We are currently at the beginning of that journey. Following a lull in the pace of development, the last three years have seen applications of AI becoming more mainstream across professional services.
I call this phase “understanding the world.” By that, I mean that AI is getting better at handling, organizing and analyzing a range of inputs; most critically, huge amounts of structured and unstructured data. To a large extent, this is because we now have the critical mass of data to allow that to happen. The digital revolution has created the fuel to feed the AI engine, and its application to a number of narrow tasks is now beginning to yield some very interesting results.
Take, for instance, the issue of lease accounting. This is a hot topic, given the recent accounting changes that demand that companies scrutinize their position with regard to leases and recognize related liabilities.
Until now, analysis of lease accounting has mainly been performed using human review. However, current pilot programs indicate that AI tools may allow the analysis of a larger number of lease documents in a much shorter timeframe. These pilots show that AI tools would make it possible to review about 70%-80% of a simple lease’s contents electronically, leaving the remainder to be considered by a human. With more complex leases (in real estate, for instance), that figure would be more like 40%, but as the tools improve, and the machines learn, it is likely that more complex contracts and data can be read, managed and analyzed.
This illustrates some of what narrow AI can deliver. It cannot, as yet, replace the judgment, skepticism or experience that humans bring to their work. Making comparisons or value judgments is not the function of this type of AI.