Guide

AI in project management: 12 uses in the tools you already have

This guide is for COOs, project managers and people responsible for the project portfolio in a mid-sized company. We show 12 uses of AI that work today in Microsoft 365, Jira and monday.com, and what each of them requires. You also get an order for introducing them and a list of situations in which AI will not help your projects at all.

Author: Kacper Włodarczyk, CEO of ALGORCOMPPublished: May 22, 2026Reading time: 10 min readArtificial intelligenceFor: Universal
AI in project management: 12 uses in the tools you already have

What AI will not do in projects

Let us start with the limits. AI will not decide which project matters more, and it will not judge whether it is worth accepting a client’s unusual requirements. Nor will it replace a conversation with a team that is tired and needs clear priorities.

AI is good at something else: it reads long documents, records what was agreed in meetings and spots tasks that have been stuck for a long time. It also prepares first drafts of reports. In short, it takes over information work and leaves the decisions to people.

Below, we divide the twelve uses into three groups: information, tasks and planning, and the team. For each group, we name the tools in which the feature works.

Group one: working with information (uses 1–4)

These are activities in which the project manager takes in, rewrites and passes on information. Here AI does the first version of the work, and a person checks it and adds context that AI does not know.

An example estimate: a project manager has eight meetings a week, and writing up notes after each one takes 20 minutes. If AI prepares a draft that only needs 5 minutes of checking, the manager gets back 8 × 15 = 120 minutes, or 2 hours a week. Plug in your own figures.

  • 1. Meeting notes. The tool creates a transcript, a summary and a list of agreed actions with the people responsible. It works in Microsoft Teams (Teams Premium or Microsoft 365 Copilot), Zoom and Google Meet.
  • 2. Summaries of long documents. A client sends thirty pages of requirements, and AI lists the key points, deadlines and ambiguities. Microsoft 365 Copilot or the business version of ChatGPT or Claude will do the job.
  • 3. Status reports for the management board. AI reviews the project board and prepares a draft: what has been done, what is in progress and where the risks are. The manager adds what is not in the system, such as signals from the client.
  • 4. Project documentation. An AI assistant – Rovo in Confluence, Copilot in Microsoft Loop (shared notes in Microsoft 365) or the assistant in monday.com docs – writes first drafts of the project plan, scope description or communication plan.
AI in project management: 12 uses in the tools you already have

Group two: tasks and planning (uses 5–8)

In this group, AI does not make decisions, but it gives the manager better data for making them. There is one condition: the system must have history. AI relies on tasks the team has already completed and on how long they actually took.

If tasks often have no deadlines and statuses are updated once a month, uses 5–7 will give poor results. In that case, you first need to tidy up how the team works in the tool.

  • 5. Effort estimation. AI compares a new task with similar ones from the past and suggests how long it might take. This is a reference point, not a substitute for the team’s judgement.
  • 6. Risk assessment. AI reviews the plan and points to places where similar projects ran into trouble, such as dependence on a supplier or a testing phase that is too short.
  • 7. Early warning of delays. AI compares the pace of work with the deadlines and signals that a phase is unlikely to finish on time. The manager then has time to react before a red status appears in the report.
  • 8. Keeping track of tasks. AI notices a task that has been in the same status for two weeks, or a task with no owner. It sends a reminder and, if that does not help, informs the manager.

Group three: working with the team (uses 9–12)

The hardest part of a project manager’s job is people. AI will not lead the team, but it makes several activities around it easier.

For use 9, good results require up-to-date data on holidays and project assignments. For use 12, the assistant only sees what the person asking has permission to see, so tidy access rights are a precondition for security.

  • 9. Team capacity planning. The workload view in monday.com or planning in Jira shows when people will be overloaded. AI helps spot this earlier and suggest changes.
  • 10. Preparing a retrospective, the meeting that reviews a phase of work. AI gathers the tasks and comments from that period and proposes a list of topics: what worked, what did not and what to change.
  • 11. Translation in international teams. Captions and meeting transcripts in another language (Teams Premium), or on-the-fly translation of comments and documents.
  • 12. An assistant that answers the team’s questions. To a question such as “which tasks for client X are open this quarter?”, AI answers using data from several places at once. This works in Rovo, Microsoft 365 Copilot and the monday.com assistant.
Project manager reviewing a meeting summary and a task list prepared by AI

AI will not replace the project manager in a conversation with the client. It will replace them in typing up notes at 7.30 in the evening.

Summary: what each of the 12 uses requires

The table below helps you choose where to start. The “When it works” column shows whether a use delivers results straight away or only after the data has been tidied up.

12 uses of AI in project management
UseExample toolsWhen it worksWhat to measure
1. Meeting notesTeams Premium, Microsoft 365 Copilot, Zoom, Google MeetStraight awayTime from the meeting to sending the notes
2. Document summariesMicrosoft 365 Copilot, business versions of ChatGPT or ClaudeStraight awayTime to analyse client requirements
3. Status reportsMicrosoft 365 Copilot, Rovo, monday.comAfter the project board has been tidied upTime to prepare a report
4. Project documentationConfluence with Rovo, Microsoft Loop, monday.comStraight awayTime to prepare a first draft
5. Effort estimationJira with Rovo, monday.comAfter a few months of historyDifference between estimate and actual
6. Risk assessmentMicrosoft 365 Copilot, RovoAfter project history has been collectedNumber of risks identified before they occur
7. Delay warningsPlanner (premium version) with the agent, Jira, monday.comAfter a few months of reliable statusesHow far ahead of the deadline the warning comes
8. Keeping track of tasksAutomations in Jira and monday.com, Power AutomateStraight awayNumber of stalled tasks and tasks without an owner
9. Team capacitymonday.com, Jira, Planner (premium version)After holidays and assignments have been enteredOvertime, postponed deadlines
10. RetrospectivesRovo, monday.com, Microsoft 365 CopilotStraight awayNumber of improvements put in place
11. TranslationTeams Premium, Microsoft 365 CopilotStraight awayNumber of misunderstandings and extra meetings
12. Team assistantRovo, Microsoft 365 Copilot, monday.comAfter permissions have been tidied upTime spent searching for information

What Microsoft 365, Jira and monday.com offer

The choice of AI tool depends mainly on where the team already runs its projects. Each of the three ecosystems charges for AI features differently, which matters for the budget.

In Microsoft 365, you pay for a Copilot licence for selected people, and Teams Premium adds extra meeting features. Planner has replaced Project for the web, and its Premium version with Copilot now has an agent that helps with planning and reporting.

In Jira and Confluence, the Rovo assistant is included in paid cloud plans, within a monthly AI credit limit. In monday.com, some AI features consume credits, so the cost rises the more you use them. The prices and rules of these packages change often, so check the price list just before you decide.

How AI is charged in project management tools (October 2026)
EcosystemAI assistantHow you payWhat to watch out for
Microsoft 365Microsoft 365 Copilot, Copilot in Teams and PlannerPer-user licence; Teams Premium as a separate add-onCopilot sees everything the user has access to – review permissions first
Jira and Confluence (Atlassian)RovoIncluded in the Standard, Premium and Enterprise cloud plansNot available on the free plan; the AI credit limit depends on the plan, and usage above it is charged
monday.comAI assistant, agents, AI blocks in automationsAI credits consumed by actionsThe cost depends on the number and complexity of actions – set limits

In what order to introduce AI in projects

Switching on every feature at once usually ends with a discouraged team. It is safer to go in three steps and move on to the next only when the previous one has become a habit.

At each stage, measure one thing before you start and again after a few weeks. That way, the decision on the next step rests on figures, not on impressions.

  • Step 1: meeting notes and document summaries. They require no change in how people work, and the effect is visible in the first week.
  • Step 2: status reports and keeping track of tasks. These require project boards to be up to date. Along the way, the team learns how to write prompts for AI and how to check its output.
  • Step 3: delay forecasts, risk assessment and capacity planning. Launch these only once the team has been keeping tasks properly in one tool for several months.

Data, recordings and security

AI notes require a recording or transcript of the conversation, which is personal data of the participants. Participants must know that the meeting is being recorded. For meetings with clients, it is worth asking for consent at the start of the conversation, even if the tool displays a notice.

Use business versions of tools, where the contract rules out the use of data to train models. Free personal accounts do not give you that control, and project documents often contain client data and commercial terms.

Before you switch on an assistant that searches company resources, check the permissions. If the folder with project budgets is open to everyone, AI will show its contents to anyone who asks.

When AI will not help your projects

AI reinforces the way of working that already exists. If that way is chaotic, AI will only show you the chaos faster. Below are situations in which it is better to deal with the basics first.

  • Projects are run in several spreadsheets and emails, not in one tool. In that case, you first need to migrate to a project management system.
  • Nobody updates task statuses. Delay forecasts based on out-of-date data are worse than an experienced manager’s intuition.
  • The problem is a lack of decisions, not a lack of information. If priorities change every week, no tool will fix that.
  • The team does not trust the tool. Without a few weeks of working with simple uses, you can hardly expect people to believe AI forecasts.

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FAQ

AI in project management – frequently asked questions

Questions that project managers and COOs ask after their first tests of AI.

Will AI replace the project manager?
No. It takes over part of the information work, but it will not take over responsibility for decisions, client relationships and people. Without someone who keeps an eye on priorities and talks to the client, even the best AI summaries will not save the deadlines.
Does a small team need AI in project management?
With just a few people, meeting notes and a document assistant are usually enough. Advanced forecasting features make sense with many parallel projects and a longer task history in the system.
Do we need to change our project management tool to use AI?
Usually not. Microsoft 365, Jira and monday.com already have their own AI features. Changing tools makes sense for other reasons, such as when the current one does not support the way you work – not just because of AI.
How much does AI in project tools cost?
It depends on the ecosystem. In Microsoft 365, you pay for Copilot licences for selected people. In Jira and Confluence, the assistant is included in paid plans up to the credit limit, while in monday.com some features consume credits. Calculate the cost for the people who will actually use it, not for the whole company.
Is it allowed to record meetings with clients so that AI can take notes?
Yes, as long as the participants know about it and the company has a legal basis for processing the recording. The simplest approach is to tell people at the start of the meeting and ask for their consent. Also decide how long you keep recordings and transcripts.

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About the author

Kacper Włodarczyk — CEO of ALGORCOMP

Kacper Włodarczyk

CEO of ALGORCOMP

Kacper specializes in implementing Microsoft 365 Copilot, Copilot Studio, Power Platform (Power Automate, Power Apps, SharePoint) and AI agents for mid-sized B2B companies in Poland. He leads dozens of projects covering AI strategy, Power Platform governance, document workflow automation and sales processes. In his writing he focuses on the practical side of AI adoption in organizations — from the first proof of concept to company-wide rollout — with particular attention to data security, compliance (GDPR, NIS2, the AI Act) and return on investment.

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