AI Projects and the Business Case Problem: Are We Funding Hype or Value?
Elizabeth is a freelance writer and project manager living and working in London. She runs The Otobos Group, a project communications consultancy specializing in project management.
Artificial intelligence is everywhere in project portfolios. But when nearly 40% of companies* report that their AI cost savings are below 10%, despite business cases forecasting 11% to 20% savings, it’s worth making sure that you are taking on the right projects.
Many AI initiatives lack clear value cases, so are we chasing FOMO and shiny things? Project leaders are often expected to deliver initiatives before the value of new tech is fully understood. Someone needs to ask the difficult questions about projects. Your unique role as a project professional, combined with your business acumen skills, means you can do that.
AI business cases are different
A “classic” business case lays out how to solve a known problem, with solutions like replacing a system, restructuring, reducing costs or meeting compliance and regulatory needs. It’s often difficult to pin down benefits for any project, but at least these have a clear goal.
AI projects can be different because they may deliver indirect benefit. For example, empowering teams with tools that should help them be more efficient, access knowledge in a more structured way, or offload repetitive tasks. These benefits are hard to link back to the project’s outcomes because there might be other factors at play. We might need to rely on assumptions, especially if there are few clear case studies …
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"We are ashamed of everything that is real about us; ashamed of ourselves, of our relatives, of our incomes, of our accents, of our opinions, of our experience, just as we are ashamed of our naked skins." - George Bernard Shaw |
