Is AI Revolutionizing the Role of Project Managers at SKILup Days 2024

Hello everyone. Thank you for joining Scale UPS People. Uh, session, uh, today we are covering a lot of things around project management ai, and in our topic today, myself, Isha, and Nisha are going to talk on is AI revolutionizing the role of project managers Today, uh, we have, we are having a packed agenda, and we have divided our session into two half.

In the first half, I'll be just opening this session with various comments about project managers, project management and AI will give you a quick walkthrough. What is the state of AI looks like in project management? What are the current market analysis?

What are some of the different frameworks on a project management, including print to agile and having a small example towards it. After that, I'll walk you through what are some of the benefits use cases of AI in project management, and then we will cover, uh, with, uh, how it is impacting, uh, a challenge, master roles with benefits. There are some challenges as well, so we'll give you the walkthrough about challenges and roadblocks in ai, uh, in project management.

And the second half, I'll let Nisha speak, uh, for herself. Thank you, Jay. So, uh, after we talk about all the different aspects such as covering, we will definitely look at how project management ties hand with artificial intelligence and with new technology coming in and then and taking over the world, what are the new skills that project manager needs to hone, need to adapt and learn?

We'll look into that as well. Also, we have different frameworks such just covering in the first half, but we have different tools, technologies that are also, um, there with AI integration for project management. We'll take a look at what are the top tools and, uh, how they can be used for project management, as well as how it can be implemented in, uh, an organization in a complete framework.

We'll take a look at that as well. Uh, coming into the frameworks and different tools, how does it really work in the real world? We'll have a real world scenario.

And what are the future for project managers with AI technology taking over the world? We'll conclude this session with final words and I'll let Jay take over now. Thank you, Nisha.

So let's begin by opening remarks and comments towards project management and ai. So we all know, like AI has been there from, from several years and especially past couple of years. Uh, it is blooming, especially the rise of chat, GPT Open AI and different open source LLM models.

And there is also a growing concern towards the jobs, uh, market, especially project management. As a project management, you must definitely asking yourself, can AI and project management collaborate effectively, or maybe in couple of months or, or next, by next year, it'll just terminate by role. Well, for a short answer, it's no, definitely you can use ai, uh, to, you know, you as a opportunity and not as a threat to streamline a lot of the current processes, to automate it, to make strategic decisions to, uh, and keep it as a, a decision making and problems solving, uh, capability.

And, uh, with this, there are a lot of powerful AI tools in the market, which are, which we are going, definitely going to cover is the later part of the session where you can use it and handshake it with, uh, project management, a ai. Together. With that, let me introduce myself, uh, myself, geisha.

I'm a cybersecurity and dev professional. I have various cloud security cybersecurity certifications. I'm a certified scrum master.

Uh, I, I'm a certified as SecOps leader. I have seven plus IEE industry research papers in the field of cloud computing, software defined networking, generative ai. I have spoken in several, uh, speaking sessions and on various topics including cyber security, dev SecOps, agile project management, and in, in the previous session with scale up days, I also spoke on ai.

In IPSF, I have eight plus years of experience in various fields in telecommunication industry education sectors, uh, consulting world. Uh, I hold both a bachelor's and master's degree, and I'm affiliated to various, uh, organizations and forums including DevOps Institute, IEEE, and I'm also a community leader and academic leaders and for Canada DevOps community of practice. With that, let's see, the current AI market, having worked for several years.

I, and, and when I talk with different, uh, uh, industries and research about what is currently happening, the tons of things, uh, people are doing a lot of, uh, companies already well advanced in ai. Gartner already is predicted that 80% of project management tasks will be eliminated by 2030. As AI takes over consulting firm, Accenture has found that 50 plus percent of their employees, especially managers, are taking more time on AI for their admin works.

Oracle recently has also advanced and announced their project management skills for the salespeople or to boot their productivity and grow their revenues. Now let's, uh, deep dive into, uh, project management and what is the state of ai PM. According to project management Institute, project managers will implement AI for their workflows, and 30% will be able to meet their project initiatives, objectives and scope.

But on the other hand, close to 50% of project managements have related to new experience on understanding ai, uh, for the project management activities. 5 billion of, uh, investment will be happening, uh, for project management and ai. So there's a lot of things happening and there's a lot of setbacks.

If, if we do not adapt to this emerging world quickly, there are chances that we might lose jobs. But rather than having a set back, let's use, let's see how effectively project manager can use AI and embrace it effectively. So let's begin with is AI really are revolutionizing project management.

The fear is real. And, uh, on the one hand, AI will give you the response to the prompt to input, but that has to be a human intervention. Uh, AI won't replace project managers, but it'll AI will solve the, uh, problems very fast, uh, cost effective and very efficiently.

So as a project manager, it's a, it's a responsibility, uh, to deep dive more into ai, to understand the background about the current topic, uh, to upscale ourselves to be a more creative think thinker, ability to motivate and manage teams together. And at the same time, uh, upscale with, uh, ethical considerations, risk management considerations, and allowing time to have informed decisions within a team and, uh, lead the project effectively and wisely to not see what are some of the benefits of AI and project management. Starting with improved accuracy.

With the lot of open source l and m models, there are high chances of advanced algorithms with data driven insights to improve product management accuracy. Or considering a ticket ticket management system like ServiceNow or Jira, we can analyze for a past behavior about some problem, what is going to be the next ticket, uh, description would look like, how effectively we can automate that ticket and how effectively we can, you know, uh, reduce the errors by having prompt decisions and, uh, and having a terminator before going to production. The second most, uh, benefit of AI in BM world is resource allocation.

We can also use it for task flowing issue. AI improves resource allocation by assigning jobs and resources more efficiently by examining the past data and present project requirements. Again, over here, the caveat is, as the project manager, the emotional intelligence and the decision should come from him or her, and then input the data into the AI system, be it a automating tool or a chat bot.

And based on that, they can do resource allocation, task of allocation, uh, by various criteria, by various exp expertise of the team members. And then, uh, in order, do divide the task effectively, uh, within the different team members from Scrum Master QM members, or even to business analyst. Next is forecasting, especially, you know, forecasting of project, forecasting of budget or forecasting of our pending on the project.

With the right set of algorithm and right set of skills and patterns, approach management can, uh, predict the upcoming forecast and upcoming number of other or no for that particular project. And with that is also the higher, uh, ROI return on investment. Uh, you know, by lowering expenses, boosting productivity and, and Nancy project results, AI can assist project financial in order to automate repetitive processes, creative analysis, and also, uh, in the generic creator, uh, predictions.

So these are, are some of the key four benefits of AI in project management with benefits, doubts, time, how project managers can leverage ai, first and foremost is doing real time monitoring. As AI continues to advance, predictions are smart insights will become increasingly more curate, right? With access to data alerts, notifications, project managers will respond promptly to changes and emerging issues.

Next, project managers can leverage AI for doing predictive planning. They can predict the risk opportunities, allowing them to plan the project more effectively. They can, you know, do a prediction if, for example, that is out of 10 members.

If, uh, two or three members are not available for the project, they can predict if they want to extend the project deadline and timeline by additional two or three weeks. And for that, how many budget allocation needs to be done? So going into Jira, going into ServiceNow, going into Microsoft Azure, there are now a lot of open source agent plugins they can install and, you know, do the automatic dashboarding reporting.

And, you know, uh, downloading the, you know, the GaN chart and one down chart and crediting the, you know, you know, balance, uh, timeline, continuous improvement and adaptive leadership. Some of the next, uh, you know, benefits, uh, of project managers can leverage, uh, how, you know, they can have a adaptive mindset to make sure that, uh, they're working in a collaborative environment and, you know, problem solving the problems more effectively. Now, let's go to some of the project management frameworks.

Some of you might know Prince two and already been working on that. Prince two is a structured project management, project management methodology and a framework especially used in, uh, uk, Europe, uh, uh, firms. And, but now these days, even a lot of North American, Asian companies also adaptively using principal framework.

The principal framework, uh, principles, uh, lives within people, processes, practices, and project context and, and all this are bound and loop together. I won't go too much in detail, but, uh, just to give you a quick, uh, high level background for a principal, uh, uh, framework via pre-project, which basically it's like a starting up of project, like considering as a project as a baby, like how you just nurture a baby to initiation stage, where you set some boundaries within different team members at some, uh, initiate the project, uh, and how you, and that is your project is throughout the project management life cycle. Then there will be different stages, and then in the final stage, you will have a, you know, managing the project delivery.

You'll be closing the project. So that's how Open two framework works. Uh, a lot of com companies, uh, a lot of, uh, you know, high, high demanding jobs, uh, and high demanding tasks of where we can implement Prince two o.

Next is a simple and basic project management, uh, framework, which most of the teams uses, especially agile. And, uh, scrum word, starting with project requirement gathering. We are planning phase.

We go to data planning. If you know, then if there is any raw data, you, you know, apply your plan, how you can use those, uh, data, what are the different tools associated to it? Do we need a DPA or not?

How we can do a project implementation on cloud, on server, or do we have proper infrastructure set up for it? Uh, especially in project management, uh, world, we have different QA who will do the testing, who will collaborate with dev environments, uh, deployment, with the help of, uh, DevOps and their setups will be deployed the code to production, for example. And finally, uh, monitoring and maintenance will come into picture with the help of different networking team, software team and, uh, system admin team who will be doing the particular project, uh, monitoring for any alerts.

Notifications. So in all this, when AI comes into picture, a lot of things will change, especially if a project when I do is, uh, you know, is leading this project, uh, uh, he or she has to be updated with the, uh, you know, the entire phases, uh, detailed phases of this. Uh, and, uh, with requirement gathering, with planning, uh, uh, what he has to input into the AI tool, how, what will the prompt given and what will be the solution towards it.

So they have to be educated. They will also have to build, uh, awareness within with team members. So as we look at the project management lifecycle and framework, um, let's quickly walk you through how project management, uh, project managers can embrace AI effectively in agile sprint planning or its management.

Uh, if considering a two weeks, uh, sprint, the first or second day will go in sprint planning, uh, you know, where different team members will be, uh, a located, uh, task development team. S uh, scrum master will have some hours, or DBA will have some, uh, business manager will have some us. So as role of project managers, they can, you know, uh, analyze this, uh, project by having a vast amount of structural data, considering factors like velocity, success, definition of done, what are the bottlenecks where we'll run, uh, you know, into errors if we need to push the deadline so they can use AI efficiently in sprint planning with, with every successful project, we have to also be, uh, mindful about risk management.

So including, you know, uh, past behavior, they have to also have me medication techniques where will be the backup code. Uh, do we have a different, uh, environment setup? So they have to, uh, you know, make sure that, uh, there are backup plans and if they want to do some escalations.

The next and foremost, uh, phase is CICD, continuous integration, continuous, uh, delivery of continuous or deployment. Uh, Jenkins, one of the, you know, popular tool in the market, uh, Azure, uh, 80, uh, you know, circle CI, where, uh, they can use machine learning models to predict the sugar data from past CI a cycles, or what are the frequency, what are the, uh, how many updates go each year or each, uh, product cycle. And also for quality assurance, how testing can be done.

Uh, rather than having manual testing, they can automate various tasks and activities, uh, by running or automated our testing, uh, having, uh, you know, load balancing, uh, having scheduled jobs, they can use all this effectively, every, with all benefits and use cases. There are also challenges of AI within product management. AI will give you results, but there are challenges with stakeholders.

There are challenges for the scoping that regulator and ethical challenges. You may have to make sure that scope is widely announced within the team. Uh, and the right scope you input into the AI model.

You have to make sure that communication is well balanced between different stakeholders and stakeholders are aware about which AI tool you are using, uh, in terms of budgeting. And so license and subscription, everything needs to be, you know, uh, heard now within the entirety. And when you use any of the tools, we have to make sure you, you are using it in the, uh, pilot program mode.

Uh, not giving confidential data, uh, not having PI data thrown out into production environment using different frameworks, uh, in terms of ity and legal frameworks like this framework, ISO framework, uh, and, uh, having a proper, uh, communication with the cybersecurity and legal team. So there are challenges away within manage management, and we have to work on it, uh, by adapting the right tools, technologies, and skills. So with that, I'll pass over, uh, the mic to my cos speaker, Nisha, who will, uh, you know, kick us, kick us off with the later part of the session around project management and how it is Handshake with AI over to Thank you, Jay.

That was a wonderful session, uh, which we have right now. So now we'll be de diving deep into how project management ties hands or handshakes with artificial intelligence. Before we dive deep into that, I would like to give an introduction about myself.

So I'm Nisha, as you can see. Uh, I've been working with Walmart as a senior data analyst and have about six plus years of experience in ai, ML and data science domain. Previously, I worked with Amazon Web Services predominantly in their ai, ml and big data services.

I have been, I have various certifications in the cloud domain like Azure, G-C-P-O-C, and AWS. Also, I'm a Scrum master certified and have about three research, IEE research industry papers published in the field of IOT Generative and OCAI am. I'm really, really annoyed in Python, and I love to code in Python.

Uh, I'm also very, very interested in Tableau dashboarding, BigQuery, and, uh, generative AI services. Let's now move into what this topic is all about. Project management handshaking with ai, AI is definitely revolutionizing project management by automating task, enhancing decision making and improving risk management.

Among other benefits. Like you can use AI for different, uh, reports that are getting generated for scheduling purpose. And as AI technology continues to evolve, project managers who embrace these tools are better positioned to lead a successful project and adapt with the changing advance.

The future of project management is undoubtedly intertwined with ai, and the possi possibilities are endless to make sure that we are having more improved efficiency and streamlined procedures, and also have the projects deployed on schedule and have a fast-paced, uh, environment. It is important that project managers are developing their skills and honing with ai, which is drastically changing the project management field. Over to the next, where we talk about how, what are the different AI use cases for project management, just recapping, uh, some of them before we go on to the next one.

AI automates a routine task allowing project managers to focus on, focus on strategic aspects where you can have AI to take the T standards to also schedule their task and, you know, reach out to people for updates on their task, which is maybe having a deadline of tomorrow, or even have reports being generated using dashboards. Project managers can focus on the strategic part of it, on the emotional part of it, and talking with different people. At the same time.

Some of the real time risk management can be done using predictive analytics, where, uh, using the history of project ma of different projects, AI can provide us with an update or pro predict whether what are the different aspects that need to be improved and what is at risk for this project so that it can be communicated by the project managers within the team. There are various challenges like data security, algorithm bias that may come into picture over here, but we need to make sure that we are able to implement AI successfully with different rules that are there, like Jay already spoke about, to transform project management practices and drive organizational success. Let's move on to what are the top skills that are required for project manage, for project management?

While we have AI taking over, and, you know, you have different tech tools and technologies already, uh, integrated with ai, there are still some top skills that are required for, uh, project manager. Basically, when it comes to creativity and critical thinking, it is very much necessary for a project manager to hone those skills and also keep learning, have continuous learning and adaptive leadership so that they can work with the new technologies coming in and the adaptive nature of the tools and technologies that we have. While there is requirement of communication across all boards and boundaries, AI can definitely provide you with some communications like we use Chat g pt.

But having said that, a project manager definitely knows what the scope is and how it has to be de deployed and how the communication needs to be done. So that is definitely required for a project manager as well as to identify the right talent required for the project. It is under the project manager's hat.

While we have AI ticking over the tools, it is important that a project manager definitely knows how to navigate AI and this, and have foundational knowledge of data to make sure that they are developing new tech skills and make sure that even people in the team are developing their skills. We all know that tools are integrated with ai, but we still have our frameworks like Agile and Prince two and prints too, and project managers definitely need to know all of those things while all these happen. What about the deployment?

Right? Project managers obviously need to know how the project delivery need to happen, and what are the execution skills that are required so that they can have a successful deployment of the project. Let's move on to what are the different tips that we can give for project managers, right?

If you're a new project manager or maybe a project manager who is trying to upskill themselves, or, you know, enhance and, uh, maybe integrate some new tools, please be sure that you're not integrating all the tool at once for the entire project. That can be really overwhelming. Let's start with a small step, right?

Take a few small tasks within the project and try to integrate AI into it. Maybe like for reporting purpose of a scheduling purpose, you can have the task scheduled or your codes running within an automated way, and providing updates to everyone in the team. Start small so that you can have a smoother transition, and you'll know whether your team is able to adapt to this new technology.

Also, based on different companies, there are requirements of different AI power tools. You have so many different new tools that we'll cover that we'll be covering in the next slide, but according to your organization and the project that you're working on, make sure to choose the right tools and align with those tools, align with the project management needs, and integrate them according to their advantage and your advantage while you are trying to adapt to new technology. Make sure to train your team on these new technologies and familiarize them by, uh, how to use these solution or else, instead of in reducing the time, you might end up increasing your time just to make sure that they are using it efficiently and you're able to adapt to this new, new technology while you are able to, while you're integrating everything and you know your team is working fine, it's very important to monitor the progress of your team.

While AI can build a dashboard for you, it can have different types of, uh, scheduling and, you know, various new ways of me letting you know that what is a progress. It is also important for a project manager to deep dive and make sure that they are able to meet the key metrics that are required post the implementation of AI within project management. Let's move on to looking at what are the top AI project management tools.

These are another recommended tools by us, uh, for you to implement. These are some of the top industry project management tools that are currently being used worldwide. com and different Trello as well.

And I'm sure Jay has also been working on some of the different tools over here. But, uh, to give us some kind of, uh, understanding of what is happening over here. Jira, I know most of y'all will be using a project, you know, Microsoft project or any of these tools over here.

They keep adapting to the new technology and have AI integrated into it. So how you can use Jira for, uh, for ticketing purpose or for Confluence. You can also get updates from Jira directly into people and have dashboards built into it so that you can leverage it.

And as well as Microsoft Project integrated with different tools so that you can use it for your project management purpose. Let's look into, while we look at different tools, how different task and top functionality can be mapped with these tools. While we have different tasks, like we already spoke about report generation, quality assurance, and productive, uh, planning and scheduling, we need to make sure that we are using the right tool for the right purpose.

Like we have Smartsheet forecast for report generation, and, um, you have Trello for productive appraisal and Slack, Microsoft teams for inter and intra team communication. Let's move on to looking at how you can implement this into a project management framework. We need to define clear objectives.

We all follow these, you know, this entire framework in our organizations, maybe this or different frameworks, but how do you integrate this and make sure that you are implementing it with AI is something that we wanted to show. I'll not dive deep into this, but we all know that we need clear objectives before even you can start with your project. You need to choose the right tools, have the current, uh, current infrastructure, make sure that you're ready with your data and your, and you're providing the right data to your AI tool, and you're not providing any p information or anything that would cause a bias.

Make sure that you're training your team with the adaptive and the new technologies that are coming in and implement the project with small and pilot data first and it trade traded to make sure that you're getting the right results and the results that are needed or required by the stakeholders. Monitor it, optimize it, make sure that you're getting the best results, and then try to scale up, right? Try to scale up and move ahead with bigger data or with bigger projects, and make sure to review and evaluate your progress.

Let's go ahead. I would like to, uh, also talk about what are the new roles that we have, uh, in AI world under the project management hood. Definitely this, these roles are not something that need to be under project management.

It could be, uh, some, it could be within the organization as well, but to have an LLM trainer to know that this person would be, you know, responsible for working with the AI platform to build context sensitive use cases and to be critical for translation of neural algorithms into actual user inputs and outputs, also have prompt engineer. This would be a customer facing role that would help your users to get the right type of responses from the system, especially early on. These resources should be assigned at the outset and ramped up before testing begins so that they can understand the strength and weakness of the system.

Now, I would like to call upon Jay to move ahead and let us know what are the future for project managers. Yep. Uh, thank you Nisha.

I know we are on right of the time, so one thing much, uh, time over here. Definitely the slides would be there for you, but now we have covered end to end about, you know, how project management is, uh, you know, used effectively with, uh, project management, uh, team members. Uh, what are different frameworks, uh, what are tools, technologies, and use cases?

So now let's see, what are the future of project managers? Uh, you know, uh, definitely project managers needs to now, you know, uh, adapt to various AI teams. Uh, they need to, uh, give PMP and prints to certifications to know end-to-end project management lifecycle.

Uh, they play a crucial role in risk, uh, mitigational risk, uh, uh, you know, considerations and, uh, with the amid, uh, changes, uh, be it geopolitically. Uh, there is supply chain issue, the ethical considerations and environmental changes, uh, AI over there won't solve the problems. It would be the role of project manager to have our emotional intelligence to make critical decisions at the right time and at the right stage.

And, uh, with that, uh, they also need to, uh, project managers are mentors, uh, for both people and technology and processes with prompt engineering. Uh, they have to train themselves there as initial mentor. They have to upgrade various skills and, uh, with, uh, you know, knowing AI data, uh, and various soft skills and technical skills.

And, uh, uh, at the same time, they have to be an enabler and where they have to, you know, fuel the data, uh, for ai, uh, going forward. I have a short, uh, YouTube video clip over here, which I, uh, you know, mentioned over here. Uh, so do check over there, uh, to see, uh, a small example of how AI agent is embedded in a standup call within a team members, and how that AI agent is taking notes in notion to io, uh, and how they are talking, uh, as a human, uh, with different team members and solving the problems, uh, you know, of a project manager.

So that is something, uh, you can definitely use ai, uh, within your, uh, team, uh, to solve, uh, and have automated responses. And at the same time, project managers rule it to review those notes to make decisions, uh, and to make that, uh, no. What is upcoming?

The next, uh, project management lifecycle. Good morning team. Let's kick off our standup.

Let's start with deep. How's the progress? I was working on adding agent's ability to read information from chart and graphs on website.

I tried it on some websites and it is able to interpret charts and graphs and gives us somewhere in the report. Got it. Could you create a document in the notion folder I shared?

Sure. It'll be ready by the end of the day. Alright, path.

What were you working on? Uh, hi. Um, I have set up the G meet agent on EC2.

It'll join the meet from the server. Uh, transcription has some minor errors, but we are able to hear the agent's response in the meet. What is the plan for correcting the transcription errors?

Um, I'm exploring deep gram and open ai. I'll discuss with the sh finalize something by tonight and push the code. And with that, uh, uh, we, we here to complete a session, uh, and with some f some of the final words and final comments.

Uh, that's why we project managers don't have to worry about their jobs going away or they're getting terminated or they're getting laid off, uh, with x number of reasons, but it's time to own oneself, uh, and to adapt, uh, to this emerging technology market and to update themselves with skills, uh, not the basic skills, but the advanced level skills, your daily operations. Uh, they need to know what SA did it to know, uh, uh, database, uh, technology, data, data, various, uh, cloud environments based on their job duties and responsibilities. And, uh, again, with automation, uh, they have to make critical and strategy decisions and, uh, uh, with that, uh, they have to, uh, make sure that AI handles everything effectively and it's in the safe hands, uh, again, with, uh, concerning legal and regulatory regulations and security compliance, uh, before anything moving into production.

And, uh, oh yeah, that's it for our, from our side. Uh, thank you for being here. Uh, we have our information, so feel free to reach out to me or to my cos speaker.

Nisha. Uh, if you have any of your stories, I want to have discussions around project management, ai, and want to learn more. Uh, feel free to connect with us on Thank you.