Though often associated with ChatGPT – the rise of which put generative artificial intelligence (AI) on the map – the reality is that AI has been around in some forms for years. Automation of manual tasks, for instance, requires a degree of AI to complete, even if the techniques are as simple as programming software to conduct basic tasks. The same goes for chatbots, which use simple AI to converse with users.
Still, the nascent technology is becoming more advanced, leading to an increased demand for AI-aware project management professionals. The Project Management Institute highlights this, pointing out that 82% of senior leaders believe AI will have “at least some” impact on how they run projects in the coming years.
You may be one of those leaders.
Or you may work for one who is investigating how to leverage AI in a project management context. That’s where this article comes in – read on to discover potential applications of the tech in project management and the possible effects of its implementation.
Example Applications of AI in Project Management
There’s one question that comes ahead of all others when it comes to using AI in project management:
How?
There are some simple answers. Your project management software may use basic AI to help with task assignments, for instance, and chatbots can be useful as the gateways to knowledge banks in your organization. However, those use cases only scratch the surface of what AI can do – the following applications showcase its true potential.
Application 1 – Risk Anticipation and Management
All projects carry a degree of risk, with the most general examples being issues that could cause delays. Getting into more complex projects – such as construction – means risks can expand to include safety, material, and workforce issues.
AI can help with all of them.
Using predictive analytics, AI can simulate scenarios related to the risks inherent in your project. For instance, you can run scenarios in which members of your team become ill – delaying parts of the project in the process – with the AI determining the potential impact of those delays. Does losing a graphic designer for two weeks mean that other key tasks can’t be completed? If so, what are the knock-on effects – both budgetary and time-wise – and how will they affect the resources you’ve assigned to the project? AI can answer these questions, giving you the information you need to form backup plans should a negative situation arise.
Away from predictive analytics, AI can also help you generate risk logs – using data from previous and existing projects – and even brainstorm ideas about the risks you may face.
Application 2 – Intelligent Assistance
What is intelligent assistance in the context of project management?
Imagine using software that’s not just capable of helping you track projects in real-time manually, but can also analyze and provide insight into those projects. Let’s say you have 10 projects running simultaneously and you want to know which are the top five to prioritize. Typically, working that out involves checking each project individually – examining budgets, deadlines, risks, and resources – to figure out which needs the most attention.
With AI in place, you can simply ask the question:
Which five projects should I prioritize?
The AI does the research for you – saving enormous amounts of time – and offers a quick answer backed by reporting.
You may see these functionalities employed in some content creation AI tools. They’re capable of providing real-time insights into your writing, including grammar checks and even research suggestions, based on what you enter into the tool. The same can apply to project management software.
Application 3 – Meeting Transcription and Reporting
Meetings are part and parcel of running a project, with the average American worker spending between three and five hours in meetings per week. That isn’t counting any time spent on creating agendas, writing summaries, or figuring out the action items to take away from the meeting.
AI can streamline the meeting process, saving valuable time in the process.
For instance, the same tech that enables intelligent assistance for your projects can also be useful in highlighting issues with those projects. Those challenges can become your agenda – based on the AI’s reporting – with AI then recording and transcribing the contents of the meeting itself. From that transcription, you can also use AI to generate summaries and create an action plan based on the discussion you had.
All of this takes minutes – rather than hours – allowing your team to follow up on problem areas almost as soon as the meeting concludes.
The Benefits of Using AI in Project Management
With potential applications for AI in project management highlighted – answering the “how” question – you move on to another question:
Why?
In other words, what benefits result from absorbing the cost inherent in implementing AI into your project management processes?
Benefit 1 – Workflow Streamlining
The most common argument for introducing automation into a company also applies to AI – the technology streamlines workflows. You see examples of this in the applications shared above. For meetings, AI can handle transcription, summaries, agenda creation, and developing action points, all of which would typically require time spent on manual work.
The same applies to intelligent assistance – no more time spent trawling through spreadsheets and project data – and risk management. The data is already in your systems or is generated as part of meetings. AI streamlines how you access and report on that data, allowing your team to focus more intently on the project.
Benefit 2 – Empowering Your Team
Speaking of your team, there’s a common misconception to confront with AI:
It’s seen by many as a technology that senior managers use to replace their project teams.
That isn’t the case, at least when AI is used in a project management context. Rather, AI empowers your team by enhancing collaboration (as seen in its uses for meetings) and saving time on tasks that pull a team member’s attention away from the project. For project leaders, the empowerment comes in the form of faster decision-making – enhanced by AI’s ability to parse through and report on data quickly – and more effective management of stakeholders.
Benefit 3 – Risk Mitigation
As mentioned earlier, risk is inherent in project management. It’s how you manage that risk – as well as the team members and stakeholders who might be impacted by it – that’s key to completion. The predictive analysis capabilities of some AI tools enable you to mitigate risk by pulling from data generated by past projects.
For instance, let’s assume your company maintains records on all projects it has completed. Those records are a data bank – which you can use to train an AI model – that provides valuable insights into how you manage projects. What works? What mistakes are you making? How does the company respond to unfavorable situations, such as last-minute changes by clients?
The answers to these questions are all useful in helping you identify risks that could impact projects in the future. After all, you’ve faced the risks before, so are likely to face them again. AI can report on that data, offering predictions for the likelihood of specific risks to occur, so project managers can make more informed decisions.
Potential Effects of Joining the AI Revolution
While the power of AI in a project management context is clear, there’s also no denying that there are challenges to confront when implementing the technology.
Assessment is one.
Attempting to implement AI throughout the entire project workflow all at once can be a recipe for disaster. As with the introduction of any tool, an adjustment period is required – including training and a staggered rollout – that allows your team to familiarize itself with the proposed solution. That adjustment period is also key to testing:
An AI tool that isn’t suited to the job can’t deliver the benefits highlighted here.
You may also encounter change resistance, particularly from employees who subscribe to the misconception that AI exists to replace rather than empower them. This is hardly a new concept – 72% of managers say that resistance to change is a major barrier to success.
That only means you need to take care when introducing AI into the project management fold. Transparency is key – the purpose for the use of AI needs to be crystal clear to your people to ensure resentment doesn’t build up. Expand on the benefits of the technology, especially in terms of saving time and how it allows team members to focus on project-related tasks, to minimize the impact change resistance has.
AI Isn’t a Silver Bullet in Project Management
As with any technology, AI isn’t a “cure-all” for the challenges you face as a project manager. It’s a tool – one you can use to enhance and empower a team that already works well together. It can’t fix a broken team, even if it can improve processes and reporting.
Perhaps that’s the key thing to keep in mind when you start using AI in project management. Any solution you implement needs to have a defined purpose. What are you using it for? Why? How will the technology improve on what you already have? Assuming you can answer those questions definitively, you’re prepared for the introduction of AI into your project management workflow.
