The future of artificial intelligence in project management

New research from APM reveals some important truths about how project professionals perceive AI technology, its usefulness for projects and whether AI can ever learn to be a project professional.

New APM research provides insights into the critical conversation about the role of artificial intelligence (AI) technology in project management. For the individual project professional, the current low use of AI in projects opens up opportunities to get ahead of the competition and gain valuable skills before the technology becomes widespread. The professionals who recognise AI’s opportunities and potential early on are likely to be the ones who demonstrate its increasing value and implement its use for positive project outcomes. According to a new APM research report, Artificial Intelligence in Project Management: A review of AI’s usefulness and future considerations for the project profession, the opportunities and challenges of using AI surround:

The number of project professionals who have received training in AI is significantly low, yet the demand for AI‑skilled individuals is high. This is an important finding since a large majority of the survey participants stated training in AI is important in order to use it for projects. Project organisations are not providing training in AI at a sufficient level. However, organisations that provide good AI training will reap the rewards.
Varying degrees of understanding. Many project professionals have a limited understanding of how AI can be used in projects, so developing expertise in AI will give professionals and their organisations significant advantages and opportunities.
A high degree of novelty. AI is still unproven in many project sectors and real‑life case studies of AI used by project professionals are scarce. However, this creates opportunities for businesses that are successful in this field to take a leading role.
Ambiguity of the impact of AI. Although project professionals believe AI will impact the project profession, there is some ambiguity around what the consequences of this impact will be. If employers successfully communicate the change and impact AI will have on professionals’ roles, organisations have an opportunity to build a trustworthy workplace and support professionals when exploring this novel technology.
Ease of use. Professionals state that using AI is a challenge because it’s not easy to use. This becomes a barrier for implementation and can slow down the overall adoption of AI. Some of the challenges of AI are inherently difficult to change, such as reusing data and AI models for different problems. However, this becomes an opportunity for early adopters to improve AI’s ease of use.

What action should project professionals and organisations take?

Offer AI training

Project organisations need to make training in AI more available for professionals. It is key for organisations’ senior management to focus on increasing professionals’ AI skills.

Create a ‘why’ for using AI

To use AI successfully it is crucial for project organisations to justify why this technology is necessary through an organisational ‘why’. This will set the correct expectations and create a common purpose for using this technology.

Define a clear AI problem formulation

Our research shows that AI can benefit decision‑making and support problem‑solving functions. To enable this, it is important for professionals to be specific in how to use AI. We suggest professionals and organisations should articulate a clear problem formulation for the objective of using AI that will enable better use of resources for data management and identify suitable AI techniques for solving specific problems.

Develop effective data management processes

Having suitable data is crucial for effective AI. To adopt and implement AI, project organisations need to establish sufficient data management processes. This may include sharing data between internal project teams, managing historical project data and using external project databases.

Create an open learning AI environment

Project professionals do not find AI easy to use and project organisations should aim to make AI more accessible. To achieve this, organisations should create an open and inviting learning environment where learning about AI is encouraged across the whole organisation.

This is an edited extract from the APM research report Artificial Intelligence in Project Management: A review of AI’s usefulness and future considerations for the project profession by Professor Nicholas Dacre and Fredrik Kockum, University of Southampton Business School (June 2022)

Can AI learn to be a project professional?

According to the APM research report Can Artificial Intelligence Learn to be a Project Professional? Potential implications for the professional status of project management, no matter whether human project professionals or an AI tool are considered, there is no conflict in terms of the targets of human project professional learning and AI learning. The fundamental target is to enhance project management performance and deliver project outcomes. Of course, who owns that learning and the uses it is put to are another matter.

To deliver, project professionals need to master both hard skills and soft skills to deal with clients’ requirements and dynamic business contexts. Since the soft skills of dealing with team members and stakeholders were considered an important competence, one of the main learning inputs of project professionals is the experience of interacting with peers and stakeholders. This situated, ‘word‑of‑mouth’ learning resource would be difficult for AI to replicate in terms of obtaining the input data as a prerequisite to developing the behaviour. Hence this creates a certain protection for the career status of project managers versus AI, provided that the practices being passed on are still of value.

Current AI mainly uses historical data to predict future performance. However, when dealing with human beings, project professionals’ irrationality based on subjective experience is too unpredictable to be digitalised within an algorithm as input for AI’s learning. Trust and reputation based on emotional reliability cannot be earned by AI as it can with human beings. However, with its learning ability and a suitable database, AI can collect changing requirements and characteristics of different clients and generalise data from different projects. Therefore, it could support a human project professional in predicting the behaviour or preferences of a client.

Data availability and quality are the main concerns in developing project management AI, which is a significant barrier. AI will have an active role in simulating project performance when there is sufficient data available. This aligns with current research into the functions of project management AI in predicting project success, monitoring cost and time, validating safety and forecasting demand, hence acting in an effective, but passive, decision‑support role. AI is a knowledge‑based platform, so in terms of enhancing the knowledge communication, AI can make a difference and contribute to ‘best practice’.

In terms of learning, there are possible impacts on the transfer of practices from senior to junior. As AI learns and historical data on project professional performance accumulates, forensic insights into team performance are possible. However, based on this, a predictive recruitment AI may decide which projects a worker gets to participate in or who is considered effective in what context. This will have serious consequences for learning and the kinds of high cost but potentially high value learning that comes from failure. Although, conversely, it could raise barriers against poor performance which might improve the reputation of the profession in a company or in society.

The project practitioner using AI could become the most important person on a project, providing a ‘sixth sense’ and ‘superpowers’ to avoid variance and identify which activities and work breakdown structure components are more predisposed to variance. Leadership can have earlier warnings of emergent issues.

To obtain the benefits of AI for and defend against the threat of encroachment that is not on professionals’ terms, human project professionals and their professional associations should:

demonstrate and develop codes of ethics, particularly around negotiation and convincing of clients;
motivate project professionals towards ethical conduct and soft skill development;
develop and reward the use of soft skills in the workplace, particularly motivation and recognition of peer excellence;
master data management skills to create better data sources as data quality can impact both human and AI development;
master basic AI knowledge in order to maintain control of and work with AI and deliver successful projects;
strengthen senior-junior relationships and peer‑learning approaches, building mentorship between senior and junior project professionals; and
promote new learning opportunities for juniors, especially if the more routine activities become digitalised.

This is an edited extract from the APM research report Can Artificial Intelligence Learn to be a Project Professional? Potential implications for the professional status of project management by Dr Kun Wang and Dr Ian Stewart, University of Manchester (June 2022)

How useful could AI be for project professionals?

It enhances decision‑making

AI does not find the correct answer to problems every time. However, when used in an efficient way, professionals suggest AI can enhance the decision‑making process in projects, which could be one of the most beneficial elements of AI.

It supports problem‑solving functions

A key benefit of using AI in projects is to support problem‑solving functions. This can be done through analysing large sets of data and identifying potential solutions when problems arise. One professional said: “We often get behind schedule, and we then need to manage and reassess our resources. Using the AI predictions can help us manage our resources better.”

It is most likely to be used during project planning

The analytical capabilities of AI can improve planning activities, and with its efficient data management an AI tool can be highly beneficial for project professionals.

It improves efficiency when analysing large volumes of data

We humans are limited in our cognitive abilities and most of us have difficulty processing large sets of information from multiple sources. Professionals stated that AI is an important tool when analysing large data sets.

It has the potential to increase project success and mitigate project failure

Professionals believe AI has the potential to increase project success and reduce project failure. This also results from the benefits of improved decision‑making, problem‑solving, project planning and analysis of large data sets.

There is a positive correlation between the level of project complexity and AI’s perceived usefulness

Professionals believe complex projects benefit more than simple projects from AI. This indicates that there is a positive correlation between project complexity and the perceived usefulness of AI. Additionally, during research interviews we found examples of professionals who preferred to use AI for complex projects rather than other projects. One professional said: “Complex projects consist of many unknowns, and the unknowns are increasing in our projects. We can see that using AI technology reduces some of our unknowns. For a simple project, we do not see the same need for AI.”

Source: Artificial Intelligence in Project Management: A review of AI’s usefulness and future considerations for the project profession (APM, June 2022)

Is AI really the future of ‘big’ project management?

Brett Parnell and Merlin Stone provoke the profession to ask some critical questions.

There is no doubt about the impact of AI in many areas of business. Wherever there is lots of data about repeated events, AI can be used to find patterns, predict what comes next, diagnose problems and so on. This also applies to projects where the same activities are repeated many times. However, for large and/or complex projects, or for ones which are full of ‘first of a kind’ situations, AI’s utility is less clear. Here, the role of the project professional – managing the people who deliver the project – will remain. Or will it? At the centre of the debate on AI in project management lie several questions:

What are project managers’ competencies, and which are relevant in different types of project?

You might have thought that the answer to this first question has been documented clearly in bodies of knowledge. However, it may be appropriate to re‑evaluate competencies, particularly the distinction between behavioural (especially emotional intelligence, creativity and ethics) and other competencies, but also to review the competencies in light of how AI is developing, so that competencies can be classified according to whether AI replaces or supports the competencies or threatens their deployment. This applies particularly to complex projects, where the relationship between competencies and project success is most critical.

What do project professionals actually do during project planning and implementation and how do they do it?

What project professionals do is generally understood, although the time and effort spent on different activities varies between projects, between the roles of different project managers, between levels of seniority and in other ways. Research into the role of AI should avoid generalisations, but focus on specific examples of deployment of AI to replace or support project professional activity.

How is this work affected by general developments in technology?

This area is well understood, with technology facilitating increased efficiency and reduced time spent on routine tasks, making non‑routine activities more rewarding and (ideally) successful. It is one of the focuses of APM’s research project Projecting the Future, and here a key recommendation is for project professionals to develop their understanding of new technologies.

In which of these tasks can project professionals be replaced by AI or supported by AI to do tasks better and/or faster?

A key issue is how human roles can be combined with AI, as opposed to being replaced by it. The idea is that AI can be used to improve predictions of outcomes of particular project actions, including enhanced risk analysis. However, there is not much reliable and deep public evidence of how project planning and delivery have been affected and, more importantly, what tools and techniques have been deployed in practice and how they should be developed and implemented.

What data development is required to ensure the deployability of AI?

AI thrives in the world of big data. AI needs big volumes of data, bigger than currently used in megaprojects. If AI is to improve project management, it will need much more data from projects, perhaps even by‑the‑minute reporting of project status. Much of the extra data needed for AI to be deployed successfully is unstructured, e.g. project professionals’ opinions about risks (perhaps even their sentiments, building on the sentiment analysis so common in the social media world), and may not even be captured now. So, much effort will be needed for identifying and collecting many different sorts of data – structured and unstructured. There is no presumption that these new data sets will be perfect. The key is to identify and make use of them, learning through AI which data sets are useful, and in what forms, and where improving the quality of the data might bring returns, including identifying where the data may be inaccurate or wrong.

How will AI be deployed to analyse and predict?

Data analysis may best be done by combining human and artificial intelligence, e.g. by humans initially identifying the meaning of data and then training the AI to generalise from these classifications – so‑called ‘supervised learning’. Once all the data becomes analysable, the idea of a digital twin for a project comes into its own. Digital twins thrive in situations where high volumes of data are used to optimise management of technical artefacts (e.g. buildings, airliners). The question is whether, in projects that involve substantial behavioural change, the digital twin approach can be used to plan, model and manage delivery.

What will the benefits of the deployment of AI be?

The benefits of applying AI to project management are expected to include:

creation of a stronger and more widely shared basis for decision‑making;
increased rationality, especially via removing/reducing decision‑makers’ cognitive bias;
more accurate forecasting of project progress and completion;
increased speed of decision‑making, especially in response to new data being available, e.g. about the status of the project, changes in expected costs or benefits or changes in stakeholder requirements;
improved identification of missing or imperfect data;
better incorporation of learning from experience; and
higher quality management of projects and resulting higher success rates.

Our understanding of AI has developed greatly in the past few years, but we must dig deeper to understand how AI can improve project management, other than by substituting automated analysis for routine tasks. The main focus of our work should be on the most central element of project performance, the human factor. We believe more research into this is needed.

Brett Parnell is Principal Consultant at MI‑GSO PCUBED, and Professor Merlin Stone is Principal at Merlin Stone Consulting