What A.I. Means For Project Management
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Thanks again and on to the article - I think it’s a good one!
If we were to rewind the clock just a few years, back to 2019, it would be hard to imagine an article like the one you're about to read being taken any more seriously than what your average palm reader might tell you during a visit to predict your future.
Without even considering the events of Covid-19, which caused a tremendous amount of disruption in its own right, what we are experiencing with generative artificial intelligence has the potential to be a game-changer not only for project managers but for the future of work as a whole.
In fact, the way we are beginning to work—only scratching the surface here—is nothing short of pure science fiction, at least for those who haven't been directly working with A.I.
If words prove challenging in putting things into perspective, let's look at what the data is showing us.
Here is the growth in searches for the keyword "A.I. Writing," which is now one of the most common use cases of artificial intelligence's impact in the world of work today. There has been an astonishing 100x growth in the last four years.
Here's another example. The key phrase "AI presentation maker" also surged in popularity in 2022. Even more crazy, before July 2022, the term was virtually nonexistent.
You can explore search terms for similar workflows that have remained consistent throughout the past decades and add AI to them, and you would see similar growth trajectories. Just give “text-to-audio AI,” “graphic design AI,” and “communication AI” a try to see what I mean. Every single one of them has exploded in popularity.
Seeing increased popularity usually means an increase in demand. That, on its own, doesn’t say too much, but when layered with a few other key components, you get the recipe for true disruption.
How Disruption Happens
Large-scale disruption tends to occur in three parts, with demand— which we briefly discussed—sitting right in the middle. Let’s pause here and provide descriptions of all three before proceeding.
Step 1: The Innovation
The initial spark occurs when something entirely new enters the market. This could be a product with new capabilities, a process enhancement that dramatically increases efficiency, or a macro-level technological evolution that changes the game altogether. In simple terms, a product, service, or process that introduces a new and most likely better way of doing, experiencing, and completing things.
Step 2: Soaring Demand
As you've seen already from the charts above, when news spreads about the innovation and there is a true product-market fit, you tend to see an explosion of demand. Customers recognize the value in it, and given there isn't a fair share of competition (yet), demand soars to the skies. During this time, traditional market leaders (the incumbents) are feeling the pressure, and the new entrants are getting pretty wealthy, famous, and gaining market share rapidly.
Step 3: A Flood Of New Entrants
When demand continues to expand, and the data indicates that the innovation is truly wreaking havoc on incumbents and the market they're in, the natural next step is for new products and services to be introduced that directly compete with the new tech. Or even more disruptively, new companies pop up to expand on the capabilities of the innovation, resulting in a flood of new products and services. At this point, you can officially consider disruption to be in full swing and really starting to make an impact.
So, why is the demand for generative AI so high? Simply put, the level of innovation (step 1) we are experiencing with this new wave of technology is quite literally life-changing, especially in the ways in which we work.
Let’s take the art of creating an action log as an example. For those of you who aren’t aware, the action log is spreadsheet or table that stores, tracks, and segments all the action items for a key initiative. This is a project manager's workhorse during the project lifecycle. Creating this tool is easy enough, but depending on the size of the project or the project manager's familiarity with it, it can be tedious and cumbersome to set up. The best-case scenario is the PM has a template of some sort they can work off of, which would eliminate creating a document entirely from scratch.
With A.I., you can create a pretty comprehensive first draft of an action log with some initial bits of data about the project and a few clicks. That’s it. Below is from my tool: A.I. For Project Managers, which completely automates the process. The image is large, so you may need to click on it.
The fact that I was even able to set this up myself is pretty insane in its own right. What's more, it is completely scalable. A project manager could literally create 100 action logs in a working day with this approach, fully automating administrative steps that open them up to a more strategic and creative level of work.
With capabilities that are out of this world and demand to match, you can bet your bottom dollar that companies, developers, and entrepreneurs have quickly come aboard to push this technology forward while capturing some of the value for themselves (step 3).
And what does that look like in the present day? Here is a sample of entirely new companies that have recently emerged or have pivoted to primarily focus on AI, disrupting traditional ways of working that have stood the test of time for generations.
When you put it all together you come up with the following:
Since entering the market, Generative A.I. has proven on more than one occasion and with various degrees of conviction that it has the capabilities to change many areas of human life, most notably in the world of work and with increasing velocity in the future.
The demand for A.I. tools is reaching levels we haven’t seen since the iPhone.
The pie that is A.I. is big enough and valuable enough to support multiple companies, each one attacking a specific use case or workflow, putting immense pressure on the old ways of working and the companies that have benefited from them.
In other words, we are witnessing one of the largest-scale disruptions happening in our lifetimes right before our eyes.
With disruption at this scale making its way into all areas of work and with an increasing level of velocity, it's more than safe to say our roles, if they haven’t been already, will be going through a shift. What that shift is and how big it will end up being is anyone's guess.
And if you’re in project management, you can expect to be in a world of change. Not only do you have to deal with your role being disrupted, but many of you will also be responsible for leading and navigating this brave new world.
Is this a bad thing? Quite the opposite. I think this is the best opportunity for project managers to date.
How A.I. Is Impacting Project Managers
It doesn't really matter which industry you're in; great project managers all possess a specific set of responsibilities and take action on key components that are widely applicable to any situation.
I prefer to view this within a framework divided into three key components of work:
Higher-Level Work
Workhorse Responsibilities
Administrative Work
Higher-Level Work
The top layer contains what is arguably the project manager's most important work but is also the most under-utilized. In this layer, the project manager spends their time diving deep into company strategy, uncovering the true success criteria for their projects and programs, and building key relationships across the company to eventually become true "dot connectors" for achieving excellence in tasks.
You can think of the Higher-Level layer as the groundwork for everything below. Without proper time spent on seeing the big picture and long-term thinking, the greater the risk that everything done in the layers below is aimless and misguided.
In an ideal world, a project manager should spend at least a third to half of their time on this layer to truly bring value to a company and infuse their role with creativity and strategy. Obviously, a fulfilling situation in its own right.
✨ A.I. Impact - Out of the three layers, higher-level work will be the least impacted by artificial intelligence in the short and medium term. However, there will be some important use cases where A.I. will play a role here as immediately as today if you want it to. One thing I love about the possibilities of large language models is their ability to be your personal coach, sounding board, and assistant all in one. Great PMs leverage A.I. to help fine-tune areas of higher-level thinking, such as segmenting all stakeholders at scale, finding weaknesses in their ability to execute on strategy, and creating concrete and objective ways to score and prioritize opportunities as they come in. Overall, the PM is using artificial intelligence to review their strategy execution framework and make it bulletproof.
Workhorse Responsibilities
The middle layer contains the tasks and items that project managers oversee and actively work on to propel their projects and programs forward. The work and responsibilities in this layer are more intricate and detailed compared to the tasks above, yet they add immense value when taken seriously. Examples of work in this layer include detailed risk assessments, handling constructive conflict, conducting retrospectives, and building productive project teams.
Project managers who excel in the middle layer are perceived as reliable and trustworthy by those they work with. Successfully managing a particular project or program is challenging without getting this area right.
In the present day, project managers should spend roughly half their time in this area.
✨ A.I. Impact - Unlike higher-level work, this layer is currently facing disruption and is expected to experience even more change in the next 2-5 years. With the right context and carefully crafted prompts, entire risk assessments and detailed lessons learned can be created with just a few button clicks. In this layer, artificial intelligence acts as your personal analyst, generating data many times faster than you can, while also surfacing insights you may have never considered.
Administrative Work
The bottom layer contains tasks that are equally important and tedious. Everything from creating and maintaining timelines, scope documents, and meeting minutes falls within this layer. For those less versed in the world of project management, they may only be aware of this layer and erroneously believe it represents the full extent of the responsibilities and capabilities of a project manager (oh, how mistaken they are).
And when I say "equal parts important and tedious," I truly mean it. Since the inception of project management, the ability to keep documentation up-to-date and record/track new information as it comes in has been a crucial aspect of the role. However, in the age of disruption and the natural evolution of the project manager title, roles and responsibilities have expanded, and the lower layer has become more administrative for the skilled worker rather than strategic.
For this layer, outstanding project managers spend 25% or less of their time here.
✨ A.I. Impact - As you have probably guessed by now, this layer is where disruption is most rampant for project managers. In my opinion, the disruption is a welcome addition. Everything from timelines to meeting minutes can now be delegated to non-human intelligence, which should free up the project manager to focus more on the top two layers. For this layer, artificial intelligence becomes your personal project coordinator, taking the tedious work off your hands and, most likely, doing a better job than you ever could.
Long story short, when examining the job role of the project manager within the three layers I've outlined above, it becomes evident that the more basic and tedious tasks will significantly shift away from the project manager (a good thing). This shift not only allows them to handle more responsibilities (also good) but also empowers them to concentrate on the top two levels: higher-level work and workhorse responsibilities (an excellent outcome).
So where do we go from here? Is the role of artificial intelligence just to automate certain workflows for the project manager? For short-term thinkers, this is where it stops, and to be honest, that’s quite a big change on its own. For us, we’re going to take it one step further and look at things that may seem scary and uncertain, and turn them into massive growth opportunities for us as professionals, and the ways we work in general.
The Larger Opportunity For Project Managers
Your company, whether you know it or not, is knee-deep in reviewing the capabilities and implications of artificial intelligence and in the process of planning/executing these findings into its existing business models and workflows. They have to be. It would be pretty unwise not to. It's quite clear to executives in every industry that A.I. is looming in some shape or form, and the impacts of inaction are scary.
All of this is going to trickle down in the form of transformation initiatives. Some of these will be minor, such as transforming a workflow for a medium-sized department, while others will be wider in scale, such as an enterprise change. The immediate downstream impacts from this are equally nerve-wracking and exciting. And with that comes the areas you, as project leaders, should get involved in as early and as much as possible to really reap the benefits.
In a nutshell, the greatest levels of opportunity will show themselves in these three areas the most:
Understand and lead A.I. transformation initiatives at scale.
Balancing Non-Human and Human Talent Leadership.
Crafting and implementing precise A.I. prompts for new workflows.
Let’s spend some time going through each one of these.
Understand & Lead A.I. Transformation Initiatives at Scale
When most people think of change, they believe the hard part is coming up with ideas, building out the solution, and rolling out new processes to support the change effort. All of these, yes, are challenging tasks, but none of them is THE hard thing.
The real challenge of change lies with people. The level of complexity arises from the multitude of personalities, skill sets, and values involved, coupled with the emotional aspect. Emotions such as anger, fear, and even embarrassment all contribute to making managing change anything but easy.
Regardless of the challenges that come with change in the world of AI, the opportunity to successfully lead enterprises through them is more than worth it.
Your goal should be, first, to understand as much about generative AI as you possibly can and how it’s impacting your industry at scale. Second, understand how your organization plans to utilize AI to fend off threats or expand the business. Third, do everything in your power to lead some (or all) of these change initiatives. Regardless of how your company labels or treats these initiatives, change is nothing more than a program or project, which is what you are best at managing.
If you become the bridge that connects the company's transformation strategy with its execution, you will be much better equipped to handle the difficult part: the people. You will be able to shed light on what the benefits of the transformation will bring not just from a short and narrow view but far and wide. You will be well-positioned to comfort stakeholders who fear change, including the threat of job loss, relocation, or any other uncertainty in this new world.
Trust me when I say this: transformation projects of this scale touch everyone. There is nothing you will do that will be more visible and challenging over the next 5 years. The two ingredients necessary to create the type of positive opportunities that will serve you well as you grow as a leader.
Finally, don’t forget you’re human as well. Before you can lead large-scale transformation, you must be comfortable with being disrupted yourself first. Managing change while your very own role is shifting to something new amps up the challenge for sure. The better you look at things objectively, shed things that don’t work, and embrace the new, the better you will be able to lead others through the same transition.
Balancing Non-Human And Human Talent Leadership
With generative AI pushing the boundaries of what's possible in the workforce, leaders across industries will look to recruit non-humans as a talent pool for the first time ever. When looking ahead, it's not unrealistic to envision artificial intelligence moving from supporting humans to taking a leading role across functions. Looking at this positively, this represents an immense enhancement in productivity for businesses.
And while the beauty of artificial intelligence is that it can chug along without human intervention, I see there being a need to manage, fact-check, and course-correct this new side of talent while it gains the knowledge it needs to truly shine. Let’s look at each point to clear the air here.
First, managing artificial intelligence may sound absurd, but there is definitely a value gap here. Right now, A.I. is great at reviewing extremely large sets of data, presenting information, and offering suggestions based on what it collects. It can do all of this faster and in most cases, better than humans can. However, AI will need to ensure it is collecting and presenting information or offering suggestions on the right things. More specifically, is artificial intelligence creating output that’s aligned with the project, program, or company objectives? Project leaders will need to keep a close eye on what the inputs are for AI and continuously ensure it’s something that makes sense for the business.
Even when the outputs from AI align with key objectives, there is still a need to fact-check the data to ensure its accuracy. Currently, large language models are trained on extensive sets of data in the form of text and images. Since this data originates from humans, a wide variance in the levels of truth and accuracy can be expected. Project leaders need to find ways of editing the outputs of AI to ensure the information is viable and correct. I believe those trained in Six Sigma and lean principles have an upper hand here by providing a means to measure variance, just as they would with any process.
With the information gleaned from the previous two points, artificial intelligence will need a way to ingest the errors it produced to learn where variances occurred and course correct for future work. Just like humans, AI can only perform better if it can learn from its mistakes. I'm a firm believer that project management offices and the project teams within should have continuous improvement built into their DNA. Finding a way to extend this from human intelligence to non-human is the first step to managing all levels of talent in the new world effectively.
Which brings us to traditional workers: the humans. While leaders become more and more comfortable managing artificial intelligence, there will also be a need to provide additional leadership to the people in their organization. As you can imagine, the introduction of artificial intelligence into an existing company, department, or group can be intimidating. Project leaders of the future should look for ways to frequently gauge the impact AI is having on the humans in their companies. Searching for signs of emotional anxiety, behavioural issues, or a lack of morale should be early warning signs requiring action from the project leader.
The best way to act on such warning signs? Utilize your newly found expertise in AI, coupled with your experience in navigating change, to guide your people into the new world. In a sense, you should think of yourself as a teacher: educating your teams about the benefits of AI and offering best practices on how to work with this new level of talent. Creating a human/AI partnership is undoubtedly a multiplier effect that will only become more critical in the future. Building a reputation for establishing these cross-intelligence partnerships will be one of the most valuable skills to pick up over the next decade.
Crafting And Implementing Precise A.I. Prompts For New Workflows
All of us in the workforce will have 'prompt generator' as a part of our job description in the future. The ability to experiment with AI ourselves to see what's possible to positively impact our role, function, and, in some cases, the company, will create new levels of productivity and complexity we have never seen before.
To get to this stage, we must go beyond what we are currently seeing with prompt generation now. Most of the prompts I’m seeing project leaders use center around crafting accurate communication or quickly generating meeting notes. In other words, the focus is strictly on speed and freeing up time. And while these are massive steps in the right direction and something we should be exploring, we are missing the point if we feel this is all AI can do for us.
Where AI is expected to be most impactful for project professionals is the ability to create entirely new ways of leading initiatives. From my experience testing AI, here are some of the ways it can become a partner in value generation for your line of work.
AI can review the way your PMO is structured, including the portfolios you have set up, the staff you have on hand, and the success criteria you’re measuring. With the right level of data as a foundation, AI can be your advisor to ensure your PMO is set up with a broad perspective, which is sometimes hard for us leaders to do working within our own bubbles.
At their core, all project leaders should be risk managers. AI can provide a full 360 review of the risks you’ve already identified and offer up entirely new ones for you to consider based on the datasets they have. You can start at the project level and scale this all the way up to company-level risks as you learn and improve your prompts.
If you think of strategy as prioritizing and working on the right things for the business, AI can play a crucial role here too. The ability to review all company opportunities and create detailed scorecards for each will set up a company to make better decisions on project and program prioritization, eliminating most of the emotion that comes with this level of cross-functional interaction.
My suggestion for professionals who lead any new initiatives is to first get extremely comfortable with working with AI prompts and then take it a step further and start seeing how improvements can come beyond just with speed and automation. Those of us that focus instead on value creation will be in a much better spot in a future that’s coming to us faster than we probably expect.
Conclusion
I hope this article has offered you some new things to think about as AI makes its way further into our lives. I don’t think I’m exaggerating when I say this is a cosmic shift for project professionals and workers at large.
The opportunity is there for all of us to explore, learn, and take charge. Like all instances of change, those who take a positive outlook on the situation and own their own destiny will be the ones who are much better off.