management as a project manager or as a project coordinator that you know how to practically plan and manage projects. And I’m not talking about collecting paperwork because it is important. Get the qualifications but have some experience, something I call the Qualified By Experts (QBE) have hands on experience about how to practically plan and manage projects right and then talking about AI-assistant project management, I’m actually sharing a slide on the screen now. June and July, in fact, it’s going to be support Knowledge Train going to be offering two courses. One is the AI-assisted project management navigator course that is all about you getting AI literacy. Just, you know, like, years ago in my day we had to have computer literacy. This is about AI literacy, understanding how to use AI in projects across the project life cycle, regardless of the tools that you’re using. So also understanding things like ethical considerations and the types of skills you need as a project manager. So, navigators for AI literacy and then the champion certification which might change the name might change to AI PMS, but for now it’s the AI system Project Management Champion certification. That’s to help you understand how to use a framework to govern ethical, efficient and effective use of AI across the lifecycle alongside a chosen methodology like Agile, PRINCE2 and so on.
01:00:53 Emanuela Giangregorio: Beyond that, there are other skills that we need then, right? So, more and more I’m seeing my clients, the demand for skills like strategic thinking and decision making becoming essential, stakeholder management, emotional intelligence, these types of skills that actually will really, really need to come into play for project managers and even project coordinators. To act at a higher level, those skills will be essential. So once people have got like they know how to plan and manage projects and know how to use AI in projects, they have a framework to kind of provide the governance. These are the skills need to be sharp as well and I know just the kind of the slides that you can see. So, I’m sharing what’s coming up in terms of the AI PMP also, Knowledge Train has a number of other. Am I going back to my slides here? The Knowledge Train has a number of other course topics as well, so you can see these on the screen, and you can look at these in the slides. When we share these with you but essentially from what I’m saying, it’s like be clear on like maybe where you want to be in the next year and then be really focused on how you need to develop yourself and if those of you that are looking at tools on the you need. And learn how to use those tools. Thank you so much, thank you Yassin, for having me. I know we’ve got a couple of minutes over the time. I appreciate you being here and also being my Copilot and thank you to all for your time in this session.
01:02:20 Yassin Abbas: Yep. Thanks so much and apologies for Manjeet, we will answer your question later, thank much thank you. Thank you everyone.