Artificial Intelligence (AI) is changing lives and revolutionising the way we work. There is no doubt it will be a key driver of innovation and transformation across Irish businesses and all sectors and occupations, including project management.
Gartner predicts that by 2030, AI could result in the elimination of almost 80% of routine work in project management. More importantly, AI can ultimately boost project success rates.
AI can help to address underlying factors behind poor performance by managing the uncertainty we face in projects. It can help to manage budgets, schedules and risks, and help PMs make better data-based decisions.
However, our Portfolio and Programme Management (PPM) Pulse survey 2018 showed that the project management community has yet to embrace AI. Given this low up-take, practical methods are needed to build up the adoption and experience of AI. Here are five practical ways AI can enhance your project management now.
Proper project planning requires time. Using AI, you can develop a detailed project plan in a shorter time frame, by analysing task lists and timings of previous similar projects.
Taking this a step further, AI can identify efficiencies in the project plan through continuous machine learning. AI can spot inefficient tasks, suggest a better sequence of activities or recommend alternative and more productive tasks. Using AI will help to prevent the misuse of resources and time from the start of a project. However, the dependency here is the availability of quality data and data sets on an ongoing basis.
As projects progress, AI should be able to quickly adapt and react to changes in the project plan as they occur and continuously revalidate the critical path. PMs will have real-time, optimised, and current project plans to guide them.
In the future, small non-complex projects could be autonomously managed by AI. It could plan, assign tasks, track progress and manage project delivery with minimum human intervention.
Estimating is an integral part of project planning. There will be synergies and reduced costs for organisations in applying AI, both in estimating and planning. Estimating can be tricky, and is often subjectively performed. No matter how good the estimate is, there is always the risk of slippage in timelines. This can create a domino effect in the project plan and significantly impact project delivery.
There are many techniques available to PMs when estimating. However, the reality is that they can often find themselves struggling between top-down ambitious timeline targets set by the project sponsor and bottom-up overestimations from team members. This can lead to unachievable timelines or inadequate use of resources, and the project is more likely to fail.
Smart algorithms can present more realistic and objective estimates by looking at the actual effort used for similar activities in previous projects. By matching these with resource availability and productivity, and by taking any other external factors into account, PMs can make more accurate estimates. Basing estimates on real project data also eliminates any unconscious bias that humans often bring.
These insights can be a powerful tool for PMs in managing uncertainty and balancing different views of stakeholders and project team. With more accurate estimates, PMs will have more confidence in their project plans.
The majority of day-to-day project management is about information gathering to aid decision-making. Administrative tasks, such as updating project plans and preparing status reports, can distract PMs from doing what they should be doing: managing their team and delivering the project. The majority, if not all, of these repetitive tasks could be automated or replaced by smart machines.
These small AI improvements would ensure that project data is robust, real-time and transparent. They will also ensure that everyone is accessing the same meaningful information, preventing any miscommunication between the project team and stakeholders.
AI is already a part of the recruitment process for many companies. From preparing targeted job specifications to analysing candidates' resumes, and even anticipating the probability of how successful candidates may be, AI is a useful HR tool.
Similar processes are useful in determining the best-fit resources for a project team. AI can scan through data about staff, their experiences and skill set, and select the people who best match project team roles. It can predict how well resources may interact with each other, as well as identifying competency gaps in a team.
AI can automatically assign tasks depending on productivity, competency and utilisation rates. Predictive analytics can also provide insights as to how long different combinations of resources might take to perform tasks and how that might impact the overall project timeline. This can also help to form the optimal team for project delivery. As the project evolves, AI can ensure the right resources are allocated to the right tasks, optimising resource use.
Risk management is about managing the unknowns in a project. It is an area where AI can make dramatic improvements to project management. PMs don’t know what the future holds. They try their best to foresee what might happen and take actions that will reduce the impact of risks coming to fruition. AI can be the solution that brings objectivity and accuracy to risk management.
Based on their experience, project teams can compile risk logs. Smart machines, on the other hand, can come up with a more comprehensive risk register based on historical project data and by analysing patterns and trends.
When it comes to assessing risks, PMs rely on their subjective judgement on the probability and impact of risks. Predictive analytics can detect threats and issues earlier than a human and can bring it to the PM’s attention for review and action. Given the right data, AI can provide an objective, accurate and real-time risk assessment and alert when risk ratings change.
Further, AI can conduct a root cause analysis that eliminates human bias. This will help to identify more effective actions to prevent risks from materialising or resolve any issues faced in projects.
The first step for organisations looking to introduce AI into their project management functions is capturing clean, relevant and large historical data sets. Does your organisation have a central repository of project management data? If not, invest in digital PMO options that might be suitable. Only with dynamic and robust information can AI learn, find patterns and start making predictions. Almost half of Irish executives recognise this as one of their top priorities.
The workplace of the future is being built on the collaboration between humans and machines. Project management is an art as well as a science. AI may take over the science of project management but will not be able to undertake the art of leading and influencing people.
The project management community needs to start embracing AI and prepare to work with and use smart machines. Project managers with strong people skills and emotional intelligence who can quickly adapt to emerging AI technologies will be the big winners in the future.