Like any technology, AI comes with it's own set of risks, from emergence of unexpected capabilities, hallucinations, creative interpretations to unexpected real-world behaviours. 

There's a growing need to track what truly moves the needle for businesses, not just on-time delivery but measurable ROI, customer impact and strategic alignment.

There are 3 key questions every exec should ask at weekly project check-ins. You're getting status updates, you hear what's 'green', but you feel the project is drifting. To shift from status to clarity, you need a different conversation.

Project execution is not just about completing tasks, but about completing them in the most productive way possible.

Navigating AI Adoption: What's your biggest challenge and how do you solve it? Trying to harness AI can feel overwhelming. It's complicated and it's not SaaS, there are key challenges that need to be faced. From decision paralysis and a lack of skills to trying to grapple with infrastructure, ethics, data, security and change management.

If you're about to start leading AI transformation, or AI projects, or even sponsoring AI projects, then this is great tick list to get you started.

Project resource wars aren't just a theoretical issue, they're a real challenge for project managers and teams.

The cost of not re-setting delivery is working hard on the wrong things. It's losing trust before you've even noticed it's gone. It's delay disguised as busy. It's more chaos and less progress, every week.

A project portfolio approach ensures every effort serves your wider strategy. It balances risk and value across all initiatives and ensures every project, programme and team is working towards a unified goal.

So you've decided to jump on that AI train......That's great, but how about your people, how are you going to bring them along with you. How will they learn the skills the company is going to need?

First, clearly define the specific business challenge you're facing. AI is most effective when applied to well-defined problems.

Breakthroughs come from integration: Studies of interdisciplinary AI teams found that diverse backgrounds drive higher adoption and more effective outcomes than siloed experts

The reality is that the rigid application of either Agile or Waterfall rarely fits the messy reality of complex delivery. 

Tech goes live. Nothing changes. Why? The impact? Tech goes live but the business doesn't change. Adoption is low. Outcomes are diluted...

Project failure doesn't happen overnight. But slowly, deadlines slip, teams disengage and momentum evaporates. 7 warning signs to watch out for are:

Successful projects are more than just on-budget and on-time, real value comes from benefits realisation. You can deliver the best project in the world, but if it doesn't deliver the benefits, then it's all been for nothing. Make sure there are measurable benefits at the start of the project, review them regularly and host post-project reviews with Business Owners.

The difference between strategy and success is delivery. Without it, every brilliant idea remains just that - an idea. Brilliant ideas don't deliver outcomes, unfortunately. It's project management that ultimately makes those ideas a reality.

And honestly, most projects fail because of a lack of clarity and alignment, because people can't answer these questions:

On large projects and programmes, keeping track of everyone's feelings, needs, and requirements can feel like an impossible task. And don't even get me started on comms.....it's a lot to keep up with

Deciding on the best projects to deliver business value is never easy and that's no different for AI projects.