The Non-Technical Leader's Guide to Evaluating AI Automation Vendors

You decided your business needs AI automation. Within a week your inbox fills with decks: glossy diagrams, infinite “capabilities,” and a creeping feeling that every vendor is selling the same three promises with different fonts.

You are not missing something technical. You are trying to buy production operations change disguised as a software purchase—and most proposals are optimised for excitement, not for what happens on a random Tuesday when the integration breaks.

This guide is a practical filter for Australian owners and senior decision makers who will not write code but will sign the invoice—and live with the consequences.

Start with the outcome, not the acronym

Before you evaluate vendors, write one sentence that would make finance nod:

“If this works, we will reduce X hours per week / cut Y days of cycle time / lower Z error rate in a named workflow.”

If a vendor cannot restate that sentence without adding ten new goals, you do not have a scope—you have a science fair.

Six questions that separate delivery from theatre

1) “Tell me about failures—and what you changed.”

Mature implementers have war stories: scopes that were wrong, data that looked clean until it wasn’t, integrations that broke on an API update. What matters is whether they can explain how they detect trouble early and how they contractually handle rework.

If everything has “gone perfectly,” you are either talking to a team with no mileage—or no honesty.

2) “What is fixed-fee, what is explicitly out of scope, and how do changes work?”

Time-and-materials without a cap is how businesses end up six figures deep with nothing in production. Fixed-fee is not magic; it is discipline. It forces:

A bounded workflow
Clear acceptance tests
A change-control path when you add “one small extra system”

Ask for acceptance criteria in plain English (examples: accuracy targets on a labelled sample set, handling time improvements measured over two weeks, defined escalation behaviour).

3) “What exactly do I receive the day after go-live?”

Implementations usually die in the handoff. Ask for artefacts, not vibes:

Runbook your ops team can follow without a developer
Monitoring that a manager can read (queues, error counts, drift signals—not raw logs as the default interface)
Training plan in short sessions with real scenarios
Support pathway with response expectations and who owns incidents

If the answer is “documentation,” ask how many pages—and who has used it successfully in a business like yours.

4) “How do you avoid locking me into bespoke glue forever?”

You may not care about standards, but you should care about portability and maintainability. Ask how connectors are built, whether multiple models/providers can be swapped, and whether the architecture relies on a single person’s tribal knowledge.

The wider industry is moving toward open interoperability patterns (for example, tooling around the Model Context Protocol ecosystem) specifically to reduce one-off integrations. A vendor should be able to explain their approach without drowning you in jargon—because lock-in is a bill you pay for years.

5) “Show me production references running six months or more.”

Demos are easy. Maintenance is not. References should include:

What workflow is automated
What still requires human review
What broke and how it was fixed
What ongoing effort looks like monthly

If references are all “pilot completed,” you are buying experiments.

6) “What ROI projection can you show me before I sign—and what assumptions is it built on?”

You want a simple model: baseline handling time, expected improvement band, implementation and run costs, payback horizon, and the risks that would invalidate the maths. If a vendor will not quantify, they are asking you to fund discovery indefinitely.

Red flags (walk away calmly)

Scope defined as features (“AI assistant,” “automation platform”) instead of operational outcomes.
No serious human oversight story for customer, financial, or HR-affected workflows.
No monitoring plan beyond “we’ll watch it.”
Mystery proprietary stack with no explanation of portability or exit.
ROI promised as “huge” but refused when asked for assumptions.

How to run the evaluation meeting (30 minutes well spent)

State your one-sentence outcome.
Ask the six questions above.
End with: “What do you need from us in week one to validate feasibility?”

If week one does not include data and workflow access, the project is not serious yet.

You can use this checklist on anyone—including us.

Ready to see how Riverstone Labs measures up? We project ROI before engagements where scope allows, scope workflows in plain English, build with human oversight where risk warrants it, and deliver handoff artefacts your team can run. Book a free assessment—we will show you what we would build, what it costs, and the expected return.

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