We know it’s coming. We know it will infiltrate many aspects of our businesses, from supporting the decisions of our staff to engaging directly with our customers either with or without a member of your human resources team. We’ve been told many times that businesses that don’t embrace it will be uncompetitive and risk being left behind.
What is it we’re talking about? As I’m sure you’ve guessed, I’m referring to AI. But here’s a challenge: what is it? While AI as an acronym is increasingly peppering our conversations, it’s in fact a very broad term. I think it’s a term we need to get better at being much more specific about.
Consider the word software. Software has been part of our world long enough that the broad term is not nearly as useful as the much more specific tools we refer to that are all software. DMS systems, word processors, accounting packages, you name it.
We’re early enough in our relationship to AI and machine learning tools that we’re still throwing around the broad term, but we need to start thinking about narrowing our language. This will make us better able to talk about, think about and evaluate AI and machine learning tools that really do have the power to transform our businesses.
So this column is going to start us down that path. Over the next while I’ll frequently use this space to try and add a level of detail or specificity to our discussions of AI, provide some examples, and hopefully add some value to your discussions.
To begin, I’ll share a very basic framework that a business partner of ours provided that gives an overview of commercial AI applications today. Three buckets that help to differentiate the different roles AI is starting to play across the economy:
Analytical AI: Finding patterns in big sets of data. Conceptually, that seems pretty straightforward.
Autonomic AI: They describe it as interacting with systems to complete a process. To add a bit more, think of systems that are self-healing, self-configuring, or self-optimizing. Many modern computer systems are so complex and need to account for so many variables to stay operational that autonomic computing is a critical ingredient in their success.
Conversational AI: Think virtual agents, interacting with humans to complete a process. And let’s not be jaded by the clunky performance of the chatbots installed in many websites. The generation of virtual assistants and agents we’ll see in the next little while will be far more capable than what we’ve seen to date. In some cases they’ll be able to improve a customer experience over what a human-to-human interaction could do in areas that have always been a challenge for customers, like conversations about money.
This is a start, a toe dipped into the AI pond. Frankly, it’s a pretty big pond and it’s growing. But we needed to start somewhere, and I think it will be a lot of fun to learn more as there is very exciting stuff coming your way.
I would love it if you could help me shape our explorations.
You may want to focus on the areas of your business that will be impacted and what the operational aspects look like. You may prefer to get more examples of AI-based products and the companies behind them.
Let me know what questions you most want answered about AI, and we’ll make sure we help find you some answers.
Please note that the real Niel will be back next time. For now, I hope Nielbot, the automated magazine publisher, has been helpful.
