Introduction
By 2030, 80% of project management tasks will be run by AI [1].
“AI is going to revolutionise how program and portfolio management (PPM) leaders leverage technology to support their business goals,” said Daniel Stang, research vice president at Gartner, the multi-billion dollar information technology research and advisory company on whose research that number is based. “Right now, the tools available to them do not meet the requirements of digital business” [2].
Ever since ChatGPT’s emergence in 2022 hastened talk of the so-called AI revolution, a number of scaremongering predictions have been thrown around regarding which jobs will stay and which made obsolete.
A more productive topic of conversation would be how AI is going to bring about change within roles. AI’s sophistication will need to develop before it starts affecting our day-to-day, but once it reaches that stage, which most predictions suggest it soon will, project management is sure to be one of the first roles affected. Key skills of project management such as scheduling, budgeting and monitoring of progress are more easily adopted by technology than positions that rely on creative thinking or interpersonal skills. As such, project managers will have to adapt.
The benefits of integrating AI into project management
Every year, roughly $48 trillion are invested in projects. And yet the Standish Group reports that only 35% of projects are considered successful [3]. Writing in Harvard Business Review, Antonio Nieto-Rodriguez and Ricardo Viana Vargas, Ph.D, put this down to “the low level of maturity of technologies available for managing [projects]” [4].
“Most organizations and project leaders are still using spreadsheets, slides, and other applications that haven’t evolved much over the past few decades,” they write. “These are adequate when you are measuring project success by deliverables and deadlines met, but they fall short in an environment where projects and initiatives are always adapting — and continuously changing the business” [5].
AI can help cut money waste and contribute to a greater project success rate. The key solutions it offers are: enabling a better, more transparent process for selecting and prioritising projects, an ability to tailor approaches specifically to each client, an enhanced ability to monitor ongoing projects in real-time, improved risk-management and testing systems, and freeing up project managers to focus on higher-level output.
The project selection process
As a company, choosing which projects you want to take on and which you want to prioritise is important. You’re going to be investing company time and resources, potentially for a number of months or years. You want to choose a successful venture/client/collaboration that will bring value and prestige to your organisation. AI can help.
AI capabilities like machine learning provide a level of accuracy in predicting which projects will be worthwhile in a way humans cannot, using data rather than gut-feel. Through an assessment of existing company data, AI can offer faster identification of which projects align with the company mission and which are likely to succeed. This approach also removes human bias from the decision-making process.
Once the project is selected, AI can then help tailor that process to each specific client by assessing how similar projects have worked in the past and either following a similar template (for successful projects) or trying something new (for unsuccessful ones). On top of that, accurate cost estimation can avoid an over-allocation of funds or, worse, an insufficient estimation that either leaves you crawling to your client looking to change your invoice or being forced to work additional unpaid hours.
Monitoring ongoing projects
In an experiment, Peter Kestenholz, founder and Head of SPM Innovation and AI at Projectum, had AI tools create work schedules based on a context initiative described by project managers.
Kestenholz used the prompt: “Global roll-out of a new ERP system to five regions following the PMBOK methodology, starting the second week of May 2023 and to be finished a year after.” The result? “In roughly 30 seconds, a full schedule was returned, containing all the requirements, the proposed task duration and a score that reflected the likelihood of the AI’s estimation of the task duration” [6].
He noted that the better project managers described the project at hand, the better and more specific a schedule AI produced, adjusting as further details were added.
As this technology becomes more sophisticated, project managers will be able to monitor projects in real-time, tracking precisely how far ahead or behind the curve they are. The AI schedule will adjust according to this information, letting them know whether they need to up their efforts to get back on schedule or are able to continue as is.
Nieto-Rodriguez and Vargas say these intelligent tools can optimise the project management office (PMO) through the ability to anticipate potential problems as they arrive and address simple ones automatically. They can also automate the report process, help select the best methodology for each project, and update the approach according to any internal or external changes as and when they appear [7].
Risk management and advanced testing systems
A key feature of AI is that it can anticipate – and mitigate – risks that might otherwise go unnoticed. Of course, project managers, experienced ones most especially, will often be aware of potential risks too, having seen and overcome many before over a storied career. For this reason, it can be useful to rely on both the experience of a project manager and the AI tools to ensure nothing slips through the cracks.
If the AI is fed data on potential risks, it can save the project manager the trouble of scouring the project constantly, as well as being able to flag the risk the second it emerges, rather than being dependent on whether or not the manager is busy elsewhere. For less experienced project managers, having a full risk log readily available can significantly improve productivity and help get them up to speed quickly and without error.
For software-related projects, advanced and automated system testing solutions allow early detection of defects and self-correcting processes. These advanced systems can ensure all bugs have been spotted and dealt with prior to release, saving recalls, and ensuring no faulty systems or products make it to the market. Such testing is already in use on large-scale projects, such as in constructing the Elizabeth Line in London [8], but will soon become commonplace for smaller-scale work too.
The role of the project manager
The existential fear is that AI will replace us. Project managers may read the capabilities above and wonder what their role is in the coming world. But the point is not to eliminate project managers, rather to streamline their processes. They will be in charge of these technologies, not the other way round. It’s vital that AI is overseen by someone who understands the information the AI is giving them – who is AI literate, essentially – and who is inputting useful information back into the system so as to allow for better insights.
Equally, by removing some of the more tedious, time-consuming aspects of the role, such as scheduling or writing up meeting notes, project managers will then be free to pursue more high-value work like meeting with stakeholders and coaching their teams.
“AI offers an opportunity to free up project manager time and allow them to do what they do best—lead teams and get the very best out of people,” says Peter Taylor, vice president of global project management at Ceridian and author of AI and the Project Manager: How the Rise of Artificial Intelligence Will Change Your World. “This will no doubt deliver far better results, fewer errors, more motivation, and greater success” [9].
The role of data
AI is trained on data. As such, the data that companies feed into their AI system’s are pivotal to how the system works. Writing in Harvard Business Review, Tomas Chamorro-Premuzic and Christine Boyce note how, “Large organizations with the time and resources to gather, clean, and structure their own data will be best positioned to maintain a differentiated position in the market” [10].
That said, it’s not just about company size. It’s about how data is used. AI will be trained to replicate the processes of successful projects in order to produce the same results. That means that prior to inputting that data into AI systems, businesses need to accurately assess which of their projects were successful and which fell short – something that sounds simple in theory, but in practice may require parking some pride.
Chamorro-Premuzic and Boyce also acknowledge that, “while training data is a critical first step, care must also be taken to gather ongoing input — i.e., monitoring progress and results — in a way that collects what is needed without being so intrusive as to disrupt or impair people or the process” [11]. A balance is required. Getting that balance right is another responsibility of the project manager.
Another factor, especially during the early stages of the AI revolution such as we currently find ourselves in, is how much data companies feel safe inputting into AI systems. The security of that data is not yet clear and proceeding with precaution is advised. As such, we may only see tentative steps at first, but no doubt, as AI processes become increasingly normalised and security better trusted, project management will soon be centred around it.
The changing face of project management
AI’s integration in the business sphere is an inevitability. Due to its organisational structure and the benefits AI offers it, project management will be one of the first areas of integration. AI can help businesses select the right project, monitor that project in real-time, adjusting scheduling and approach as necessary. Managing and mitigating risks ahead of time will save businesses money and time, while advanced testing will help ensure nothing makes it to market without being optimised first.
Tasks that once belonged to the project manager will still fall under their remit, but their role will be based more on supervision, freeing up time for other vital tasks, not least training staff on AI tools and ensuring the best (honest) data is being put into the software. Until such a time as security can be verified, trusting all data to AI systems will not be the norm. But AI’s day is coming, and project management will be first to feel the shift.
More on AI
New York City’s Bold Step on AI in Hiring – Will Other Countries Follow?
References
[1] https://hbr.org/2023/11/4-factors-that-will-help-project-managers-fulfill-ais-potential
[10] https://hbr.org/2023/11/4-factors-that-will-help-project-managers-fulfill-ais-potential
[11] https://hbr.org/2023/11/4-factors-that-will-help-project-managers-fulfill-ais-potential
Adapting accordingly
Evolutionary change has led chameleons to adjust their mindset and develop unique abilities over millions of years. Some of these unique skills include a talent to change their skin colour instantly in response to predators, to control each eye independently and alter their body shape to communicate with other lizard species. They possess a consistent competence to sense changes in their environment and adjust accordingly.
In our professional world, we know many types of changes can occur. From a people perspective, employees are often asked to be responsive to shifts in their environment, such as being asked to work three days in the office instead of zero days during COVID-19. They may also be tasked with winning a significant business opportunity, such as designing and presenting a presentation to a client. Or they may need to adapt to unexpected structural and strategic changes, such as two functions coming together as part of a merger.
Regardless of the scale of organisational change, people are ultimately at the centre.
Common goals
Change can be a complicated process involving deep rooted behaviours, internal politics, impending risks and numerous benefits. To navigate change effectively, it is critical that teams have support and opportunities to feedback.
From a strategic perspective, leaders should evaluate their engagement process to ensure there is active, timely and effective communication. They should ensure that their teams feel involved and that they actively listen to what their people are saying. As the single source of truth, it is the leadership team’s responsibility to truly understand the core impact(s) any professional change will have on their people before it occurs. By doing this effectively, it sets a tone and builds the foundations for long-term success.
How do leaders ensure that they understand their teams?
Pace, pace, lead
The ‘pace, pace, lead’ framework is a technique used in psychology and performance coaching that originates from Neuro-Linguistic Programming (NLP). Taught within Executive Coaching courses globally, it is an intentional process that helps build trust and gain momentum by establishing rapport with the person or group.
The first step, pace, involves mirroring behaviours, language or communication style to create a sense of familiarity and connection. The second step, also called pace, involves matching their behaviours while introducing new ideas or perspectives. The last step, lead, involves introducing new behaviours or suggestions, which are more likely to be accepted because of the previously established rapport.
The technique ‘pace, pace, lead’ refers to a deliberate process that moves forward at a measured pace. Although it’s not slow, the process can be perceived as gradual. This approach involves carefully building trust and momentum before ultimately leading towards change. This ensures that a clear understanding is established before change occurs.
Summary
During their evolution, chameleons have experienced many failures giving them the skills to learn, adapt and grow through experience. When it comes to small or large organisational change, experience tells us it is critical for leaders to understand their people. The level at which people feel engaged, through active listening, will either build or break trust.
Once a clear understanding is established, organisations, leaders and departments should work towards a common goal of aligning the culture with desired behaviours. Successful change happens when people are given the right environment to develop new skills and the autonomy to be accountable for their responsibilities.
This powerful combination of alignment, advancement, autonomy and accountability provides a genuine competitive advantage resulting in greater individual and collective performance and a significant return on investment.
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Innovation is everywhere. It always has been. From the discovery of fire through advances in weaponry, healthcare and industrialisation, humanity has always found a way to adapt to the latest grand alteration; the next big thing. Invariably, once something as profoundly groundbreaking as the aeroplane or the internet comes along, change is wrought. Old practices are overhauled, then quickly shunted into the annals of history to be either forgotten or roundly mocked – can you believe we used to…?
And yet, to trudge through the mastheads, web blurbs or corporate video montages of almost any organisation today is to see and hear the word innovation endlessly. It’s wielded freely and often vaguely, to the extent that its meaning is diluted if not lost entirely. You’d be forgiven for thinking, given its overwhelming prevalence, that innovation itself was a 21st century innovation. Some of the companies claiming to be innovators are indeed just that – Apple can justly lay claim to having changed the way the majority of people operate in their day-to-day lives. Others simply know how to cash in on a buzzword when they see it.
But what actually is innovation? What does it offer businesses? How should it be used? What are risks and tradeoffs of pursuing the oft-discussed “innovation mindset”, and can they be side-stepped?
What is innovation?
Innovation is a bit of a catch-all term, but generally it just means finding a better way of doing things. That doesn’t necessarily mean inventing something new, though that is of course included. Innovation is just as much about fostering improvements to existing processes and ideas as it is about designing some groundbreaking new product.
When Alexander Bell first communicated with someone on the other end of the phone line, that was an innovation. When industries moved in their droves from the traditional in-office 9-5 to a hybrid working system just a few years ago, that was an innovation too, albeit one forced by global circumstances. It can be too easy to believe (the self-promotion of self-proclaimed) innovators and think that innovation must be cut-throat: the death of the old way; the birth of the new. In practice, things are rarely so straightforward. Which is a helpful reminder of what innovation is not.
Innovation ≠ disruption
Innovation and disruption have come to be seen as one in the same. This is understandable as some innovations are disruptive. Naturally, the more disruptive the innovation is, the more coverage it will receive, thus developing an associative bond between the two in the mind of the public. Uber and Amazon would be prime examples of disruptive innovators. Almost overnight, industries that we took for granted were irrevocably changed. Many taxi drivers, as well as booksellers both commercial and independent, lost their livelihoods. Similarly streaming’s impact on the entertainment industry has seen a total upheaval in how multi-billion dollar organisations now operate, whether that was Netflix’s obliteration of Blockbuster or Napster and its contemporaries’ shake-up of the music industry that paved the way for Spotify’s ascendency.
But there exists a far more gentle (and far more prevalent) form of innovation; W. Chan Kim and Renée Mauborgne, authors of Beyond Disruption: Innovate and Achieve Growth Without Displacing Industries, Companies, or Jobs, call this “non-disruptive creation” [1].
Non-disruptive creation is defined as a means by which new industries, new jobs, and profitable growth come into being without destroying existing companies or jobs [2]. The obvious benefit of such forms of innovation are that they can “foster economic growth in a way that enables business and society to thrive together” [3]. Chan Kim and Mauborgne are swift to differentiate between this non-disruptive creation and disrupting, noting that, “Disruption imposes a clear trade-off between winners and losers…That’s because the leap in consumer surplus provided by the disrupter can nearly wipe out the existing industry and its incumbent players” [4].
Non-disruptive creation, on the other hand, “provides no evident losers and only minimal painful adjustment costs,” while having “a positive impact on growth and jobs” [5]. They cite Kickstarter as a good example of non-disruptive creation. The users were able to fund projects that otherwise would have struggled to accumulate backing; they could choose which projects they wanted to give their money to, as well as how much and how often, and artists on the site were able to realise their dream projects. No livelihoods were displaced. Everyone emerged a winner.
Chan Kim and Mauborgne argue that there is an increased demand from the public for capitalism to give back to society, rather than simply chasing the profit-at-all-costs ideology first theorised by Nobel Prize-winning economist Milton Friedman [6]. Non-disruptive creation, they say, is in-step with such demands.
Social defence
Whether an innovation is disruptive or not, it is still at the mercy of social defence. For innovators, social defence is the great nemesis, stifling their dogged pursuit of progress at every turn. As a definition, social defence is the – quite natural, and often unconscious – attempt to preserve the more traditional aspects of an organisation [7]. Essentially, the “legacy structures, strategies, or cultures that make leaders feel proud and their followers feel safe” [8].
To the innovator, such blockades to all things new and shiny can be sources of great frustration. They argue that change is on its way, if not already here, and that attempts to slow its approach are as futile as they are jurassic. But it’s easy to understand why legacy employees at a large and successful company would be reluctant to rock the boat. The old approach has carried them to such heights; it looks a dangerous game to turn around and bite the hand that has fed them so well. After all, new is not a synonym of better.
That said, change is inevitable, and there are plenty of examples of companies who fell by the wayside because they failed to see it coming, or outright ignored warnings it was on its way. Reactions of major industry players to large-scale innovations have been compared to that of grief, with denial and defensiveness featuring heavily [9].
The music industry’s reaction to the initial emergence of MP3 and streaming is a prime example. Unsure how to fold this game-changing new technology into its existing offer (or at least how to do so and still reap the major profits they were raking in at the time), they went on the offensive, suing the free streamers into oblivion. They won in court, but as Justin Timberlake’s smug grin tells you in The Social Network [10] (where he plays Napster founder Sean Parker), the major labels emerged from the affair as anything but winners. “You wanna buy a Tower Records, Eduardo?” Timberlake smirks, like the fourth horseman of the old industry’s apocalypse.
How should businesses approach innovation?
Writing in Harvard Business Review, Gianpiero Petriglieri, associate professor of organisational behaviour at INSEAD, argues that, “Leadership, at its core, is an argument with tradition. As a leader, you are always relating to a tradition that you are trying to preserve, expand, or change. That means, as a priority, that you must care about the tradition. Or, more precisely, you must care about what the tradition is trying to accomplish” [11]. This is where those desperate to innovate at all costs can go wrong. They see change itself as the destination, not the means by which they’re getting there.
Still, an openness to change is vital. This is at the core of the fabled “innovation mindset”. That mindset can be established in-house or it can be forced upon businesses by external circumstances. The Covid pandemic was a clear example of this. Workplace practices were altered almost overnight; overlong vaccination protocols were streamlined – only possible because the whole world was in step, a rare instance that likely won’t roll around again any time soon.
Susan Rienow, Country President of Pfizer UK, wrote as much in the New Statesman, saying of the incredible innovations and the speed with which they were introduced [12]:
…these kinds of breakthroughs don’t happen by chance. It takes the right environment, support and conditions for science and innovation to thrive. It is not just about expertise; it’s about mind-set and how we come together in pursuit of a shared mission. This mission-led approach and entrepreneurial spirit, coupled with collective and powerful collaboration, helped us achieve what had previously been unthinkable. This shouldn’t begin and end with Covid-19.
Risk vs return
The key, as is often the case, is balance. Genuine openness to change paired with an understanding of what your business is and why – as well as what would happen to it were that to alter. And it’s not solely about whether the business itself is fine to change. Equally important are the circumstances around the business, and its users.
All innovations change the trade-off between risk and return, and “many of the risks associated with an innovation stem not from the innovation itself but from the infrastructure into which it is introduced” [13]. What ardent innovators can miss is that the rate of innovation is often so high that it becomes counterintuitive to invoking systemic change – companies cannot restructure according to each new innovation because by the time they’ve done so the next innovation will have emerged to displace the one they’ve just changed to accommodate. Innovations can possess the most hurrysome of expiration dates – store in the fridge and use within 24hrs of opening, etc. – and so the urgency to adjust with haste feels palpable to the innovation driver. But if you were told the best way to store a bottle that’s soon to go off is to buy a new fridge, well, you can understand the reluctance. Especially when the next bottle is just a day away.
Which innovations are worth adopting or adapting for is a difficult call. Some will alter life as we know it forever; others will fade faster than last summer’s T-shirt tan. To an extent, it’s a gut call and a leap of faith. One that if you get right, can pay huge dividends. Approach with cautious openness, and do not fear the inevitable overhauls. Business, after all, is no more or less predictable or ephemeral than life itself.
References
[1] https://hbr.org/2023/05/innovation-doesnt-have-to-be-disruptive?ab=hero-main-text
[2] https://hbr.org/2023/05/innovation-doesnt-have-to-be-disruptive?ab=hero-main-text
[3] https://hbr.org/2023/05/innovation-doesnt-have-to-be-disruptive?ab=hero-main-text
[4] https://hbr.org/2023/05/innovation-doesnt-have-to-be-disruptive?ab=hero-main-text
[5] https://hbr.org/2023/05/innovation-doesnt-have-to-be-disruptive?ab=hero-main-text
[5] https://hbr.org/2023/04/driving-organizational-change-without-abandoning-tradition
[7] https://hbr.org/2023/04/driving-organizational-change-without-abandoning-tradition
[8] https://hbr.org/2023/04/driving-organizational-change-without-abandoning-tradition
[9] https://www.ericsson.com/en/blog/2018/5/5-key-steps-to-creating-an-innovation-mindset
[10] APA. Fincher, D. (2010). The Social Network. Columbia Pictures.
[11] https://hbr.org/2023/04/driving-organizational-change-without-abandoning-tradition
[13] https://hbr.org/2013/04/innovation-risk-how-to-make-smarter-decisions
