Feature
Vendors have spent the last few years rapidly introducing a range of generative AI features into the workplace software applications and products we already use. Sometimes it's hard to think of a platform that doesn't have some sort of AI-powered feature or integrated service from one of the main large language models (LLMs).
While some of these GenAI features can feel a little AI-for-the-sake-of-it, project management software is one class of application where the addition of generative AI makes a lot of sense.
Projects can be complex, large and resource-intensive, but they also have structure. GenAI offers a range of features that help drive efficiency and productivity — from project set-up through to support analysis and reporting — to support project managers (PMs) to keep a project to time and budget.
Project management software is a mature market with a range of well-established products. From its original foundations in Gannt charts, task management and Kanban boards, project management solutions have expanded into wider productivity suites, taking in aspects of collaboration, workflow automation, data management, document management, knowledge management and data visualization.
How Is AI Supporting Project Management?
Generative AI features in project management software tend to focus on a number of uses:
- The generation of text to create project plans, tasks descriptions and at times, responses.
- Improving and translating existing text in any of the above.
- Automated intelligent summaries and reporting, for example on project status.
- Answering questions or carrying out project-related actions based on natural language queries.
- Streamlining and automating project set-up from less structured artifacts such as meeting notes and even discussion threads, in particular creating tasks and sub-tasks based on these sources.
- Intelligent suggestions for opportunities for the creation of automation, workflows and apps, with the ability to then set these up.
- Analysis across different aspects of a project, for example covering risk assessment, roadblock analysis and sentiment analysis.
- The ability to configure specific AI prompts or actions as suggestions for users.
- Specialist features, depending on the particular product, such as automating aspects of data management.
Shared Characteristics of AI-Driven Project Management Software
The AI features in project management software tend to share a number of characteristics.
Firstly, vendors tend to brand what might essentially be a bundle of disparate AI features. For example, monday.com has monday.ai, ClickUp has ClickUp Brain and Wrike has Wrike Work Intelligence. With potential high interest from customers, vendors are keen to stress their AI credentials, so this type of branding and packaging comes as little surprise.
Secondly, data privacy is guaranteed. None of the data entered by a client is then used for training AI models either by the software vendor or by the third-party who owns the LLM. ClickUp, for example, assures customers about its agreements with third-parties to ensure client data is neither retained or used for training.
Thirdly, the AI is available either as a paid-for extra, or as part of one of the subscriptions. While AI features are not typically included in freemium versions, it appears to be available for most users.
Fourthly, the vendors are basing these features on some of the most widely known LLMs. OpenAI appears to be driving most of the integrations with Monday.com, ClickUp, Wrike and Asana, although the latter also uses Anthropic, the provider behind Claude. This will likely evolve due to the volatility of the LLMs and solutions space, as the recent Deepseek debacle has shown. Indeed, some of the project management solution providers state that their models are constantly updated.
Finally, the set of features currently on offer are almost certain to expand, as AI functionality progresses and becomes a core requirement for businesses looking to acquire project management software.
Let’s dive into some of the specific solutions.
Monday.com: monday AI
Monday.com is a popular project management and productivity solution founded by Roy Mann, Eran Kampf and Eran Zinman in 2012. Originally launched as “Dapulse,” the product rebranded to monday.com in 2017. The company is headquartered in Tel Aviv, Israel.
The company’s AI offering is branded as monday AI. Monday AI is designed to “handle your team’s grunt work, and turn your data into actionable insights.” It leverages the Azure OpenAI as its service provider, but stresses it could use other LLMs in the future. The solution is currently available for customers on “Pro” and “Enterprise” plans.
Monday.com’s AI features are integrated throughout the product and allow users to choose a number of pre-set AI actions. Some of these involve content generation and manipulation, including the ability to translate content as well as improve text. It’s also possible to summarize and reduce large amounts of text to a set of bullets, for example.
Other actions center on organizing, managing and automating data. For example, the “Categorize” action allows users to analyze and categorize volumes of data into tables and then tag it with different criteria, such as analyzing a list of outstanding or upcoming tasks to then automatically tag by task type, or perhaps level of urgency. A similar exercise could be carried out to a list of requests or tickets to then assign to the right person based on the task. Users can automate these tasks and workflows too by creating custom actions or AI apps.
The built-in sentiment analysis in monday AI can analyze the sentiment of free text and then summarize these points in a table with a sentiment flag for each point.
As with some of the other solutions, monday AI can also extract actions from text such as meeting summaries or notes to suggest sub-actions, which can then be assigned in turn.
Customers can also create their own default custom actions using natural language to support automation and workflows, which can then be triggered when selected. For example, you could set the platform up to automatically summarize any meeting notes and extract suggested tasks whenever the action “Turn meetings into tasks” is chosen.
Beyond this, an “AI assistant” app allows developers or more technically-minded admins build a custom AI app to access and use different features across the platform. The app could create documents with a particular template, export data or even integrate a voice assistant. Anyone interested in further development can use monday.com’s API.
ClickUp: ClickUp Brain
Zeb Evans and Alex Yurkowski founded ClickUp in 2017 in San Diego. The SaaS-based project management and productivity platform presents itself as an all-in-one solution with a number of workplace capabilities including project management tasks, collaboration, whiteboard and chat features.
ClickUp’s AI offering, ClickUp Brain, claims to be “The world’s first neural network connecting tasks, docs, people, and all of your company’s knowledge with AI.” The offering is based on OpenAI models and is available as a paid add-on to existing subscriptions.
ClickUp Brain features three main features: AI Knowledge Manager, AI Project Manager and AI Writer for Work. The latter's writing assistant generates content, fixes spelling, does translations and also writes messages from shorthand notes. It also includes voice and video transcription. Some of the writing capabilities can directly help with aspects of project management, including the ability to create tables to summarize data, and the ability to generate templates for different tasks, documents and project plans.
In terms of project management, the AI automates various aspects, including the ability to generate progress and status reports. For example, you could ask for a progress update over a specific time period, and it could share if the project is on time, major recent updates, actions which are about to take place, and so on. This potentially can save time on project reporting and even stand-up.
The generative AI features also support project management set-up using natural language to create tasks and automated workflows, or to automatically generate sub-tasks in a project from passages of text or based on as little as a title. Additionally, ClickUp Brain has specific add-ons to ClickUp’s chat features, including the creation of summaries of chats, the ability to extract and create action items (tasks) from conversations and to query past chat threads.
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Perhaps the most unusual AI service ClickUp Brain offers is the ability to ask questions and get answers based on any wiki, project, document or people information that is connected to ClickUp. This could be questions about the project, but potentially related to other sets of documents and knowledge bases. The AI can also cover data sources which are connected to ClickUp with connectors covering popular apps like GitHub, G-Drive, Box, Confluence, Salesforce and Slack. This service claims it can produce “instant, accurate answers,” although as always, the answers are only as good as the content that is feeding them.
Asana: Asana AI
Asana is a well-adopted work and project management SaaS platform launched in 2012 by Dustin Moskovitz and Justin Rosenstein. The company is based in San Francisco.
Asana AI promises it can “Automate manual work, get insights on what to prioritize, and adapt workflows to your organization’s evolving needs.” It’s suite of capabilities are based on LLMs from OpenAI and Anthropic. Asana AI is currently available in all of Asana’s paid tiers, but not currently in the freemium version. Some elements, such as AI Studio, are available at additional cost.
Asana AI stresses the opportunities to streamline project management and accelerate and automate workflows through the project cycle. For example, the AI can automatically analyze an intake form and ask the requestor for more information if necessary; this could be used to collate requests for assistance, feedback or information through a project, for example.
Like some of the other solutions, the AI automatically generates status updates, and users can get a summary of progress through natural language queries. Users can also ask the AI to analyze risks, identify roadblocks and so on.
The ability to generate text is of course a feature here, as it is with all the other solutions. The AI can also help with project set-up by automatically creating descriptions and tasks and tag projects with particular fields. Project team members can also create written responses to questions or tasks within Asana, and then vary the tone, for example.
The AI Studio add-on allows teams to create custom smart workflows that incorporate elements of all the above. These workflows can then be embedded these into project or organizational processes, helping to drive automation and efficiency.
Additionally, Asana AI can be used to support goal-setting and reporting across different teams. The AI can draft goals for you, then report on them with dashboards and visualizations.
Wrike: Wrike Work Intelligence
Wrike is another popular, highly mature project management tool that has been around in one form or another since 2006. Based in San Jose, Calif., the company was acquired by Citrix in January 2021.
Wrike’s generative AI capabilities and integrations are collectively branded as “Wrike Work Intelligence.” The company bills it as a “self-learning AI and automation engine built for work” which can “make recommendations, reduce mundane tasks and predict outcomes.” Work Intelligence is based on the Azure OpenAI model and is available for all paid-for subscriptions. The lowest level Team subscription does not include the AI-powered risk predictions feature, however.
Wrike’s AI provides the common generative AI capabilities in text generation and improvements, so it can create an outline of a project brief, a campaign plan, details of an event, a meeting agenda or even specific action items. These options and more are offered within the editing interface used for project set-up or when adding further details to an existing project.
A range of editing and translation options are also available, which can be triggered from lists of options such as fix typos, shorten, summarize, change the tone, translate and so on. Further choices such as the language or the type of tone can then be indicated.
One project management feature that is unique to Wrike is an AI risk prediction feature. It can identify risk factors that could delay the project, based on issues which tend to reoccur as well as histories of previous projects.
The AI also flags tasks which need to be completed that might otherwise be lost in discussion threads or other plain text. For example, from some rough notes or text, the AI can automatically create parent tasks and sub-tasks, which has the potential to save a substantial amount of time.
A voice assistant available in Wrike’s mobile app can take spoken instructions.
Wrike’s Work Intelligence also supports automation by making suggestions on aspects of project set-up or project management workflow that could be automated. When a user activates AI suggestions, the AI will analyze repetitive activity, identify a potential opportunity to automate a task (such as adding an automatic comment when a project status changed) and then implement it if instructed to.
What's Next for Project Management?
Given AI's rapid evolution, it's safe to say project management software will continue to integrate new AI features accordingly. Just this week, Monday announced the forthcoming launch of its first AI agent, monday Expert, expected in March. The agent is designed to aid with onboarding into the platform and sharing tips for achieving objectives.
It's inevitable that we'll see more AI agents in the future. These agents could in theory perform even more of the project set-up and reporting for project managers. This could allow PMs to focus on value-add tasks such as the human interventions needed to overcome hurdles and unblock roadblocks, as the AI acting like a member of the project team. The creation of project are also likely to grow increasingly smarter and more reliable. And in extremely complex projects, or in organizations that carry out many projects every year, the AI may be able to spot trends and risks that help to minimize risks, reduce costs and spot roadblocks early.
Whatever happens, if it can help projects achieve successful outcomes, it's a good thing.
