What the case needs to prove
A strong AI contact centre business case should define the problem, scope, success criteria, cost model, delivery assumptions, and organisational readiness. Agent assist, summarisation, conversational AI, sentiment analysis, quality monitoring, and routing all solve different problems.
Starting with the outcome prevents misaligned investment and gives finance, operations, IT, HR, and the board a clearer basis for deciding whether AI should be adopted now, phased later, or challenged.
Benefits without overpromising
Supplier ROI models often assume optimistic adoption, integration quality, and productivity gains. A useful model tests sensitivity: what happens if adoption is lower, handle-time improvement is smaller, or containment takes longer than forecast?
- Separate hard benefits from softer customer and agent experience benefits.
- Model handle time, first contact resolution, after-call work, quality effort, and containment conservatively.
- Include change, training, governance, data, knowledge, and integration effort in the cost base.
Independent challenge
The common mistake is letting the supplier lead the case. Supplier calculators are useful inputs, but the final business case should be owned by the buyer and tested against operational reality.