How to Evaluate AI Automation Vendors: An Advisor's Framework

A client last month asked me to evaluate three automation vendors for their business. All three had polished websites. All three claimed AI expertise. All three proposed a 6-figure engagement within the first two calls.

One of them could not explain how they would map the client's existing workflow. Another proposed a tool stack without asking what systems the client already used. The third wanted a 12-month retainer before delivering any measurable result.

None of them passed the evaluation framework I use with clients. The market has over 12,000 automation agencies as of mid-2026. Roughly 80% of them launched after January 2024. The barrier to entry is a website and a Zapier account. The barrier to quality is much higher.

This is the framework I use. Six scoring dimensions, a weighting system, and a pilot protocol. It works for any automation vendor — boutique agencies, platform providers, and enterprise consultancies.

Dimension 1: Discovery methodology (weight: 25%)

This is the heaviest weight in the framework because it predicts everything that follows. A vendor with a rigorous discovery process will build something that fits your operation. A vendor without one will build something that fits their template.

Score 1 (poor): No structured discovery. The vendor proposes a solution in the first meeting based on a verbal description of the problem.

Score 2 (below average): A questionnaire or intake form. The vendor asks standardized questions but does not observe the workflow or interview the people who run it.

Score 3 (average): A discovery call with follow-up questions. The vendor asks about the workflow but does not produce a documented process map before proposing a solution.

Score 4 (good): A structured discovery phase of 3 to 5 days. The vendor interviews the team members who run the workflow, documents the current process step by step, identifies exceptions and edge cases, and presents a written process map before any build begins.

Score 5 (excellent): Everything in score 4, plus the vendor quantifies the current time cost per step and proposes a measurable target (hours saved, cycle time reduced) before the build starts.

I learned this at KPMG, where no governance framework was designed without mapping the process it would govern. The same principle applies to automation. If the vendor has not documented your workflow in detail, the solution is a guess.

Dimension 2: Technical credibility (weight: 20%)

Technical credibility is not about having the fanciest stack. It is about being able to explain why they chose the tools they chose — and acknowledging the trade-offs.

Score 1: The vendor cannot name the specific tools or platforms they use. "We use AI" with no further detail.

Score 2: The vendor names tools but cannot explain why those tools fit your use case specifically.

Score 3: The vendor explains their tool choices and demonstrates working knowledge of the platforms. They can speak to limitations.

Score 4: The vendor has built workflows on multiple platforms (Zapier, Make, n8n, custom code) and selects based on the client's needs, not their own preference. They explain trade-offs clearly.

Score 5: Everything in score 4, plus the vendor has direct experience with the client's existing tool stack and can demonstrate prior work with those specific integrations.

Dimension 3: Scope control (weight: 15%)

The best predictor of a failed automation engagement is scope creep. A vendor that proposes a broad, multi-workflow project on the first engagement is either overconfident or padding the contract. Good vendors start narrow and expand based on results.

Score 1: The vendor proposes a multi-month, multi-workflow engagement from the start with no option for a smaller entry point.

Score 2: The vendor offers a smaller scope but structures pricing to make it uneconomical (e.g., a $15,000 minimum for a single workflow that a solo consultant could handle in 2 weeks).

Score 3: The vendor offers a single-workflow engagement at a reasonable price point but does not define clear success criteria.

Score 4: The vendor proposes one workflow with defined success criteria, a timeline of 2 to 4 weeks, and a clear decision point for expansion.

Score 5: Everything in score 4, plus the vendor explicitly defines what is out of scope and provides a written change-order process for scope additions.

Dimension 4: Results measurement (weight: 20%)

A vendor that cannot tell you how they measure success has no way to prove they delivered it. Results measurement separates service providers from vendors selling hours.

Score 1: No defined metrics. The vendor describes success in vague terms ("your team will be more efficient").

Score 2: The vendor mentions metrics but does not measure a baseline before the build starts.

Score 3: The vendor measures a baseline (current hours spent) and reports on the outcome after delivery.

Score 4: Baseline measurement, post-delivery reporting, and a defined monitoring period (30 to 90 days) where the vendor tracks whether the automation holds under real conditions.

Score 5: Everything in score 4, plus the vendor ties some portion of their fee to the measured outcome. Outcome-based pricing is still uncommon, but the vendors that offer it have strong incentives to deliver.

Market benchmark: outcome-based engagements for workflows recovering 10+ hours/week typically run around $5,000.

Dimension 5: Team and experience (weight: 10%)

Score 1: No information about the team. The website describes capabilities but not people.

Score 2: Bios are available but the team's experience is primarily in marketing, sales, or unrelated fields.

Score 3: The team has relevant technical experience (automation platforms, integrations, API development).

Score 4: The lead has operational experience — they have managed teams, run processes, or built systems inside an organization with real operational complexity. Technical skill plus operational judgment.

Score 5: The lead has a track record at recognizable organizations, with specific examples of systems built and outcomes delivered. References are available.

Dimension 6: Post-launch support (weight: 10%)

Score 1: No post-launch support. The vendor delivers the workflow and moves on.

Score 2: Email support for a limited period, with no defined SLA or response time.

Score 3: A defined support period (30 to 60 days) with a response-time commitment for issues caused by the vendor's build.

Score 4: Support period plus proactive monitoring — the vendor checks the workflow's health, not just reacting when something breaks.

Score 5: Ongoing performance reporting, proactive monitoring, and a structured handoff process that trains your team to maintain the workflow independently after the support period ends.

The pilot protocol: what to test before committing

Scoring a vendor on paper is necessary but not sufficient. Before signing a full engagement, run a pilot. Here is the protocol I recommend to clients.

Pick one workflow. Choose something that matters but is not mission-critical. A weekly report, a lead routing process, or an internal scheduling task. Something that runs frequently enough to generate data within 2 to 3 weeks.

Define the baseline. Measure how long the workflow takes today. Count steps, count hours, count errors. Write it down. If the vendor does not ask for this baseline, they are not planning to measure the result.

Set a 3-week timeline. Week 1: discovery and mapping. Week 2: build and testing. Week 3: live operation with monitoring. If the vendor cannot deliver a single-workflow pilot in 3 weeks, their process is too slow for the scope.

Measure the outcome. After week 3, compare: hours spent before versus after. Error rate before versus after. Team satisfaction (ask the people who used to do the work manually). If the numbers are better and the team trusts the automation, expand. If not, you have invested 3 weeks and learned something useful about the vendor.

Evaluate the working relationship. How responsive was the vendor during the pilot? Did they communicate proactively or only when you asked? Did they document what they built? Could your team explain the automation to a new hire? These qualitative signals predict how the relationship will work at scale.