Picture this: You’re sitting in yet another vendor demo. The rep walks you through slides showing an “AI Agent” that promises to research, reach out, qualify, follow up, and close the deal; all while you sleep. The story is irresistible. Who wouldn’t want to scale revenue without scaling headcount?
But if you’ve been in GTM long enough, you know how this movie ends. Big promises, slick demos, and… an underwhelming pilot that leaves your team skeptical, your workflows messier, and your credibility dinged.
That’s because most “agents” in the market aren’t really agents. They’re copilots, scripts, or thin wrappers around automation tools. And unless you press for clarity, you’ll end up buying into myths instead of measurable outcomes.
So how do you separate signal from noise? You ask sharper questions. Here are the five most important ones every GTM leader should put on the table before signing with an AI agent vendor.
1. Workflow Ownership: What does the agent actually own?
One of the biggest myths vendors sell is that an agent can replace an entire team. The fantasy of a digital SDR or CSM that never sleeps is powerful, but it’s not real.
Here’s the truth: Agents excel at task-level execution. Think list enrichment, scoring, duplicate detection, or campaign triggering. They don’t carry judgment, empathy, or nuanced decision-making.
When a vendor claims “end-to-end” ownership, challenge them:
- Which parts of the workflow can the agent run from start to finish?
- Where must a human still step in?
- What happens when context is fuzzy or judgment is required?
Why it matters: If you don’t map the boundaries upfront, you’ll end up either over-trusting the agent or constantly firefighting when it drifts.
2. Decision Limits: Where does the agent hit a judgment wall?
Every agent has an invisible line it cannot cross — the “judgment wall.” This is the moment when it runs out of structured logic and risks going off the rails.
For example: an agent might flawlessly update CRM records but fail miserably when deciding whether a prospect sounded “interested” on a call.
Ask vendors to show you:
- The exact conditions that trigger escalation to a human.
- How the system handles ambiguous or incomplete inputs.
- Whether you can adjust those thresholds or not.
Why it matters: Agents that don’t know their limits will act outside their scope, which in GTM workflows means brand damage, lost deals, and angry customers.
3. Production Readiness: What does it need before it delivers value?
Many teams fall for the “plug-and-play” myth. The demo looks magical — tasks flow seamlessly, outputs look polished, and it feels like the agent is ready to drop into your stack.
Reality check: agents require structure, context, and supervision. Without clean data and well-defined workflows, they drift into chaos.
Push vendors for specifics:
- What data sources must be in place?
- How do we map our schema, rules, and workflows?
- What level of training, tuning, or prompt engineering is required before this works in production?
Why it matters: If a vendor hand-waves away setup, you’re signing up for months of hidden work. And by the time you realize it, adoption has already stalled.
4. Failure Modes: How does the agent break, and how do we know?
No agent is perfect. Every system fails — the only question is how, and whether you’ll catch it in time.
Vendors often tout accuracy metrics but gloss over brittleness. What happens when the data is messy, when rules collide, or when the system is pushed outside its trained context?
Ask vendors to be brutally specific:
- What is the expected failure rate in production?
- How do errors get flagged — to the system, to a human, or to no one?
- What monitoring and audit trails exist?
- How are corrections fed back into the model?
Why it matters: In GTM workflows, quiet failures are the most expensive. A campaign sent to the wrong segment, a missed renewal flag, or a bad handoff email isn’t just a glitch — it’s revenue lost and trust eroded.
5. Accountability: When it fails, who owns the outcome?
This is the question most leaders forget to ask — and the one that matters most.
When an agent makes a mistake, who takes responsibility? Your team? The vendor? No one?
The Playbook makes this clear: you can never outsource accountability. You can buy software, but the outcomes — good or bad — remain yours.
Still, vendors should answer:
- Who owns support and escalation when the agent misbehaves?
- What SLAs, guarantees, or remedies do they provide?
- Do they offer shared dashboards or visibility so you can monitor performance in real time?
Why it matters: Without clear accountability, mistakes get lost in the cracks. And when those mistakes touch customers, the damage is yours to clean up — not the vendor’s.
5 Questions at a Glance
The Bigger Picture: Don’t Buy a Teammate, Hire One
At the end of the day, choosing an AI agent isn’t like buying another SaaS tool. It’s closer to hiring a teammate. You’re not just asking: what features does this product have? You’re asking:
- What job are we hiring this agent to do?
- What training and guardrails do we need to put in place?
- How will we supervise it over time?
- Who owns it when things go wrong?
Vendors will happily sell you myths. But GTM leaders who treat vendor evaluations like a hiring process — pushing for clarity on scope, decision limits, readiness, failure modes, and accountability — end up with agents that truly amplify their teams instead of draining them.
Final Takeaway
You don’t need an AI agent that can “do everything.” You need one that does something specific, well, and reliably.
So the next time you sit in that vendor demo and hear about the agent that can “run your entire pipeline while you sleep” — smile, then ask the five questions above.
That’s how you separate the hype from the hire.
Go Deeper: The AI Agent Playbook
This blog scratches the surface. If you want the full breakdown of myths, guardrails, workflow fit, and vendor evaluation frameworks, download The AI Agent Playbook — a pragmatic guide for GTM, marketing, and CX leaders.
