Business Analysis and AI

In a recent chess match during the Candidates tournament, a player - Hikaru - took more than 60 minutes to think on a single move. There were two possible moves that were playable at the position. After more than an hour thinking, Hikaru chose the wrong one and he eventually lost the game. After the game, the US grandmaster accused his seconds (his preparation team) of not having prepared him properly for that specific opening variation. This episodes sheds some interesting light on how AI is used and on the boundaries of that use. You see, all chess grandmasters use computers to analyze openings before a game. The computers, with their immense calculation power - can show the best move in every position. However, the application of that knowledge by a human player on the live chessboard comes with some challenges. One cannot remember of all possible moves and all possible variations - even GMs have a limit. So players at the Candidates level analyze the most possible variations...

The AI systems we use are built on data. Data that are derived from the world we live in. As Business Analysts (BAs) working as trusted advisors towards a better world, our job is still the same in its core. We still work with people trying to understand needs and the best ways to satisfy them. However, with AI, a new dimension is added to this work: We must now also safeguard the way AI systems are trained and the way they produce outputs, so that these outputs are aligned with the better world we all strive for. For example, a new banking screening process should be fair to all. This was true before the advent of AI and it is still crucial in the AI era we live in. In both cases the advisor to the customer should pinpoint potential areas that could generate bias and eliminate them. The BA should work to clarify and establish the criteria used and how their application will result in better decisions. If in the past this was a set of COBOL programs in zOS or if in the future...

Have you used Copilot? Are you using ChatGPT? Do you utilise Manus? Have you tried Lovable? The need to use artificial intelligence today is more and more presenting itself as an urgent need. We, as business analysts, have to use AI tools to improve our efficiency and the quality of our work. To do that, skills like prompt engineering have made their way in the training curriculum of BAs across the world, while a constant pressure to show that you use AI tools is making everyone participate in this gold rush without putting much thinking into the how (let alone the why). Just go out there, open Copilot and start typing! Create agents and start training them! Show results! Site y efficiency gains! And as in the gold rush in Klondike, the people who profit more are not the ones seeking gold but the ones selling the tools. Back then it was about shovels, but now it is about subscriptions and use credits. But even if the tools are now available and we c...

Have you written user stories?  Do you know how to write acceptance criteria?  Have you developed use cases? These topics might soon be obsolete as part of the introductory interviews for junior business analysts. Let me explain why... The advent of AI tools in the field of business analysis (and not only) means one thing: The role of a business analyst (BA) is shifting towards a more advisory role. The BA is not expected to be an expert in writing user stories properly, since this work will eventually be unrtaken by the AI tools. The BA is expected though to have deep knowledge of the customer and its needs, thorough understanding of the product (the business analysis role was for a long time now moving towards a more product-owner-ish role) and, last but not least, the ability to manage the new resources available. The latter, means that the BA will have a managerial role regarding the AI tools available. Like a manager has resources to use, advise and ...