**6.2 Challenges in AI of diabetic care**

Though there are many diabetic AI apps and devices everywhere, however, there has been a lower uptake in the long-term engagement of digital health technologies [65]. Even with a slower understanding of technologies, digital data collected from diabetic patients is growing exponentially. Data is the key to creating better AI insights, but it can be very easy to get exhausted by big data. Besides, data collected by wearables has constraints around their integration into existing systems. It also raises concerns about data privacy, security, and even legal hurdles.

Our ambition should be to create comprehensive and relevant solutions to enhance the usability of AI-based tools with evidence-based models in collaboration with all stakeholders including patients. Effectiveness will depend on the rapidity of construction and modification of new apps, devices, and sensors according to improve diabetes experience for patients and organizational needs. The resolution of such challenges will depend on adequate scientific research and regulation.
