Debunking a Persistent Project Management Myth: It's not just Time and Budget we manage. One of the biggest misconceptions in project management is that PMs are simply “deadline-and-budget enforcers.”  In reality, the best project managers know that success is measured by more than on-time delivery and cost control. While timelines and budgets are essential constraints, modern PMs balance a wider set of priorities, quality, stakeholder satisfaction, team morale, and business

What if your AI wins were hiding in your most boring problems? The real game-changers aren't necessarily the flash AI demos but, instead, the biggest wins could come from using AI to tackle everyday annoyances that quietly eat up your time. Companies that start by automating these boring tasks quickly build confidence and experience. Then, tackling bigger, more ambitious AI projects feels a lot more manageable.

Stop annoying your sponsors: 𝐌𝐚𝐬𝐭𝐞𝐫 𝐭𝐡𝐞 𝐀𝐫𝐭 𝐨𝐟 "𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐄𝐬𝐜𝐚𝐥𝐚𝐭𝐢𝐨𝐧". Escalate too often, and you look incapable. Escalate too late, and you become a liability. Sound familiar? Before even thinking about your sponsor, ask: "Can my team and I solve this without external help?" and "Is this issue significant enough to warrant executive attention?" This shows you respect your own authority and your sponsor's time.

Successful adoption of AI demands more than just technology. It requires the right structure, strategy and ongoing monitoring. I've written up the 10 steps I believe are key to lasting and scalable AI adoption, from choosing the right tasks and tools to managing risks and ensuring ethical alignment. These 10 steps help set the foundation for meaningful, sustainable impact.

Your project dashboard is a sea of green but you know something's off.  Your status updates say everything is on track, your weekly reports are all positive. But you know that it's not accurate. 𝐖𝐞𝐥𝐜𝐨𝐦𝐞 𝐭𝐨 𝐆𝐫𝐞𝐞𝐧 𝐋𝐢𝐠𝐡𝐭 𝐒𝐲𝐧𝐝𝐫𝐨𝐦𝐞!

There seem to be the same two patterns, companies either going all-in on AI (and crash) or avoid it entirely (and fall behind). The smart approach isn't necessarily revolution, instead it's a systematic evolution, experimenting without over-committing.  AI isn't always going to be a system replacement, but a capability enhancement.  Don't underestimate the hidden complexities of integration, data security, and the need for new team skills.

Successful Transformations need 3 distinct voices in the room from day one - Voice of the Customer, Voice of the Employee, Voice of the System.

Not sure how to measure ROI for AI Projects? Traditional ROI models don't work for AI projects. You can't always point to direct cost savings or revenue increases in year one. AI often delivers value in ways that don't fit into a standard business case template. The benefits are real but they are different.

onfused about the difference between Generative AI and Agentic AI? As AI continues to move fast and reshape the way we work, it's crucial to understand the difference. 𝐓𝐡𝐞 𝐊𝐞𝐲 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞? ✴️ Generative AI is reactive and collaborative. Agentic AI is proactive and independent.

You've integrated all your project dashboards into one view. So why is your Steering Committee still confused? I've seen organisations invest heavily in Project software and unified dashboards, integrating every project management tool, all to create the perfect "single pane of glass" view. Then they sit in Steering meetings where executives still ask the same questions: "Are we on track?". "What does this really mean for the business?". "Should we be worried?".

There's been a lot of talk about AI taking over everyone's jobs.  Duolingo, Microsoft, Oracle and IBM all made redundancies in 2024, based on AI being able to replace workers. In 2024 alone, over 150,000+ workers were laid off, with 45% of cuts directly tied to AI automation.

After years of managing technology transformations, I've learned that you cant treat AI like "just another IT project". There are critical key differences, including mindset and approach. AI projects aren't traditional tech projects with a new label. They operate under fundamentally different rules:

How do you build trust when AI isn't 100% certain? Your board expects certainty, BUT your AI delivers probability. AI adoption is different to SaaS platforms and their 'deterministic systems'. But people are used to systems that are 100% predictable (think ERP, CRM). AI just doesn't work that way. AI operates in probabilities, not guarantees. And that probabilistic nature isn't a bug to be fixed in the next release, it's the core of how these systems function. I've been resea

A project might tick every box during delivery, on time, on budget, stakeholders happy, but fail to deliver the promised business value months later.  Without post-implementation tracking, you're essentially flying blind.

Whilst AI can handle more of the technical and admin work, the uniquely human aspects of project management become MORE critical to success, not less.

That "move fast and break things" mentality? It's invaluable in early days. BUT what works at 10 people doesn't work at 100.

Why Transformations Fail (and how to save them). Most transformation failures follow the same pattern. The root causes are rarely technical or financial. They're organisational.

Use AI to help you unlock strategic advantage. If you're looking for smarter and faster ways to shape strategy and drive successful outcomes, then take a swipe through the carousel to see 10 ways that AI can help you.

Launching a new digital product across 12,000 retail locations taught me that scale isn't about size, it's about psychology. You can't just double the resources for double the locations. The real challenges are human. Here's what I learnt about scale:

Research shows that companies that invest in innovation consistently outperform their peers, interestingly especially during periods of economic uncertainty.