The true value of cloud-based AI isn’t what you think

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Artificial intelligence is one of those concepts that was hot in the 80s, kind of went away, and now is red hot. Most point to AI’s new features and functions to explain its growing popularity, but it’s actually because public cloud computing has made it affordable. For a few hundred bucks a month you can have some pretty heavy-duty AI systems in place that would have cost millions 10 to 15 years ago.

However, integrating AI with applications, such as banking, medical, manufacturing, and other systems, is actually not where we’re finding the value of cloud-based AI. It’s perhaps the most misunderstood aspect of the value of AI—now, as well as in the future.

I’m talking about AI engines integrated with cloud-based and cloud-oriented management, monitoring, and self-healing services that now take advantage of AI and machine learning.

Those who sell AIops tools these days, especially where AI powers cloudops systems, understand this. Those who buy cloud-based technology, and currently are transferring core systems to public clouds, often don’t. Thus, the end-state cloudops systems and processes are not as valuable as they could be. What’s missing is AI and machine learning.

The points of value are clear to me, including:

The capability of self-healing. AI-based cloudops are capable of learning how things are fixed through matching problem patterns with solution patterns over time. After a while, they can do so automatically and better than humans can. This type of automation removes people from having to fix ongoing minor and major issues and increases reliability. As the cloudops knowledge engines become more experienced they get much better over time. 

Better defense of cloud-based data and applications. Security and AI have long been two concepts related to each other in theory, but often not understood by either AI or security experts. Indeed, AI can allow secops systems to become proactive and learn as they go what constitutes a breach attempt, and how to defend against it.

Opportunities for sharing knowledge. An operationally oriented AI system has a great deal of value but has to learn things over time, which is fundamental to cognitive computing. What if knowledge could be shared in real time? In essence you’d have a smart ops system from day one, benefiting from collective learning and knowledge. This is going to be a larger push in the near future.

The reality is that AI is one of those things that we tend to glamorize. Although we think of science fiction depictions of AI systems, their daily value is more pragmatic and less dramatic.