A Procurement Manager's 7-Step Checklist: When Your B2B Sales Team Actually Needs an AI Sales Assistant

If you're a RevOps lead or sales manager being asked to sign off on an AI sales assistant this quarter, this checklist is for you. I'm not a salesperson — I run procurement. Which means I don't care how slick the demo is. I care about what shows up on the invoice twelve months later.

Over the past four years I've evaluated fourteen AI prospecting and lead gen tools for our outbound team, across roughly $290,000 in cumulative tooling spend. Seven of them made it past a pilot. Two survived renewal. This is the process I now use every time someone forwards me a "revolutionary" AI SDR pitch.

Seven steps. Roughly three weeks of work. Do them in order.

Step 1: Price your current prospecting motion before you talk to any vendor

You cannot evaluate an AI sales assistant against a number you haven't calculated. Most teams compare the tool price to zero — that's the wrong benchmark.

Total up: SDR salaries and benefits, list purchases, email verification, enrichment credits, LinkedIn seats, sequencer subscriptions, and the hours your team spends cleaning bad data. When we did this in Q1 2024, our six-person SDR pod was running about $180,000 a year all-in, before quota was even a factor. A $24,000 AI prospecting agent doesn't look expensive next to that number — it looks like the only rational option.

Or it doesn't. That depends on what the tool actually does. But now you have a denominator.

Step 2: Test data accuracy before you test features

This is the step most buyers skip, and it's the one that kills deployments six months in.

Every AI SDR demo looks great because the vendor scrubs their sample data before showing you. Ask for 500 contacts from your ICP — not theirs — and bounce-test the emails. Run them through your existing verifier. Check title accuracy against LinkedIn manually.

Here's the thing: an AI prospecting agent with brilliant intent signals and 8% bounce rate is worse than no tool at all. Sender reputation is hard to rebuild. When we tested one well-known platform in 2023, its live-ICP sample came back with a 6.4% bounce rate. The demo sample had been under 1%. That single test saved us from a bad contract.

Ask what verification method they use (SMTP handshake, catch-all handling, AI-based inference) and what happens when a record goes stale between export and send. If the answer involves the word "typically," press harder.

Step 3: Ask where the intent data actually comes from

It's tempting to think intent data is intent data. It isn't. There are three sources, and they are not interchangeable:

• First-party: activity on your own site, CRM, and email. Most reliable, smallest volume.
• Second-party: direct publisher partnerships. Vendor-specific quality.
• Third-party: aggregated, often resold by multiple vendors from the same upstream feed.

If two competing platforms quote "intent signals" and both trace back to the same third-party source, you're paying twice for the same noise. Ask for the source name and the match rate against your TAM. Anything under 20% coverage on 500 test accounts is a red flag.

This is also where waterfall enrichment matters — a platform that layers multiple providers (as okkigo describes its waterfall enrichment + intent model) usually returns higher match rates than a single-source tool. Ask how many providers are in the waterfall, and whether credits only bill on successful matches.

Step 4: Run the pilot with one rep, not the whole team

This is the step where nine out of ten teams overspend. Rolling out to eight SDRs on a 30-day pilot costs the same as rolling out to one, except when it fails — and pilots fail often — you've burned eight weeks of productivity and a lot of political capital.

Pick one rep with a mixed territory. Establish a baseline: meetings booked, replies, pipeline value per week over the previous 60 days. Turn the tool on for 30 days. Measure the same metrics. The signal is imperfect — 30 days won't separate seasonality from tool impact — but it catches integration failures, data quality issues, and the biggest problem of all: reps who won't use it.

Step 5: Get the human-in-the-loop claim in writing

"Human-in-the-loop outreach" is one of those phrases that means three different things depending on which vendor is saying it:

1. Every outbound email requires manual approval before sending.
2. AI sends automatically, but humans review escalated replies and edge cases.
3. AI runs the whole sequence, humans get a weekly summary.

All three can be legitimate. But the language is doing a lot of work, and if you assume (2) and sign a contract for (3), your team will find out the hard way when a prospect replies to an auto-sent email that nobody saw for four days.

Get the workflow documented. Ask for a screenshot of the approval queue. Ask what happens when the AI is unsure about a reply — does it route to a human, or does it guess?

Step 6: Model the renewal price, not the intro price

Intro pricing on AI sales assistants is typically 20–40% below renewal pricing — verify current figures directly with vendors, since this varies by seat count and contract length. If you're signing a 12-month deal, ask for the renewal rate to be written into the contract, or at minimum confirmed in email.

I want to say our last AI SDR contract jumped 32% at renewal, but don't quote me on that — the exact number is in a spreadsheet I can't find this morning. What I can tell you is that it went from "reasonable" to "needs re-evaluation" in one invoice.

Step 7: Verify compliance, data residency, and exit terms

Most procurement teams forget this until legal gets involved at signature. Three questions to ask early:

• Data residency: where does enriched contact data sit? US, EU, or mixed region?
• Unsubscribes and suppression: if a prospect opts out, is that synced to your CRM, or just the tool's internal list?
• Exit: when you churn, who owns the enriched records, and can you export them in a usable format?

GDPR, CCPA, and CAN-SPAM all have answers to these questions. The vendor should too, without a follow-up email.

Common mistakes I've watched teams make

Buying on feature count. A sales intelligence platform with 40 features your team uses two of is more expensive than a platform with 8 features they use all of. Count usage, not checkmarks.

Ignoring integration cost. If the tool needs a custom CRM connector, budget for it. We spent $4,100 on a Salesforce integration for a tool we cancelled six months later.

Skipping the exit clause. Some contracts auto-renew 60 days before term. Calendar it.

Assuming the reps will adopt it. If your top SDR doesn't like the interface, adoption is zero, and the tool is a line item you argue about at renewal.

One caveat

My experience is based on evaluating B2B SaaS tools for a 40-person company selling mid-market. If you're at enterprise scale with a dedicated RevOps function, your procurement and testing process should be more rigorous than this. If you're a team of two founders doing your own outbound, several of these steps are overkill — pick steps 2 and 6, and move on.

And if you're evaluating okkigo or an okki-go prospecting agent specifically, the same checklist applies. Agent-native prospecting, waterfall enrichment + intent, and human-in-the-loop outreach are all testable claims. Test them against your data, your ICP, and your bounce rate — not their demo.