Executive note·Execution & value·2-minute read
Most AI business cases are precise about the technology and understate the business change required to deliver the return.
Manasi Mashru · Founder, Trove Advisory
We know what the software, licences and implementation will cost. The business change is usually less specific.
I was recently reviewing a set of AI initiatives with a client. The use cases were clear and the benefits were quantified. Each benefit also depended on specific teams working differently.
Consider a finance process expected to be 70% automated.
The 70% tells you what the technology is expected to handle. The remaining 30% is where exceptions sit, decisions get made and problems still have to be solved: an invoice does not match the purchase order, a payment looks unusual, a supplier issue needs judgement.
The teams involved need to know when to step in, what decisions they can make and what they are accountable for when the process does not run as expected.
The same applies to speed. If information arrives in minutes rather than days, the value is only realised if someone can make the decision sooner.
The technology is funded against a commercial return. The investment required to change how the business works is often treated separately, through training plans and completion rates.
The question to ask
Before approving the next case, who owns the cost of getting people to work differently, and where is it in the investment case?