She Writes Change

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.

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

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

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.

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