She Writes Change

Understand your risks before you go all in for AI. Successful AI implementation needs a clear business case, supported by strong data foundations, and a change management strategy that puts people at the heart.

Want to start an AI project but don't know whether to Buy, Partner or Build? The "Buy vs. Partner vs. Partner" dilemma is not a new one, but in the age of AI, it has become one of the most critical strategic decisions a leadership team can make. Before your data science and engineering teams default to "we'll build it ourselves", it is critical to recognise that this is more than just a technical preference, it's a decision that will fundamentally shape your project's scope,

AI needs to be viewed through the Product lens, as it's never going to be a project, where you go live and walk away. If you treat AI like a project, your AI initiatives aren't going to deliver sustained value.

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.

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.

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.

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.

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

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.

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.

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

"In a recent MIT study on whether LLMs should be used as a therapist that tested model responses to psychiatric symptoms, the researchers noted that LLMs “encourage clients’ delusional thinking, likely due to their sycophancy.”

It's easy to think that 'digital natives' will adopt new AI tools easily. However, the reality is that training, communication and trust are just as critical, if not more so, for AI projects.

𝐅𝐫𝐚𝐦𝐞 𝐲𝐨𝐮𝐫 𝐀𝐈 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠: It’s a business tool, not a side experiment so apply the same strategic intent, and ROI focus you would to any core investment

Using AI, Project Managers and Leaders can create more compelling project Cost Benefit data.

The AI for project management market is predicted to hit $14.45 billion by 2034. Organisations betting on AI for scheduling, risk management, governance, and admin are seeing measurable gains in cost control, agility and oversight.

When AI becomes invisible, how do we stay aware of what we're actually interacting with?