There’s an attention-grabbing paradox in information engineering I’ve noticed over the past couple of years.
On the one hand, Knowledge and AI are touted because the new oil. The Knowledge Engineering neighborhood is rising at a rate of knots. Some information engineers are “well-known” and have reported salaries of $600,000. Have to be getting some severe outcomes…
Regardless of this, there are severe issues with information. Knowledge Groups are seen as a cost centre in lots of organisations, many have been let go of throughout 2022. Duplication, or model sprawl, is rife, and governance is on the rise.
Companies can barely make use of their Knowledge, and the notion amongst executives and leaders within the house is that the overall high quality of all this information getting engineered is that it’s quite low; actually not AI-ready.
This results in the “Gold-rush” Paradox:
The “Gold-Rush Paradox” encapsulates the stress between the excessive worth positioned on information and AI (akin to a modern-day gold rush) and the substantial difficulties in making information actually helpful for enterprise. Whereas there’s an inflow of expertise and funding, corporations nonetheless battle with information high quality…