Laying the groundwork for AI
Feeling the pressure to adopt AI and deliver data-driven transformation at work?
With 67% of organisations facing budget constraints and resources stretched thin, making smart investments is essential.
In my latest whitepaper, I look at how to set the stage for successful AI implementation. I focus on the 3 key pillars of investment – technology, use cases, and culture – interwoven to drive continuous growth.
By prioritising investment in the area that needs the most attention, you’ll create the tension needed for real progress.
Take technology. It’s easy to get caught up in the latest tools and platforms, but without alignment to your organisation’s specific needs, they’re unlikely to drive meaningful change. Similarly, identifying impactful use cases can be a game-changer, but only if the people in your organisation are ready to embrace and act on the insights those use cases provide. Building this alignment requires deliberate effort, but the rewards – improved services, better decision-making, and increased efficiency – are well worth it.
In my experience, one of the most significant barriers to data maturity is cultural resistance. Change is hard, and it’s natural for people to feel apprehensive about new ways of working. That’s why it’s essential to involve teams early, communicate clearly about the benefits, and provide the training and support they need to succeed. Without buy-in from the people who will be using and relying on data, even the best technology and most well-defined use cases won’t achieve their full potential.
As well as investing wisely, it’s equally important to identify and remove any obstacles slowing your progress. I’ve identified 6 distinct archetypes or personas – each reflecting unique challenges and barriers to progress.
Are you the over-enthusiastic leader striving for ambitious AI goals, or the frustrated creative – excited by the possibilities of data but facing limited support? These archetypes provide valuable insights into why some organisations find it harder to advance, and why progress can stall despite best efforts. By understanding the common challenges each one represents, you gain valuable knowledge to shape your data and AI strategy.
Organisations that understand these challenges and who use the 3 pillar ‘helical’ model to inform their roadmap and guide their investments are naturally positioned to be ready for AI. AI adoption isn’t just about having cutting-edge technology. It’s about being able to strategically apply AI to solve relevant problems in a scalable and sustainable way.
If you’re looking to start or accelerate your AI journey, I’d encourage you to read my full whitepaper. It offers further insights into the 3 pillars and practical ways to tackle the barriers to progress.
