Do you recognize these challenges of AI?
Many organisations see the opportunities of AI, but in practice it proves more difficult than thought. Teams struggle with the question of which AI tooling best suits their processes, and how to deploy generic models without losing their organisation's specific knowledge. Data is scattered across different systems and linking to AI often feels like a complicated puzzle with privacy, security and compliance always in the background.
In addition, the internal expertise to implement AI structurally is sometimes lacking. It sticks to pilots and prototypes that never fully come to life, even though everyone feels that added value is possible. And even when an AI solution is up and running, the question arises of how to manage, monitor and safely scale it up without jeopardising processes or data.