This article from McKinsey makes an important point; Change management will be critical to implementing generative AI
An important conversation missing from many organisations when they are exploring generative AI is how to ensure the change sticks and scales. While it’s normal for companies to be in exploration mode—testing proofs of concept (POCs) and assessing value—there’s a need for deeper focus on the organisational changes required to unlock AI’s full potential. The real challenge lies in understanding what humans need to do differently to adopt, accept, and scale AI effectively. More effort is needed to drive this transformation beyond the experimental phase.
On the technical side, proving AI’s capabilities is just the first step. For those committed to scaling, it’s essential to establish the necessary foundations, like robust machine learning operations (MLOps) to handle model production at scale and a solid data infrastructure to power AI systems.
These are critical conversations, and more organisations need to focus on building the technical and operational frameworks that will allow generative AI to thrive long-term.
In our experience, the catalyst for this is strong governance and a clear leadership of the connection between business strategy, and the power of AI. Unless and until this clarity exists, production efficiency and cost savings are legitimate goals for AI use, but meaningful transformation is not.