01
What does a credible AI business case include?
A credible business case defines the current process, baseline volume, time, error or leakage, the proposed intervention, implementation and operating cost, adoption assumptions, risk controls and the evidence that will be reviewed after launch.
02
How should a business calculate AI ROI?
Use transparent arithmetic tied to the specific process. For example: current monthly handling time multiplied by loaded labor cost, plus measurable error or delay cost where defensible, compared with implementation and operating cost. Revenue effects should be modeled separately and labeled as assumptions until measured.
03
Which business outcomes can justify AI investment?
Useful work returned to the team without adding avoidable manual steps.
Reduced recurring effort, rework or tool duplication.
More cases, enquiries, documents or transactions handled within the same operating capacity.
Fewer opportunities lost through delay, missed follow-up or broken handoffs.
Stronger control, consistency, traceability or human review.
Better access to the information needed for operating decisions.
04
What ROI claims should be avoided?
Do not treat vendor benchmarks, modeled savings or industry anecdotes as your own result. Do not assume every hour technically automated becomes productive capacity. Adoption, exceptions, review time and ongoing maintenance belong in the model.
05
How does the AI Ownership Audit use economics?
The Audit can rank opportunities using business impact, readiness, dependency, control requirements and economics. The goal is to make funding decisions before expensive implementation begins, not to manufacture a positive ROI number for every idea.
06
When should a business decide not to fund an AI initiative?
Do not fund the initiative when the baseline is too small, the process is not stable, the data or controls are not ready, an existing feature already solves it, or the expected value does not justify implementation and operating cost.
QUESTIONS
Common questions
What is a good ROI for AI?
There is no universal threshold. The required return depends on cost, risk, strategic importance, uncertainty and the alternatives available to the business.
Can we estimate ROI before implementation?
Yes, but it should be a model with explicit assumptions. Realized ROI should only be claimed after the outcome is measured against a baseline.
Does GrowAILab guarantee ROI?
No. GrowAILab can define the business case, assumptions and measurement plan, then help measure actual results.