How to use AI in the PMO

The biggest danger of artificial intelligence is spending too much time talking about it and not enough time implementing it to get value.

When it comes to the PMO, there are a lot of ways that AI can harness existing knowledge of projects and planning, as well as taking it one step further to data analysis. AI can assist with all the core functions of the PMO.

AI-Generated Schedules

Finding the best way to create schedules for new projects is an art. It should include best practices as well as taking key deadlines and deliverables into account. Traditionally, most companies have relied on predefined schedule templates containing commonly needed phases, milestones, and tasks.

However, this static approach to controlling the quality of a schedule is a thing of the past, as AI can generate highly complex and accurate schedules by analyzing all your available data. With AI, it’s possible to generate schedules with a complete work breakdown structure (WBS) and schedule within seconds.

The more context you provide, the more precise the output.

Simply stating the context as “ERP implementation project with an 18-week duration” could be improved by adding more context, such as “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.”

In Projectum xPM, we’ve added the ability to use AI for planning, along with a score that reflects the likelihood of the AI’s estimation of task duration. Not only can this save project managers time when creating schedules, but it also helps the PMO improve processes and workflows as they connect their experience to the AI’s suggestion. The output can lead to more accurate schedules, better resource allocation, and successful projects.

AI-Generated Risk Logs

Project success often hinges on managing risks. Identifying potential risks allows you to mitigate them and tackle them head-on. Of course, it’s tricky because risks arise in many different areas, such as the business case itself, resource availability, schedule, quality, and more.

An experienced project manager can quickly create a log of potential risks based on their own experience. They can also predict the probability and impact of the risks and explain how to mitigate them in case they become real issues.

However, a second set of eyes might see something that you don’t. And that’s where AI comes in. With generative AI, you can generate a risk log by simply explaining the context of the project and requesting a certain number of risks. Within seconds, the AI populates, categorizes, and ranks the risk log according to the context. It could also be asked to write detailed risk descriptions, mitigation steps, and contingency plans. AI is your assistant that pulls from the combined knowledge available on the internet or your data.

Improved communication with AI chatbots

Communication and alignment are what create success in large organizations – but it’s precisely the size that makes it both essential and difficult.

With internal AI chatbots, you can build your own chatbot using company-relevant data. This could be documentation, procedures, or standards that are important to follow.

This means employees can get the answers they need much faster and be sure that they’re getting the right answers.

There is a wide variety of opportunities to program your own bot, from choosing tone-of-voice to supplying it with different roles depending on the usage.

With Projectum xPM, we’ve integrated an AI chatbot that makes sure you don’t forget anything, creates projects, and gives you insights from project data. But imagination, truly, is the limit. If you have the data, you can do it.