Project management is arguably the world’s most influential neo-profession. Its success at establishing itself as a dominant and ubiquitous form of management is unprecedented. Currently, about one-third of all economic activity in the OECD is conducted in a project format.
Your choices are to embrace artificial intelligence (AI) as a new paradigm for project management, or to risk being left behind by those who do. If you look to the comfortable and established Baby Boomer or Gen X professionals for leadership, there is a risk that you will pay the price of lack of awareness.
In 2017, Arup published a report called ‘Future of Project Management’. In an otherwise excellent piece of work, there is a critical error – timing. It stated that, by 2040, smart algorithms will prove to be better than expert judgement. A correct forecast, but 20 years too late, because it’s happening right now.
Much of what happens in project management is about gathering, structuring and making meaning from project data and reports in order to drive good decisions, then organising the implementation of those decisions. Due to the complex nature of many projects, a high degree of professional skill is often involved in determining which information is valuable, what it means, and how it should be used to make decisions that deliver the desired outcome.
Right now, AI machines can do this activity far better and more efficiently than the most experienced professionals. This is a hard revelation for experienced and senior professionals to accept, and many will retire before the disruption really takes hold. It is too easy for Baby Boomer and Gen X senior managers to gloss over disruptive technologies, instead leaning on the successful career strategies of the past which led them to their
leadership positions. The senior members of a firm have the power and position to select what they regard as a winning strategy, because the boss is always right.
Emerging leaders cannot afford the same ambivalence. Adapting to the inevitable paradigm change is a survival skill for the new generation of project professionals.
The emergence of AI in projects requires a paradigm change in the way we think about the project management task. Paradigm change is not easy, and it rarely emerges from the status quo. “Almost always the men who achieve these fundamental inventions of a new paradigm have been either very young or very new to the field whose paradigm they change,” noted science philosopher Thomas Kuhn.
At the core of this paradigm change is the underlying philosophy of project management. All forms of human knowledge have a philosophy, because philosophy is about how we think about knowledge itself. The philosophy of project management is about logic and is mostly cause and effect based. All you have to do is read the PMBOK to see how dominant the logic approach is or look at a P6 schedule to see a shining example of cause and effect
In this paradigm there is an underlying belief that logically organising things will result in predictable outcomes. This underlying belief makes it philosophically foundationalist. The counterpoint to this approach is called the empiricism, and it is the philosophy that underpins the artificial intelligence approach.
Current project management methodologies rely on cause and effect analysis to form the foundation of decision making, whereas AI methods are more aligned to a probability approach. This is similar to the difference between classical physics and quantum physics. Changing from a cause and effect focus, to a probability focus is a bigger step than you might think, since the former is so deeply embedded in almost all project management methodologies.
The emerging generation of professionals are well placed to embrace the new paradigm and be the catalyst for organisational change. They are also the likely champions of organisational understanding of AI, with the mindset to allay some of the fears that traditionalists may be experiencing.
AI will change the world of project management, but it is not going to take over the world.
Can we be more human with AI?
AI is essentially a mechanical mind and can be compared to the mechanical muscles (such as excavators) of earlier eras. Excavators replaced many men with shovels, increasing productivity, and redeploying workers to more sophisticated jobs with better pay and conditions. We haven’t yet reached our full potential as a society and, by taking advantage of the opportunities which AI presents, we have the opportunity to take another step forward.
AI can do many of the technical tasks required in our day-to-day work lives, enabling us to focus our energies and be more targeted to the things that really matter. The common understanding is that AI allows us to automate repetitive tasks, but although this is a comforting thought, it is an overly simplistic view.
AI is already performing expert tasks which we traditionally associate with high-end professional skill and experience (such as medical expertise) exercising their judgement. The technical skills which are often associated with experts will start to take a back seat to soft skills. Communication, emotional intelligence, creativity, critical thinking, collaboration and cognitive flexibility will become the most sought-after human abilities, along with our abilities to operate in teams.
Are our jobs at risk?
This is a burning topic and the tendency is to either predict the end of work as we know it, or glibly forecast that it ‘will all be okay in the end’. It is true that the work environment will change, and it is also true that a new balance with be established. To that extent, it will be all right. The question for millennials is this; what will happen between now and this future new balance?
Although there are many commentators and thought leaders willing to make predictions, in reality nobody knows. There is a reason disruption is called disruption. History shows that the world does not change smoothly, but in big and unexpected steps, which demand adaption. Fortunately, we are pretty good at adapting, and millennials as a group are probably the leaders.
The risk is not so much to our jobs, but to our perception of what our jobs look like. This is particularly so for the professional service class, whose jobs are mostly mental effort and the application of hard-won experience in a specialised knowledge area.
Academics Richard and Daniel Susskind’s book The Future of the Professions makes the point that change to the traditional professions is inevitable and that in the future professional work will be done through combination of technology and people, probably by people who look very different from today’s professionals.
This is both a risk and an opportunity for millennials whose vision of their future roles and the way these will be affected by AI will emerge not from the traditional practice of learning the ropes from senior members of their firms, but by their own work innovation. Perhaps jobs are not at risk, but job descriptions will change.
In terms of those affected, there is a lot of current focus on robots. This is missing the big impact area, of cognitive workers. In reality, it is much more difficult for an AI machine to undertake physical tasks requiring dexterity in an unstructured environment, than it is for a machine to undertake complex cognitive-like tasks.
Of course, we might consider that machines cannot respond to human problems with empathy, creativity or resourcefulness. But as the technology emerges, it is worth thinking about what sits behind things like resourcefulness.
One author who has done much thinking in this field is psychologist Daniel Kahneman and it’s worth keeping an eye out for his publications.
Does adopting AI require technical expertise?
A study by Forrester found that around 70% of decision-makers don’t think their staff have the technical capabilities to take on AI. This presents an opportunity to clear up misunderstandings of what AI is and showcase what tangible benefits it could have for your business.
The adoption barriers to AI are not predominantly technical, any more than it is necessary to understand the workings of an engine in order to drive a car. AI at its core is complex (like a modern car engine), but AI products can be designed to run their intricacies in the background and provide their insights in user-friendly ways.
What is important is to know the capabilities and limitations of the AI you are using. It’s important to become an informed user, and this will require some knowledge, particularly for businesses.
The prospective benefits of AI are enormous in scale and diverse in focus. The value doesn’t lie in the technology alone, but in how willing we are to challenge our own paradigm.
Millennials should take the lead, because they are well placed to adapt to the emergent impacts in a way that leads our society to mitigate the human disruption and maximise advantage through adaption. Though we do not know when major changes will occur, we do know that they definitely will. AI is a change on the scale of the introduction of the internet or the motor car, and companies which experiment with early adoption will be well placed to weather the inevitable change.
Baby Boomer bosses do not have the answers. As Donald Rumsfeld famously said, “there are things that we don’t know that we don’t know”. Millennials can assist businesses to transform some unknown unknowns, into known unknowns, which would be a good start.