How to use generative AI for project management

Project management has always been about balancing creativity with precision. But let’s face it - juggling deadlines, coordinating teams, and foreseeing potential pitfalls can feel overwhelming. The good news is that AI has developed to the point that it can have a tangible impact on how project managers deal with their workload.

In this post, we’ll explore practical ways you can you can use AI to make your project management smoother, smarter, and less stressful. But before we get to that, let’s take a quick look at how AI is used in project management.

How AI is used in project management

Traditional software

AI has been embedded in traditional project management software for quite some time. Common ways you might use AI within software include:

1. Automating repetitive tasks: like scheduling, reminders, and basic project tracking.
2. Allocating resources: using software with integrated AI to analyse available data, such as team member availability and skillsets.
3. Risk prediction: traditional AI systems analyse historical data to predict project risks and suggest mitigation strategies.
4. Budget and time estimates: AI can improve the accuracy of project budget and time estimates by analysing previous projects' data and identifying trends.
5. Performance tracking: project management software often uses AI to monitor milestones, flag potential delays or budget overruns, and generate progress reports.

Generative AI

Beyond traditional software, the use of AI in project management has evolved significantly with the advent of generative AI. While traditional AI in project management was about improving efficiency and accuracy, generative AI is transforming how project managers approach creativity, communication, and strategy in their day-to-day work.

Below we’ll explore some common ways project managers are integrating generative AI into their daily workflows.

Automating routine project management tasks with AI

Task automation is one of AI's most significant advantages to project management. By automating routine tasks, project managers can focus on more strategic aspects of their work that require human skill. Typically, project managers can use generative AI to automate:

• Scheduling meetings
• Generating meeting prep summaries
• Sending reminders
• Adjusting timelines based on project progress
• Generating regular project reports

Using AI for predictive analytics

Predictive analytics is transforming how project managers anticipate challenges and allocate resources. By leveraging AI, you can move from reactive problem-solving to proactive planning, ensuring your projects are better equipped to handle uncertainties. Project managers use predictive analytics and AI to:

• Analyse historical project data to predict potential risks
• Resource allocation: predicting resource needs based on project scope and past project data
• Timeline forecasting
• Success probability

Practical example: Using AI to conduct a pre-mortem analysis

Running a pre-mortem analysis involves identifying potential risks before a project begins, allowing you to prepare and mitigate them effectively. AI can facilitate a pre-mortem analysis by guiding your team through potential failure points and suggesting mitigation strategies.

Here’s how you can do it:

1. Define the project scope and objectives using the help of ChatGPT, to set the direction for the pre-mortem session.
2. Again using ChatGPT, identify potential risks by analysing historical data and project specifics. AI can suggest common failure points based on similar projects and help you focus on critical areas.
3. Ask ChatGPT to generate a comprehensive risk management plan. This plan should categorise risks by their likelihood and impact, assign ownership, and set deadlines for implementing mitigation measures.
4. Monitor and adjust after the pre-mortem, using ChatGPT for help on adjusting to the risk management plan as needed.

Data-driven decision making with AI

In project management, AI enhances data-driven decision making by providing powerful tools that go beyond traditional project planning, cost estimation, and scenario planning. Project managers can leverage AI to:

• Analyse real-time project performance data, predict outcomes and adjust strategies on the fly
• Identify patterns in team productivity
• Forecast resource requirements
• Suggest alternative strategies based on predictive models
• Prioritise tasks by evaluating their impact on project timelines and budgets

Using AI for enhanced communication

Effective communication is crucial in project management. Generative AI can enhance communication by ensuring that project updates, summaries, and important information are shared promptly and clearly with all stakeholders. Here are some ways AI can be integrated into project communication workflows:

• Summarise lengthy project documents, emails, or meeting notes
• Implement AI chatbots to answer routine queries from team members or stakeholders

Practical example: Automate communication with AI-powered project updates in Slack

By using automation tools combined with the power of AI, project managers can keep their team updated in real time, reducing the need for manual updates and ensuring that critical information is never missed.

Here’s how you can do it:

1. Add the Zapier Central extension to your Chrome browser, so you can connect your project management tool to Slack.
2. In Zapier Central, create a bot that can automatically extract key takeaways from your project management tool (e.g., Airtable) and post them to a specific Slack channel. Set up the behavior trigger (e.g., “update Slack”) and define the bot’s instructions.
3. Ensure that the bot is set to send messages to your designated Slack channel. This could be a general project update channel where all relevant stakeholders are notified.
4. Turn on the automation and trigger the bot from within your project management tool. The AI will scrape the necessary data and post a summary directly to Slack, keeping your team updated without requiring manual input.

Using AI for project performance monitoring

AI can help keep project timelines and goals on track by providing real-time insights and analytics that identify potential issues before they escalate. Specific examples include:

• Asking AI to monitor key performance metrics in real-time
• Using AI to analyse team productivity data and identify bottlenecks or areas for improvement
• Sentiment analysis of team comms to assess team morale and identify potential issues
• Analysing ongoing tasks and predicting their likelihood of being completed on time

Practical example: Improve outcomes with AI-assisted project retrospectives

Retrospectives allow teams to reflect on what went well, and what didn’t, and how processes can be improved for future projects. By incorporating AI, you can make this process more structured and actionable.

Here’s how you can do it:

1. Create a retrospective outline in ChatGPT that ensures all critical aspects of the project are covered.
2. During the retrospective, have ChatGPT suggest activities and prompts to engage participants and draw out valuable insights.
3. Consolidate findings after the meeting and generate a report that highlights areas for improvement and actionable next steps.
4. Use the insights from the retrospective to make data-driven adjustments to your processes.

To sum up, generative AI isn’t just a tool - it’s a partner in project management. By integrating the techniques discussed above into your workflow, you’ll not only save time but also make smarter decisions and keep your projects on track.