Focusing on projects that align with business priorities and benefits. Projects must pinpoint business challenges AI can solve, aligning these projects with company objectives, market trends, and customer needs to ensure strategic investment and impactful results.

It is crucial to not just focus on the successful deployment, but also to continuously measure and enhance outcomes . This ongoing process involves analysing performance data, identifying areas for improvement, and implementing changes to optimise AI functionalities. By doing so, organisations can ensure that their AI initiatives remain aligned with evolving business goals, technological advancements, and user expectations. 

Equally imperative to the success of AI projects is the management of risks associated with these initiatives. AI risks can manifest in various forms, such as data privacy concerns, ethical implications, and the potential for biased outcomes. Proactive risk management not only involves identifying potential issues early in the project lifecycle but also requires the development and implementation of mitigation plans. This approach ensures that projects are delivered with technical precision and are ethically sound and aligned with regulatory requirements.