Global Trends

Using Artificial Intelligence in PM: Just a good bedtime story?

8 August 2018 / 10:07

Technological evolution has become an unstoppable mindset. Resultantly, actions and behaviours of individuals, organizations and societies are shaped and dictated by their degree of interaction with the technologies around them.  Emerging technologies including, but not limited to, artificial intelligence (AI), machine learning, big data and social media are gradually becoming part of our lifestyle.

Organizations across the globe have, therefore, seized upon the opportunity to integrate technologies into their operational routines for productivity and profitability.  Coca Cola, BP, GE Power, American Express, BMW, Volvo, Walmart, Disney and Microsoft are some of the names on an unending list of companies that are using emerging technologies such as AI and Big data for the business purposes.

Projects live and breathe in a context, be it organizational or extra-organizational. When organizations use a certain technology for its ongoing activities; intentionally or unintentionally it influences adhoc organizational activities too. Projects being one of the adhoc activities, therefore, often get thrust into a situation where they may need to adopt technologies being used by the parent organization.

Given the above, the question then is, can AI well be used for project management (PM) or Using AI for project management is still just a good bedtime story?

Since AI technology is still evolving and undergoing further developments, hence it may be premature to form a firm judgement about if and how AI can be used in PM. However, to develop some initial understanding per se, we can look at some of the possible uses and roadblocks towards use of AI in PM as discussed below:

Possible uses of AI in PM

1. Robot-assisted preliminary and detailed drawings

Use of AI can be beneficial for preparation of preliminary and detailed drawings tasks in projects. While the task may seem of routine nature, it is at the core of the success of projects (particularly product development projects) and the product being created by the project.

Preparing drawings for projects such as construction, health care machinery and instruments, IT hardware development, heavy-duty machinery, ship building, aviation products, space exploration and supporting infrastructure, just to name a few, could be very complex.

Using AI technology for drawings could help in innovations, improving quality of planning, minimizing errors and resultant risks, achieving execution efficiencies and facilitating consideration of complex interaction among a large number of variables to develop the optimum drawings.

AI provides unparalleled power to perform complex computations and make decisions far beyond the computation and processing capabilities of human beings. Therefore, AI technology can overcome human computational limitations to develop project drawings/plans ultimately saving costs, time and minimizing risks.

2. Simulated risk assessment and management

Risk management often does not receive the attention it deserves, despite the far-reaching impact it has on the outcome of projects. It is often considered additional work that is driven by subjective assumptions and chance.

AI can help alleviate some of these challenges in project risk management by simulating the project environment to facilitate objective risk assessments and prioritization. The robot-assisted risk management can enable identification of trigger events and risks, assignment of severity and impact scores to identified risks, and development of optimized risk treatment protocols. AI technology can facilitate risk status monitoring on an ongoing basis and perform simulated assessment of risks in real time to keep risks profiles current and relevant on an ongoing basis.

By using AI, projects can benefit by reducing their risk exposure, re-defining risk management philosophy by inducing some objectivity into a task considered mundane and subjective by project staff, and improving chances of successful completion of project as per client requirements. Artificial intelligence-based risk management could be very useful for large projects, in particular.

3. Fraud detection and prevention

According to a global study by Association of Certified Fraud Examiners, several industries including Construction, Technology and Energy face a variety of occupational frauds and abuse (http://www.acfe.com/report-to-the-nations/2018/). Another report published in 2013 suggests that the fraud in global construction industry alone could reach $1.5 trillion by 2025 (Bottari, 2013).

AI can help detect and minimize project-based frauds. Using AI technology, projects can minimize or eliminate various types of frauds, such as: over estimation of time and cost, billing frauds, bid/contract rigging, expense reimbursements, fictitious vendors, anomalies in plan vs actual, change order manipulation, resource procurement, and funds management and disbursement (Bottari, 2013). Specially, in large projects plugging loop holes by using AI technology can work wonders for the health of the projects.

4. Workflow management

AI technology can also be useful in design and management of project workflow. Large number of stakeholders’ involvement often lead to gaps in communication resulting in inefficiencies and cost / time overruns. AI technology can help develop optimized project workflow, and constantly monitor and update the workflow. Such an ability will help in removing bottlenecks in work performance and keep the chain of tasks smooth to avoid work pileups.

5. Dashboard monitoring and control

The use of program and portfolio approach to management of projects requires some form of control tower mechanism to monitor and control the progress of projects from a single-window view to achieve program and portfolio objectives. Dash board control is one solution to such needs.

Dash Board monitoring and control can include a number of parameters related to scope, time, cost, risks, procurement, quality, change management, contracts terms and conditions, integration / configuration management, and performance of technologies, equipment and infrastructure being used in the portfolio / program, just to name a few.

The interaction among these parameters could be complex with unknown outcomes. AI-enabled Dash Board controller can help in dealing with these complexities by considering all the possible parameters in real time and making informed decisions to provide control and trouble-shooting efficiencies across the entire project eco-system.

6. Planning and estimation

One of the advantages of using AI for PM is to develop optimized plans and estimates.  Particularly for large projects, a small saving can have a significant benefit outcome. Moreover, using AI technology for planning and estimation of projects within a Program or Portfolio can provide capabilities to consider a host of assumptions, risks, and areas of savings in an integrated manner to develop optimized estimates.

AI technology can also help in establishing stakeholders specific project performance indicators and provide optimized control to monitor performance against those desired set indicators.

Possible roadblocks towards use of AI in PM

1. Cost prohibitiveness

AI is still an expensive technology and may not be affordable to majority of projects. In hindsight, cost to benefit ratio of using AI technology will be too high for the small to medium projects and in many cases large projects even, limiting its use. It may, however, suit very large and mega projects, such as space exploration, oceanography, oil and gas, and energy projects, to name a few.

Another factor that needs to be considered is how much AI can do to help manage projects. Its utility function will define it benefits. If the utility is low, benefits will be low and technology will be cost prohibitive. Therefore, cost prohibitiveness is disadvantageous to use of AI in PM.

2. Dealing with emergence dilemma

Complexity in PM comes from emergence and people management. The involvement of a large number of stakeholders with their varying needs and dynamic human thinking and behaviors make project environments very complex. The question is whether AI technology can deal with such dynamics, particularly as the stakeholders and hence thinking could vary from one project to another project.  If AI technology is not able to handle emergence in PM—which often is the cause of projects failures, then it may limit use of AI in PM.

3. Low benefit-cost ratio

PM is a structured packaged solution to consistently deliver projects successfully. Due to this standardization characteristic, organizations may consider that using AI in PM will be of limited benefits and may not yield desired return given the costs in adopting and maintaining AI. This perception may retard uptake of AI for PM and prove to be disadvantageous for further developments.

4. Confined utility

Since PM is an adhoc business activity, often organizations do not put a lot of effort in building capabilities in PM. Hence, utility of AI may remain confined to few types of organizations that deal with complex or mega projects only. It may lead to a wide-spread non-adoption of AI in PM, stifling AI technology development efforts. The lack of technological developments means costs will remain high with limited functionalities and utility, which will be a disadvantage for uptake of AI for PM.

5. Fit to the context dilemma

Despite a large number of people use PM skills and techniques, yet the acquisition of contemporary PM knowledge and skills remains low. Using AI technology means people working on projects need to have up-to-date knowledge on PM and an aptitude for adoption and use of new technologies. Till that happens, use of AI may be limited to few organizations / tech-savvy individuals resulting in a low uptake of AI overall and will be a disadvantage in long run.

The terminological variations across industries, cultures and linguistics differences are some other factors which could also pose barriers to develop AI technology which can decipher every other jargon and industry, culture-based variations used in PM. It may disadvantage uptake of AI.

Concluding thoughts:

Organizational lives have reached a point where technology-dependent operations have become a necessity rather than a matter of choice. PM is no exception to these developments.

While currently, AI technologies may not be cost-effective and developed enough to be used for PM, but, certainly it does not mean the end of road. In fact, it should mean beginning of efforts to make AI workable for PM, so that PM as a profession is not left behind when AI becomes a necessity for organizational survival.

Reference
Bottari, T. (2013), https://www.aconex.com/blogs/construction-project-fraud-statistics-prevention/#_ftnref3

Authored by:
Professor Jiwat Ram
© 2018 Jiwat Ram, All Rights Reserved.

Source: IPMA

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