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AI is changing many industries and project management software is no exception. AI has the potential to save companies time and money when used correctly. In fact, 96% of business owners see the overall impact of AI as beneficial, according to one survey. AI project management software can improve project workflows and streamline repetitive tasks. However, the risks and challenges of AI need to be fully considered before adopting it. This article covers AI for project management, what capabilities AI has, and the specific challenges to consider before using these tools in your business.
AI and automation are often used interchangeably, but they have different meanings:
Artificial intelligence (AI) refers to machines or software that can make decisions typically made by a human. AI can help provide suggestions, increase efficiency and problem solve. There are many different applications of AI for project management software such as analyzing risks and suggesting mitigation strategies.
Automation refers to software completing repetitive tasks like setting up calendar reminders, taking meeting notes, or updating a project status which can save a team time in the long run.
Here are some of the ways AI is currently being used in project management software. Some of these features are built into project management software like Monday.com, Asana or Clickup. Others are additional tools you can integrate into your current software.
AI tools take project management software one step further with predictive scheduling that takes into account past data, resources, delays and more and integrates this new information into the current project plan. For example, AI can predict whether there is a risk of missing a deadline due to supply chain issues and suggest a new one based on the data.
AI can also help prioritize tasks based on urgency, flag high-priority tasks, reassign specific tasks and identify tasks that are at risk of being delayed. If you’ve ever struggled to organize your schedule in a way that doesn’t have a frustrating number of 30 minute empty blocks, you’ll probably appreciate that AI can also optimize individual schedules. It does this by organizing your schedule for maximum productivity, including the best balance of heads down time and meetings.
The role of project management requires juggling many different tasks, team members, budgets and time lines. Here are some of the advantages of AI for project management software.
By analyzing past and current project data, AI can keep an eye on everything that the project manager may not have time to consider, and analyze issues like delays and risks based on data from previous projects, information a project manager may not refer to on a daily or weekly basis.
AI tools like meeting summaries, reminders and notifications can help make sure the team is aligned. AI can also help identify which team members are overburdened or underutilized, which can help promote a more balanced work environment.
Despite all the benefits of AI in project management software, no technology is too good to be true. There are challenges and potential risks to consider before introducing AI into your project management process and are critical for each company to address. In the last year, more companies have implemented AI safeguards and guardrails, an increase from 62.9% in 2024 to 77.6% in 2025.
AI tools pull from large amounts of data to make predictions and insights. One concern is that AI will have too much access to sensitive data, including past project data, personal information or proprietary company data. This can pose ethical questions or make company data vulnerable to cyberattacks or security breaches.
Implementing AI responsibly will require necessary security measures to make sure data used by AI does not leave the company or team members vulnerable.
Whenever a new tool or system is introduced to a team, it’s safe to assume it will be met with some resistance, and AI is no exception. Resistance to using these tools may come from not wanting to rely on it, distrust for AI, or not understanding how the technology works. There is also potential for team members to become distrustful when AI makes mistakes, like scheduling a meeting at the wrong time or sending a reminder message on the weekend.
The other potential challenge is the training and skills needed to adopt new systems or methods to use AI. Training can require resources and time, which can set teams back in the short term even if it pays off in the long term.
Even when AI is doing so much work behind the scenes, it’s not meant to replace project managers. There is a risk that project managers and the team as a whole will become overly dependent on AI and miss catching the errors that AI will inevitably make. While AI can be helpful, it’s not meant to replace complex decision making that is the job of humans.
AI is still relatively new and is developing fast. What will AI be capable of doing in a few years, and how will it change the landscape of project management and project management software? As you are integrating AI into your company, here are a few possible future directions AI may be heading in to consider.
AI is already making predictions about timelines, potential bottlenecks and recommended actions, but these predictions will likely become more accurate and advanced. For example, AI could become more sophisticated at using historical data to forecast potential outcomes.
AI may also continue to integrate with technologies like cloud computing or the Internet of Things (IoT) devices. For example, AI could provide data in real time about the usage, performance, and maintenance needs of a device. Based on this data, AI could also make predictions about when equipment may fail or need to be repaired, which can help the team avoid potential time or cost delays. AI has the potential to dramatically change project management in industries like construction by monitoring and adjusting workflows in real time based on sensor data from project sites.
There is also the potential that the role of the project manager will change from oversight-based to a more strategic and decision-making role where AI takes on more of the administrative tasks with human oversight. This will free up the project manager to focus on stakeholder communication and foster a strong work culture and team collaboration. Project managers may also be responsible for learning how to use AI tools, determining which tools will be best for the team and training others on how to use them.
Bias is a top concern with AI, since it pulls from historical data and is at risk of inheriting our biases. As more ethical questions come up about AI, it’s possible the role of project manager will also come to be more of AI governance, to ensure AI tools are being used ethically and appropriately.
With so many AI tools on the market, it can easily feel overwhelming to assess which options will be the best fit. A good place to start is understanding your business’s specific needs. What challenges does your company face? Whether it’s related to scheduling, team communication, or risk prediction will inform the steps you’ll take. For example, if team communication is an issue, consider AI tools with workflow automation features could help with that.
You’ll also want to consider how easily these AI tools will integrate into your current workflow. Are there ways to integrate it into the project management software you are already using? How easy will it be to use, who will need access? All the logical questions will play a role in whether a tool gets adopted successfully in a company. Think about how scalable the tool is as your organization grows in the future. Think about how you will adopt this program in your company. Does the tool require training? If so, what kind of training resources will be available and who will be responsible for this? Consider the tool’s data protection policies. What kind of security measures are in place, and which security measures will you need to implement?
Implementing AI into your project management software can be a huge advantage for your business. It can save time on administrative tasks, predict risks and identify budget or timeline issues in advance. However, it’s important to remember the risks of AI, including bias and the potential for the team to become overly dependent on the technology. Regardless of how helpful AI is, the project manager should still oversee its work and be in charge of final approval.