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A lot of smart people are confused by AI right now, and we can’t blame them.
GTM teams are facing board-level pressure to adopt AI, but when they look out at the market they don’t know what to do, or if AI even works. They see big headlines like these:
- 73% of buyers feel overwhelmed by too many options
- 88% of companies aren’t reporting ROI from AI investments
- 42% abandoned most of their AI initiatives last year
We are an AI company, and even we think the AI market is noisy, risky, and filled with confident claims from vendors who can’t back it up. We wrote this piece to provide an honest response to some of the biggest myths about AI GTM agents, to help you cut through it all and make more informed choices.
Myth 1: AI GTM agents don’t work
AI is in about its second year of mainstream, widespread adoption, but it continues to fight some stigmas created by poor expectations in year one.
When LLMs like ChatGPT, and AI GTM agents like AI SDRs, first came out, they quickly divided people into two categories. The first group had a negative knee-jerk reaction and said “AI sucks, it’ll never work, and I’ll never use it.” They are largely sticking to this reaction without testing if it’s true.
The second group saw these tools and thought “AI is a magical solution and can do anything.” They went out and did a lot of pilots of early AI tools across every use case. These tools turned out to not be the panacea they were looking for, the pilots failed, and AI’s reputation took some hits.
We’re now seeing both camps were wrong. AI is working now. The AI tools that survived, learned, matured, and developed are generating real results (here are case studies with quantifiable long-term outcomes) and everyone is developing a more realistic picture of where and how to deploy agents.
Myth 2: AI is software that works out-of-the-box
This is a big misconception that was nurtured by less-than-honest vendors over the past 1-2 years, and continues to be hyped by some. It isn’t true.
You can’t think of an AI agent like a piece of software. You have to think of it as a digital employee, and like any employee it won’t work perfectly on day 1. It needs time, it needs training, and it needs ongoing oversight. When you do all of that properly, an AI agent can do exponentially more work than any single human employee with less management, but it still needs support.
For AI GTM agents, that means setting them up with the right campaign templates, ICP definitions, product marketing materials, and the like. It means taking a couple weeks upfront, or even a couple months, before it’s ready to scale. It means reviewing performance once a week, tweaking as needed, and adding new experiments to try and campaigns to run.
This “training” component of AI agents likely isn’t going away, and even if AI agents do become extremely advanced, that doesn’t mean they will be rolled out much faster or with less oversight. In large organizations there is a concept known as “risk management” that is taken very seriously, and even proven tools take time to pilot, land, then expand. One Fortune 1000 customer of ours ran hundreds of successful production calls with 11x’s AI agents before they did any CRM integration. This isn’t going away.
Myth 3: AI “only” automates simple tasks
AI does largely automate routine, high-volume, manual tasks across research, data collection, and execution. Our platform does things like build and enrich lead lists from ICPs, draft outreach messages from positioning and send those messages out at scale, and respond to and nurture leads. Each of these is a relatively simple task, or a collection of relatively simple tasks.
But there are two downstream implications that people don’t talk about.
First, when you automate these tasks with AI you solve problems that people could never solve on their own, at least not in a cost-effective manner. You cannot throw enough bodies at GTM to respond to every inbound lead in 5 seconds, or personalize hundreds of thousands of outbound messages. Even if you could, the overhead would be cost-prohibitive and kill your CAC.
Second, when you automate 10, 20, or even 30 hours of routine tasks per employee, per week, you do more than just streamline your operations. You free your people to come up with more ideas, run more experiments, iterate faster and easier, and build more relationships. These are strategy-level benefits that only open up after you take “simple tasks” off everyone’s plate.
So while this myth is partially true, it doesn’t tell the whole story.
Myth 4: No customer or prospect wants to interact with AI
This myth is also only partially true, and it depends on the type of interaction.
Gartner predicts that 75% of B2B buyers will prefer high-touch human interaction in the sales cycle by 2030, but that is only for “critical touchpoints in the buyer journey” during complex, high-stakes transactions. They state that AI will continue to be “especially effective in the early stages of the buyer journey” including “streamlining information gathering and pre-sales activities.”
And for smaller, simpler, faster transactions, 82% of customers would rather use AI like a chatbot than wait for humans, especially for basic customer service. The reason is simple. AI can take routine actions instantly, provide the most up-to-date knowledge, and interact across email, chat, or other channels.
This aligns with what we’re seeing in the market. Our customers are using AI GTM agents to do the work of 40+ BDRs with a single operator, but they still launch high-touch human-first motions as soon as a lead gets on the phone.
We believe customers and prospects will prefer AI agents for most transactional sales, support, and account management use cases, and prefer humans for complex, big-ticket, high-trust sales processes or tricky issues.
Myth 5: AI GTM agents will take everyone’s jobs
This is a very common and understandable fear that people have, but we just aren’t seeing it. We have spoken with thousands of GTM teams, and nearly every single one wants to deploy AI to augment their existing team, not replace them. Most of these teams were given the mandate to “scale pipeline without increasing headcount,” and AI offers the only way to do so.
And when these agents are deployed, we don’t see existing team members fired, we see them promoted. SDRs and BDRs stop doing the boring work they don’t enjoy (like researching prospects, writing emails, or qualifying leads) and instead focus on cold calling, handling objections, and learning to be relentless… all of which gets them promoted to AEs faster.
Other GTM folks are seeing similar career growth due to AI. Instead of juggling follow-ups, building out campaigns, or doing other manual tasks, they’re focusing on being strategic and creative, and taking on more responsibilities within the function. The best are using AI and building a wide range of specialized agents to build pipeline, and blurring the lines between sales, marketing, ops, and growth.
AI is accelerating career paths and expanding job descriptions for GTM practitioners, but it isn’t eliminating these jobs altogether
Trying AI yourself is the only way to get to the truth
If you want to see what good, deployed AI for GTM actually looks like, not a pitch, the real thing, reach out.
We'll show you our platform in action, walk you through real customer results, and give you honest answers to your hardest questions.
