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Is AI your new best friend? – Top 3 ways to integrate AI into project management 

A virtual superhero that magically unlocks every time management issue and gradually replaces the human’s ability to interpretate nuances and variables in projects – not quite, but close!

Project management won’t entirely be replaced by AI. However, a clever human can get quite friendly with AI if they only know which tools and platforms to leverage, making the combination of human and AI greater than the sum of its parts. 

From initiation to completion, AI-powered tools are becoming essential for driving project success. For a project manager (PM), there are multiple ways to integrate AI into the project framework effectively. Here is my top 3. 

1. Speed up the project from the get-go  

    Ever encountered a project where information and documents are scattered across emails, chats, and cloud storage? Sigh. This is the place where AI can truly assist a project manager in distress: by accelerating the information search process from multiple data sources. Take, for example, Jira and Salesforce — platforms with AI-embedded tools that help project managers quickly access summaries of agreements from the sales process and details of the development pipeline. 

    Instead of spending countless hours hunting down past notes, project managers can use the freed-up time to engage with stakeholders and create meaningful connections from the start. It means essentially that these capabilities allow the project manager’s role to shift from administrative tasks towards more strategic leadership.  

    2. Communicate and be proactive 

      The single most important thing with successful project outcomes must be communication.  The most common project management frameworks (e.g., PRINCE2, PMP, IPMA) truly emphasise the importance of communication and stakeholder reporting. 

      While keeping stakeholders up to date might be crucial and rewarding, it is often still quite repetitive. The AI solution to this challenge is large language models (LLMs) that help generate executive reports and project highlights in the blink of an eye. They can even be adjusted to fit the agreed terminology.  

      Moreover, KPIs and measurable insights, along with predictive forecasts, can shed light on future progress. By adjusting project parameters based on these insights, project managers can easily evaluate different potential outcomes and be smarter in future decisions. From a risk management perspective, having this type of predictive “crystal ball” is extremely useful in mitigating potential issues and shifting the project trajectory proactively. 

      3. Analyse and get insights 

        As the project wraps up, deliverables are ready to be sent forward. However, whether these deliverables include documents or other outputs, summarising the project’s outcome can require many people’s time and efforts. The good news is that AI-generated summaries offer a huge relief in this regard. Beyond summaries, it pays off to let AI analyse even the overall project success.  

        I am only scratching the surface with these insights — the possibilities of AI in project management are endless. While the core principles of project management remain unchanged, AI is reshaping the landscape, shifting our focus away from the tedious tasks of documentation and towards what really matters: delivering true value. 

        Author: 

        Viivi Nissilä, an advisor at the Transformations Centre of Excellence, is an expert in leveraging AI in project and product work. Her expertise spans project management, product ownership, and generative AI projects in the B2B world. With a strong data background, she bridges the gap between business and technology, successfully guiding data and AI projects. 

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