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AI, blockchain and IoT convergence improves daily applications

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Blockchain, AI and IoT yet to converge as holy trinity

The scope and architectural designs of any one of these technologies — never mind all three — are truly vast and advancing daily. Each suffers from various limitations, such as lack of interoperability, processing speed for high-volume or mission-critical applications, and different standards. Each offers new design paradigms in privacy and security contexts. Each faces significant legal, political, cultural and ethical challenges relative to incumbent models. Not one individually, nor all three, is a silver bullet for capitalizing on data or data-driven economies, but all are subjects of extreme hype and promise. Nonetheless, there are important caveats that help ground an understanding.

AI, blockchain and IoT convergence
Figure 1. IoT data funnels to AI to improve analysis and feed information to run applications. IoT and AI data can become immutable in a blockchain.

Much depends on the problem. Whether in a business, health or societal context, do not blindly pursue these technologies because they sound innovative. Instead, evaluate the criteria, capabilities and constituencies needed to solve an actual problem. Look beyond organizations to capitalize on ecosystem-based technologies.

Not everything will be registered to a blockchain. It’s unlikely any blockchain will be able or need to capture all data emanating from IoT devices or elsewhere. But there are plenty of device transactions or interactions that warrant an immutable record, including when a car passes through a tollbooth or when perishable cargo reaches a distribution center. What are the events that multiple constituencies in the network need to agree on?

IoT is just part of the big data iceberg. Sensor and device data are just a fraction of the myriad data feeds powering AI. What’s essential is data quality. When it comes to blockchain, however, there are important limitations to current DLT architectures that make that distinction even more important. For example, billions of sensors in an agricultural environment or 1 million cars in a city might cause issues with the scale or connectivity required for real-time reconciliation on a blockchain.