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How AI Is Transforming Project Management: 3 Real-World Examples

  • Writer: Lionel Deguy
    Lionel Deguy
  • Aug 1
  • 3 min read

Updated: Nov 14


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Not long ago, artificial intelligence (AI) was limited to research labs and big tech. Today, it is entering organizations everywhere and reshaping the way we work.

Project management is no exception: faced with complex environments, tight deadlines, and cost pressures, teams need new ways to increase efficiency.


👉 According to Gartner, by 2030, 80% of project management tasks—data collection, reporting, tracking—will be automated by AI (ITPro, 2019).


👉 The Project Management Institute (PMI) highlights in its Pulse of the Profession® reports that poor project performance still causes between 9% and 12% of investment waste in recent years (12% in 2019, 9.4% in 2021) (PMI 2019, PMI 2021 PDF).


AI doesn’t replace humans — it augments them. Automating repetitive tasks, detecting risks early, and optimizing resource allocation are powerful performance drivers.

1. Automating Project Reporting and Tracking

Preparing progress reports is a time-consuming activity: consolidating data, checking variances, formatting charts…With AI, these steps are automated:

  • Real-time extraction from ERP, project management, or financial tools.

  • Automatic variance analysis between forecasts and actuals.

  • Dynamic, visual reports ready to share.


👉 Tangible impact:

  • Save several hours every week.

  • Reduce manual entry errors.

  • Faster decision-making thanks to always up-to-date data.


Real-life examples:

  • Independent consultant Rose Thun cut her reporting time by 90%, from 5 hours down to 30 minutes, thanks to a customized AI workflow (SimpleConsultants.ai).

  • Firms like Grant Thornton and EY saved up to 7.5 hours per week per employee by integrating Microsoft Copilot, with 40% of administrative tasks automated and an overall 20% efficiency gain (The Australian).

2. Anticipating Risks Through Proactive Detection

Delays and cost overruns often stem from recurring causes: poorly managed dependencies, underestimated critical tasks, or overloaded resources.AI can analyze past project histories and trigger alerts as soon as weak signals appear.


👉 Examples of detection:

  • A similar activity has caused delays in many past projects.

  • The schedule shows too many critical dependencies.

  • A key resource is over-assigned across multiple projects.


👉 Tangible impact:

  • Early detection of potential problems.

  • Greater accuracy in estimates.

  • Continuous adjustment of mitigation strategies.


📊 The McKinsey State of AI 2025 report shows that companies are already reorganizing workflows to embed AI, particularly in risk management and incident anticipation (McKinsey, 2025).

3. Optimizing Human and Material Resource Allocation

Balancing workloads, accounting for available skills, and handling unexpected changes is a constant challenge.AI helps by:

  • Recommending optimal assignments.

  • Simulating alternative scenarios.

  • Adjusting in real time based on absences or shifting priorities.


👉 Tangible impact:

  • Reduce team overload (Muri in Lean).

  • Boost employee engagement.

  • Improve on-time delivery performance.


📌 McKinsey highlights generative AI agents as the next step: systems capable of autonomously managing complex workflows, including resource reallocation (McKinsey, 2024).

Conclusion

These examples show that AI is more than a buzzword: it delivers measurable benefits — time savings, better risk anticipation, and improved resource allocation.But its real potential lies in the synergy between human and artificial intelligence. Teams keep the creativity and strategy, while AI takes over repetitive analysis. Together, they enable faster delivery, higher quality, and greater profitability.


👉 Curious about how AI can transform your projects?

Contact NYLL today for a diagnostic.


📚 Sources

  • Gartner (2019). AI to Transform Project Management by 2030 – via ITPro

  • PMI (2019 & 2021). Pulse of the Profession® Reports – 2019 | 2021 PDF

  • McKinsey (2025). The State of AI – How organizations are rewiring to capture value

  • McKinsey (2024). Why agents are the next frontier of generative AI

  • SimpleConsultants.ai (2023). AI Reduced Report Creation from 5 Hours to 30 Minutes

  • The Australian (2023). How AI has changed professional services

  • Arxiv (2020). Artificial Intelligence Applications in Project Management

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