Back in the 1950s, Artificial intelligence was described as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.
Artificial Intelligence systems today will typically demonstrate at least some of the following behaviors associated with human intelligence: planning, learning, reasoning, problem solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity.
Artificial Intelligence is used to recommend what you should buy next online, to understand what you say to virtual assistants such as Amazon’s Alexa and Apple’s Siri, to recognise who and what is in a photo, to spot spam, or detect credit card fraud.
The Business Intelligence landscape has been evolutionary for the past couple of decades now. While there’s no question that today’s most popular platforms are faster, more scalable, and easier to use than they were in the 90s, that improvement has been driven by incremental changes. The overall paradigm hasn’t changed, however—giving people tools to ask a question and making the answer easier to understand.
Artificial Intelligence would in the long-run escalate those changes. For example, the machine learning behind search suggestions can allow end users ask questions without significant training, the usage of a search bar is quite common, for one, and algorithms that pick the best visualization, or decide that the best way to show an answer isn’t a visualization at all, but a table, promises to make the answer easier to understand as well.
But the promise of Artificial Intelligence goes further than just rapidly improving the two existing areas of growth. It also adds a third; helping determine the right question to ask in the first place. For example, Artificial Intelligence is starting to allow Business Intelligence technology to:
Tell you what question you should have asked, instead of just answering the one you did.
Provide relevant, interesting, additional insights about the question you did ask.
Identify anomalies in the data that might be actionable and proactively alert a business person that action may need to be taken—even if they’ve never asked a question about that dataset in the past.
Rather than just augmenting the technical features of a product, today’s artificial intelligence and Machine Learning technology augments the user’s workflow.
As we start to see more vendors who have built artificial intelligence into the core foundation of their product instead of just treating it as an additional feature (“Now with AI!”), we’ll really start to see the value of artificial intelligence’s promise…not just making businesses better, but actually creating new workflows based around answers, not questions.