How AI is Shaking Up Project Management: The Good, the Bad, and the Wins

We have already discussed AI’s role in project efficiency (see here>>>) and why the human touch is as important as ever (see here>>>). But what are the tangible pros and cons of AI for talent, projects, and organisations?

The Good:

1. Efficiency: AI takes care of the boring stuff, so you can focus on the important work.
2. Smarter Decisions: AI gives you the insights you need to make more informed decisions.
3. Risk Management: AI identifies problems before they escalate.
4. Better Collaboration: AI keeps teams connected, regardless of their location.
5. Personalised Learning: AI helps you develop your skills in a way that suits you.

The Not-So-Good:

1. Cost: Implementing AI tools can be pricey.
2. Learning Curve: It takes time to get comfortable with new systems.
3. Over-Reliance: Don’t let AI replace your critical thinking.
4. Data Privacy: AI requires access to sensitive data, making security a key priority.
5. Creativity Gap: AI can’t match human creativity or emotional intelligence.

Real-World Wins

Here are a few examples of AI in action, inspired by real challenges I’ve seen through working with a range of clients in this space:

Case Study 1: Saving a Global ERP Rollout

A manufacturing client was struggling with a complex ERP rollout across multiple regions. Delays were piling up, and resources were stretched thin. By bringing in an AI-powered project management tool, the team:

• Adjusted timelines automatically as issues popped up.
• Predicted delays caused by regional regulations.
• Reallocated resources to fill skill gaps in key locations.
  The result? The project wrapped up 20% faster, with a 15% cost saving.

Case Study 2: Winning Over Sceptical Teams

A financial services client was rolling out a new customer management platform; however, employees were resistant to the change. Using AI-driven sentiment analysis, the project team:

• Monitored feedback during training sessions.
• Tailored communication to address concerns.
• Created personalised learning paths for employees.
  The outcome? Adoption rates jumped by 30%, and the project hit its ROI six months early.

Case Study 3: Balancing Workloads in Healthcare

A healthcare provider was implementing a new patient records system but struggled with resource allocation. By leveraging AI, the project manager:

• Predicted peak workload periods.
• Balanced team capacity to avoid burnout.
• Automated status reporting to save time.
  The project wrapped up with minimal disruption and a 25% boost in team satisfaction.

The Challenges Ahead

AI isn’t without its hurdles. As we adopt these tools, we need to keep an eye on:

• Bias in AI Algorithms: Make sure AI is used ethically and transparently.
• Change Resistance: Help teams adapt to new ways of working.
• Data Security: Protect sensitive information as AI becomes more integrated.

What’s Next?

The future of project management is all about blending AI with human skills. We’ll see:

• More AI tools integrated into everyday workflows.
• A growing demand for hybrid roles that combine technical and soft skills.
• Project managers are taking on more strategic roles as AI handles the heavy lifting.

For talent, this means staying ahead of the curve. For hiring managers, it means building teams that can thrive in an AI-driven world.

Let’s Get Started

Here’s how to embrace AI:

1. Talent: Utilise AI tools and demonstrate your adaptability in your professional endeavours.
2. Hiring Managers: Invest in training and look for individuals who can effectively balance technical and soft skills.
3. Teams: Foster a culture that is open to innovation and change.

The future is here. Let’s make it work for us.

More about Jane…

Jane Olden is a Senior Associate in the Projects, Transformation & Change division of Barden’s talent advisory and recruitment firm.

Connect with Jane on LinkedIn or at jane.olden@barden.ie.