AI: Who Owns the Data
AI is quickly becoming a must-have tool for most organizations. If your organization does not have an AI steering committee it is quite possible that you will be at a disadvantage to competitors that do. I do not believe AI will replace jobs; I believe that people who use AI as a tool to become more efficient will replace those that do not.
The most advanced companies that use AI and have added an analytics layer on top of the data to synthesize volumes of data into usable information. The analytics layer is key, because without it, you pretty much just get retrieval capabilities without the ability to draw conclusions or receive inferences from the data. What is also key and more important; the data must be accurate, normalized, timely and consistent. Making this occur is the job of data scientists.
I googled high paying jobs in demand for the next 10 years and Data Scientist was the second highest growth job in the next decade (behind Nurse Practitioner) at 35.8% with the average job being 5.3% growth(1). Just to double check this, I also went to the Bureau of Labor Statistics which had Data Scientists third in growth in the next decade behind Wind Turbine Service Tech and Nurse Practitioner (2). The reason for this high demand is simple; companies are realizing the value of their data and are utilizing analysis and tools such as AI to draw inferences from them. Image a scenario where you can categorize fallout from leads generated by a third party by salesperson. You may be able to identify a problem in a specific salesperson’s knowledge, sales approach or even identify pricing for a certain product that may be slightly noncompetitive. Your ability to diagnose the problem, provide training or another solution can provide a tremendous revenue boost by reducing fallout- even if only by 1%. I call this fallout attribution analysis, and it is only possible if the data is consistent and correct. The world is changing constantly and the ability to identify a sudden change in the market such as a competitor lowering price by looking at the data can also cause you to move fast and quicker to adapt to changes. Time is money, and the lean and athletic organization that can move quicker than the competition clearly has a competitive advantage.
This can only happen with good data and your data may not be up to par with the demands needed unless you are focused on it. I implemented a high-tech accounting system with AI inference capabilities but knew our data wasn’t good enough to use this technical component of the system (but the rest of the lower-level functionality worked fine). We implemented anyway as the changes necessary to fix the data were painful and part of our legacy procedures – now we had a state-of-the-art system and could successfully lobby for a change in procedures to better utilize the system. To my team, I called this the tail wagging the dog and believed it was the only way to enact the necessary change to utilize this tool to become better. My team was the ultimate consumers of the data; however, we did not enter any of it into our systems. The question of who owns the data has come up constantly. My take on this is that my group, as the ultimate consumer of the data, owns it despite not entering it into the system and, because of this, we need to lead change to make the data more usable tomorrow.
You should be thinking of using AI as a tool today and I recommend forming a steering committee to begin thinking about it if you have not. Simultaneously, you should critically be looking at your data and assessing whether it can be relied upon in its current form. You may need to consider bringing in a data scientist to assist. It’s too late to be ahead of the curve today, but you can still keep from falling behind the pack in utilizing AI.
