Will Artificial Intelligence Replace the Business Analyst Job?
Disclaimer: I had a dream about this last night, but the warranty expired on my crystal ball while I was sleeping. When I started it up this morning, it just responded “NFI”.
According to the online handbook, that means “No Idea” – and it doesn’t say what the F stands for. Since I’m flying blind now, the least I can do is share a couple of thoughts on the topic from my non-functional-crystal-ball perspective.
Machine Learning Needs a Problem
For starters, I’d say we have nothing to worry about, at least not until later today. I could stretch that out to 5 – 50 years of relative job security, but I am not taking any bets after that.
Seriously, I think Business Analysts are going to be more in demand than ever to help the world figure out how to take advantage of AI. For example, take this description of Machine Learning (one of the pillars of modern AI):
“Machine learning tools excel when they can be trained to solve a problem using vast quantities of reliable data…” (Artificial Intelligence: The Insights You Need from Harvard Business Review (HBR Insights Series).
Well, who is best qualified to define business problems?
Right, your intrepid Business Analyst.
S/he may need to hone the ability to express the business problem in the best form for the machine to learn the right answers, but the basis is certainly there.
After all, we have been teaching and practicing business problem definition techniques for centuries (All right, decades, but they sometimes feel like centuries).
The Business Analysis Future is Brighter than You Think (I Think)
As Devin Fidler, research director at the Institute for the Future is quoted saying in the same source, “As basic automation and machine learning move toward becoming commodities, uniquely human skills will become more valuable.” Ta-da! There we are again; I just love the idea of becoming more valuable (my next raise is coming soon to an employee near you).
I believe that the Business Analyst of the future is more likely to be drowning in data, so another survival tactic is to learn how to best evaluate alternatives. AI can uncover a plethora of potential relationships in data, but it still struggles distinguishing between correlation and causation as Kalev Leetaru points out in his Forbes article.
That kind of implies what is needed is some serious ANALYSIS work. Gee, I wonder who is best qualified to deliver that? Again, we may need to tweak some of our skills, but I have the feeling that we are going to be able to make a more-or-less honest living for quite a while.
Meanwhile, I’ll check online for a new Crystal Ball. I hope they have upgraded the features on the newer models; my old one never was all that reliable, anyway.