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.

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.

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:

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.

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.

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. 

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.

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.