THE BUSINESS AI PLAYBOOK
How to choose an AI model using your business benchmarks
Choose AI models with tests from your own workflows. Compare quality, review effort, response time and total cost instead of relying on public leaderboards.
Discuss with Oliver and his team 
Choose an AI model by testing the complete workflow on examples from your business. Define the quality threshold first, then compare response time, tool reliability, review effort and total operating cost. Public benchmarks can inform a shortlist but cannot tell you whether a model handles your documents, terminology and exceptions. Keep a repeatable evaluation so model changes become controlled business decisions rather than reactions to announcements.
What to take away
- Use your own tasks and acceptance criteria to compare models.
- Compare total cost per accepted outcome, including human repair.
- Re-test when model versions, prompts, tools or input patterns change.
Describe the workload before the shortlist
List what the model must do: classify requests, extract fields, draft explanations, use tools or reason across several records. Note input size, image or audio needs, latency expectations and data-handling requirements. These constraints may eliminate candidates before any quality comparison.
Separate tasks that look similar but have different consequences. Drafting an internal meeting summary and preparing a customer-facing account explanation may require different evidence and review. A single organization-wide model choice can be convenient, but it should not obscure the requirements of each workflow.
Compare on a shared case set
Run candidates on the same representative cases with the same permitted information and a comparable tool setup. Include normal cases, difficult cases and requests the system should decline or escalate. Record configuration details so the comparison can be reproduced.
In a hypothetical document intake test, Model A extracts routine fields quickly but misses conflicts between attachments. Model B takes longer but catches those conflicts more often. The business might route clean forms to a simpler path and ambiguous packets to a stronger review workflow. The decision depends on measured case behavior, not the labels attached to the models.
Count the costs the invoice does not show
Model usage is only part of cost. Include retrieval, tool calls, retries, reviewer time, corrections and the operating support required. Track tail latency as well as an average: a workflow that is usually quick but sometimes stalls may be unsuitable for a live customer call.
Calculate cost per accepted outcome rather than cost per generated response. If a cheaper output needs extensive correction, the complete workflow may cost more. Conversely, a highly capable model may be unnecessary for a tightly constrained extraction task with strong validation. Let the measured result determine the tradeoff.
Keep the selection reversible
Isolate model-specific configuration from your business rules, tool contracts and case records. Maintain a baseline test set and a documented rollout procedure. A replacement model may use tools or follow instructions differently even when the interface appears compatible, so do not treat a successful API response as evidence of equivalent behavior.
Copy-ready comparison brief: “For each candidate, report task acceptance, material errors, review minutes, response-time distribution and total cost. Explain the conditions where it performs poorly. Recommend a default and an escalation path, with the evidence required before changing either.” Revisit the choice when business needs or verified capabilities change.
FROM READING TO ACTION
Your first steps
- Define task requirements and non-negotiable data or performance constraints.
- Create one representative evaluation set with expected outcomes.
- Use consistent inputs and record model and workflow configurations.
- Compare quality, review effort, latency and complete operating cost.
- Document a controlled rollout and rollback procedure for model changes.
What to measure
| Measure | How to track it |
|---|---|
| Accepted outcome cost | Divide all execution and review costs by outputs accepted without material repair. |
| Critical-case performance | Report success on difficult or consequential case categories separately from routine work. |
| Response-time distribution | Measure typical and slow-case completion times for the end-to-end workflow. |
Common questions
Should we always use the newest model?
No. A newer model is a candidate for evaluation, not an automatic upgrade. It may improve some tasks and change behavior on others. Run the relevant tests and assess the operational effect before replacing a working system.
Can we use a cheaper model for routine work?
Yes, if the routing rule and quality checks are reliable. Define which cases qualify for the routine path and how uncertain cases escalate. Test the routing system too, because a good specialist model cannot help a case sent to the wrong path.
Sources & further reading
These sources provide background. The workflow designs are Palnau Systems implementation guidance; examples are illustrative, not reported client results. Product capabilities and requirements can change.
Prepared with AI assistance for business owners and managers. For a recommendation based on your actual systems and requirements, work directly with Oliver and his team.
