Is artificial intelligence overused? Perhaps it was initially when cloud computing providers began to offer AI as a service. The cloud made it cheap and readily available to solutions developers. As a result, AI found its way into applications that did not require AI capabilities and the solution ended up less valuable. It’s like putting high-end, high-cost racing brakes on a subcompact car. The car will stop just fine with stock brakes; high-end models just waste money and resources.
These days we better understand the pragmatic use of AI—when it will prove worthwhile and when it will not. Business solutions that typically find the most value with cloud-based AI include:
Business applications with potential patterns in large amounts of data. These can be new patterns from new data, or new patterns that emerge based on what an AI engine already processes and learns over time. The more data that gets analyzed and the more patterns the AI system identifies, the better the AI engine gets. We see this in our daily lives: Our cars learn from our driving patterns to accordingly adjust braking and acceleration. Smart thermostats determine better patterns of use, adjusting temperature based on past preferences and current weather.
The creation of new data and/or understanding. Retailers leverage online recommendation engines to better determine who they are interacting with and suggest products and services the user will likely purchase. Based on customer behavior, these engines can determine the customer’s demographics, such as age, sexual orientation, income, location, and even the amount of education and if they have a spouse or kids. These engines can increase sales, often by 20% or more. This “educated” method of enticing you to purchase additional products weaponizes AI.
An existing data set combined with AI’s ability to determine new meaning. This is why AI exists in the first place. Most enterprises realize they have valuable data, but they have not figured out how to mine its value. Data is at the heart of all AI-enabled systems but is rarely noted as such. If you understand that there are better ways to learn from your business data and gather information that is not necessarily obvious, then you can grasp the value of AI and the cloud.
Notice what you’re not seeing. You’re not seeing standard business applications with embedded AI systems, no matter if you need AI or not. I’m seeing AI in business tactical systems where the value of AI is just not there. This increases your cost and risk.
Traditional ways of defining application logic and behavior work just fine, and you’ll save the additional cost of using AI, which is about 35% more. Yes, even in the cloud.
Enterprises need to deal with the realities of AI: Just because you can does not mean you should. I hope that many of you are asking this exact question as technology becomes more accessible and thus allows us more opportunities to make mistakes with it.