Project managers’ roles and required skills are changing as a result of the increasing use of AI in project management software. Experts in the field of project management, Hussain Bandukwala and Peter Taylor, discuss how Canadian businesses should prepare their PMs for AI work.
One in three project managers (33%) anticipate increasing their investments in AI by at least 30% by the end of the year, according to a new Capterra study of 2,500 project managers worldwide and 200 in Canada.
Let’s start with the steps below:
AI features aren’t used enough or need to be added in project managment
In order to fully take advantage of the opportunities presented by AI-enabled software and technology, businesses need to prepare themselves and their project managers. They will need to take a look at the project management software they currently use and learn how their project managers are using the tools.
A few easy steps can be taken by businesses to audit their software stack:
- All project management tools and their AI capabilities should be listed in detail.
- Examine the purpose, frequency of use, and user satisfaction of each tool. Collect comments from project managers. You will have a better understanding of which tools and features are crucial and which may be underutilized or redundant as a result of this.
- Examine each tool’s security and compliance. You can guarantee that they meet your company’s standards this way.
- Find out how much support and training each tool has. This will assist you in determining training gaps and scheduling additional resources or training sessions.
Create training project management’s programs that emphasize essential soft and hard skills
Most project managers think that artificial intelligence has a significant impact on the team’s ability to achieve its goals.
In a survey made by Capterra, project managers are asked what soft skills they struggle with. The most commonly mentioned are resolving conflicts (37%), influencing others (30%), and self regulation (30%).
Here are some effective methods business leaders can use to train their project managers:
- Simulations and role-playing games that give project managers a chance to practice in real-world situations and try out different ways to deal with conflicts, negotiate, and build positive relationships.
- Workshops that teach strategies for active listening, understanding different personality types, managing difficult conversations, and creating a collaborative team environment include activities like group discussions, case studies, and interactive exercises.
- Programs for mentoring and coaching that pair experienced mentors within the company with project managers to provide ongoing support and individualized guidance, helping them to address specific challenges, set goals for improvement, and monitor progress.
The increasing use of AI also requires entirely new hard skills, such as data analyses, data management and how to get the most out of the AI-enabled project management tools.
Create safeguards to prevent AI applications from misusing data
The first step is to understand the advantages and the limitations of AI-enabled tools; companies should select the tools based on the goals they want to achieve.
The second step is to create the right data management process. It’s better that business leaders implement a number of best practices to ensure constant data quality, such as:
- establishing the appropriate frame of mind, which includes accepting the fact that change management is necessary to preserve an acceptable level of data quality.
- Don’t just delegate responsibility for data quality to the IT department; instead, spread it across multiple roles.
- Utilize technology to integrate data sources and measure and report operational source data quality.
- Map the relationship between business outcomes, performance, and financial effects and data quality consistently.
Larger companies that want to operationalize data risk management can leverage risk management software, which can be integrated into project management software.
Both the set of skills needed to work with AI tools and their capabilities are always changing. To ensure that they can keep up with new technological developments, businesses will need to make investments in their project manager’s knowledge and skill set.
The next thing you should do is collaborate with the leaders of your company to agree on which insight you will use and when. By anticipating your project managers’ knowledge gaps and the steps you can take to fill them, you can set yourself up for success.
Project management will benefit even more from advancements in AI
The level of AI capabilities offered by project management software vendors varies. However, vendors are rapidly adding AI to their products as a standard part of their offerings.
AI will advance to the point where it can accurately differentiate voices during project meetings, allowing tools to provide increasingly precise summary reports of who said what. Additionally, he anticipates that vendors will make such records searchable at increasingly granular levels by utilizing AI. Montgomery expects large language models to make it easier for project team members to use project management software to perform complex tasks. Using LLMs, those staffers can engage with the software using everyday language rather than writing code.
Cousins anticipates advancements in AI’s capacity planning capability, which is still in its infancy. Technological advancements could also increasingly support other areas where AI is only just beginning to make inroads, such as demand management, resource assignment and prioritization.
In the future, Cousins said, project teams will also be able to use AI to generate synthetic data to further aid predictive and prescriptive analyses. This, in turn, will help project management professionals increase their overall management accuracy, including their ability to audit their entire project portfolios.
By bringing data-driven insights to a task that currently tends to be more subjective than objective, Cousins also anticipates that AI will assist teams in determining when to cancel struggling projects. Additionally, he asserted, AI may have advanced sufficiently to handle numerous responsibilities associated with project portfolio manager and change manager positions. “There will still be a human who has responsibility for [those jobs], but they’ll be massively assisted by AI,” he said.
