With an adoption that doubled compared to 2017 based on the McKinsey State of AI report, AI is going through a shift.

Initiatives are going past the experimentation phase. Some noteworthy changes in the space include:

• An increasing number of capabilities being used by organisations as part of their AI initiatives.
• An increasing level of investment allocated to machine learning projects, which goes hand in hand with a higher adoption rate.
• More interest in collection, governance and ethics, aiming to ensure compliance for production deployments.
• Stable, secure, scalable tooling is a priority for enterprises. Having AI that enterprises can benefit from is critical.
• AI is more affordable and performant, with needs that are better addressed, tools that mitigate risk and an ecosystem that is better integrated.

How do you navigate these changes in the fast-paced world of AI?

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