There’s one question I am asked more than any other. It recognizes the biggest uncertainty for the project profession: ‘What is the future of the Project Professional?’
We can readily speculate on where AI might be going. But it’s far harder to infer what that will mean for us, as project professionals. It’s something I have been thinking about a lot, over the last 12 months and, particularly, since the start of the year.
We’ll Tackle this Question in Four Chunks
We’ll start by answering two central questions:
When I’ve shared the two big questions, I’ll answer them with two answers:
- Project Steward: The Future of the Project Management Role
- Project Analyst: The Future of Project Controllers and Trainees
I’ll end my asking for your thoughts so, with no further ado…
Let’s get to it!
Why is this Such a Difficult Problem?
AI is more than just a new wave of technology. It feels much more like the kind of existential change that the Industrial Revolution created in the mid to late 18th century. But there is a difference. That unfolded over tens of years. AI is changing our capabilities, and may therefore change our society. And it will do so an order of magnitude faster: in years, rather than decades.
It will affect every aspect of what we do. Those who claim solace in the fact that ‘project management is 80 percent communication’ omit to recognize one thing. Every day, millions of people are training AI to communicate like us, with their prompts and the access we increasingly give to our inboxes. It’s likely that AI will be better at sounding like a human than some of the leading politicians that show up on TV every night.
We may be able to foresee what AI will be able to do, as it matures. But figuring out how that will affect society, jobs, and the professions we enjoy is far harder.
What are the Big Questions we Need to Answer?
And two of the questions we most need to figure out, in our profession, are:
- What will be the role of the project manager?
When so much of what we do will be susceptible to agentic AI and the tools it will command, what will be left for humans? - What does this mean for training and early career?
If there is a role left for us, how will we train for it and get early career experience? Because it will be the easy tasks that AI will be best able to do, in ways that are faster, cheaper, and possibly better, than any early career professional.
Project Steward: The Future of the Project Management Role
A steward looks after something and makes sure it is cared for, nurtured, and safe. The future role of a senior project professional will be less one of managing a project, and more one of taking accountability for its outcomes. This drives several roles:
- Articulating the intent that will drive the project (goal, objectives, scope, constraints).
- Exercising their judgment in the presence of uncertainty. They’ll do this by interpreting signals, evidence, and predictions.
- Making decisions and authorizing experiments, tests, activities, and iterations.
- Orchestrating the work of AI and human agents.
- Building trust among commissioners, owners, users, customers, and both internal and societal stakeholders
Increasing Agility
These project stewards will work in a new world of increasing agility. AI tools can spot trends and plan alternative responses faster than we ever could.
And, to make use of that speed, governance will be more direct, with fewer layers. A project steward will be directly accountable to the political ownership of the project. They will either consult them directly or exercise their authority to make decisions on behalf of those owners.
They will do this by coordinating human and machine execution of project tasks. They will delegate oversight of work packages to agents: sometimes human – more often AI. This will take advantage of the rapid increase in the ability of agentic AI to plan, execute, monitor, and control work.
Underpinning this capability will be vast data-sets that allow the AI to not just understand the project but also the wider enterprise context. The change from stand-alone systems to ERP (enterprise resource planning) solutions in the late 1990s and early 2000s showed the value of wide-scale integrated systems. When they arrived, we saw massive process restructuring (BPR: Business Process re-engineering). The aim was to optimize ERP efficiency by configuring processes to the way the systems worked. We’ll see that with AI implementation too.
Across the enterprise and within the project context, we’ll also see broad-scale continuous improvement. AI can learn, interpret, and change itself. This will create short cycle times on experimentation, assessment, and rejection/confirmation of change.
What Will Project Stewards be Doing?
Beyond their coordination role, the main ‘project management’ function will be tailoring the systems to balance pace and rigor. Project Stewards will design and approve the systems that will deliver rapid, consistent, high-quality interpretation and decision-making.
We’ll no longer describe the team members (human and agentic) they lead in terms of their functional roles. Rather, they we’ll see job titles that reflect current accountabilities. Recruitment will focus on the question: ‘what can we safely leave you to oversee?’
The most important governance role of project stewards will likely be proactive. It will involve the setting up, and constant review, of guardrails and agentic peer review systems. In the early days, there will be a lot of human-in-the-loop oversight. So, part of the stewardship role will be to determine how much and at what points, this will be necessary for each specific project.
Project Analyst: The Future of Project Controllers and Trainees
Project support and control roles are one of the commonest routes to a project management career. And from there, onwards to program management, portfolio management, and PMO leadership, for example.
If AI can do all the things traditional early career project people and project controllers can do, how will people learn their roles? And without learning those roles, how will they progress to project management and leadership?
For the avoidance of doubt, yes. I do assume that AI will absolutely be able to do all the things traditional early career project people and project controllers can do. And yes, I also accept that some people do move directly into project management roles – sometimes with no formal training or experience.
Learning on the Job
But the question remains… What will early career professionals do, to prepare themselves for the new senior role that I am calling Project Steward?
I certainly think we need to drop the terms project controller or project coordinator. Any reasonable interpretation of those terms leads to a job role already well within the capability of agentic AI tools. This just leaves the data entry to an administrator.
So, while AI does this routine stuff, I am going to start to refer to ‘Project Analysts’. This is a deliberate echo of the terms Systems Analyst and Business Analyst. These are, incidentally, two roles that are also likely to disappear, to be done entirely by AI tools. However, the disappearance of BAs and SAs from your company coffee room might put you off that job title. So, I can offer ‘AI Strategist’ as an alternative.
The Project Analyst Role
Either way, these new early-career project professionals will no longer have executing roles. Theirs will be evaluating roles. They will become the critical assessors of the AI’s outputs. They will:
- Interpret intent from their Steward and the wider context
- Task Agentic tools
- Look for and arbitrate on exceptions
- Act as human-in-the-loop decision-makers
- Brief human colleagues on alternative options and facilitate decision-making
Training Project Analysts
Their training program will focus on honing their judgment – especially around complex edge cases. This means that complexity theory and systems thinking must be at the core of their professional training.
Alongside it will be learning about collaboration with, and coordination of, mixed teams. Teams will cross the boundaries of:
- Functions and professional expertise
- Experience levels and cultural perspectives
- Machine processing architectures (different forms of AI tools)
- Human processing architectures (diverse forms of human intelligence and cognition)
We will need future project professionals to be far more comfortable than we are, in much more diverse environments. For example, neurodiversity must become less a matter of workplace equity and belonging, and more a matter of competitive advantage, innovation, and resilience.
This means that, alongside systems thinking and complexity theory, we’ll need other pillars of project education. These will be:
- Psychology and neuroscience, to help them understand Human Intelligence (HI), and
- Machine learning and data science, to help them understand Artificial Intelligence (AI).
The remaining pillar of Project Analyst training needs to be the context in which they will work:
- Business and commercial acumen
- Political and social acumen
- Moral and ethical acumen
So, What Do You Think?
This is very much a set of opinions. Carefully thought-out, yes, but still subject to omissions and biases. So, please give me your own thoughts and critiques of my assessment, in the comments below. I’ll respond to every contribution.
