When everyone has the same AI tools, what makes outbound better?

Back from ApolloNEXT in San Francisco, I keep returning to one question: what will make one company's outbound better than another's when both have access to the same AI tools?

What changes when everyone has the same AI tools?

The gap in tooling between companies gets smaller. Your competitors can use the same platforms, follow the same playbooks and generate messages based on the same public information about the same prospects. When two teams work with the same data and the same models, the first drafts of their outreach will often look alike.

The usual response is more personalization. I don't think adding another layer of it will be enough. A message that mentions a prospect's latest post or funding round is easy to produce when everyone can pull the same facts. It can still be useful, but it is hard to build a lasting advantage on something a competitor can reproduce with the same settings.

What is harder to copy is the knowledge the system is built on: who you sell to well, why they buy, and what your sales process needs from a first conversation.

What does it mean to build outbound around how the business sells?

For me it starts with three questions about the business, before any question about the tool:

• Which customers can we actually help?
• What gives those customers a reason to buy?
• What needs to happen between the first conversation and a signed deal?

Each answer becomes a decision in the system. The first one defines who to contact and, just as important, who to leave out, even when they look like a good fit on paper. The second shapes what the message is about and which signals are worth watching, because a reason to buy is usually tied to something happening in the prospect's business. The third decides what counts as a good outcome: a conversation that can move toward a deal, rather than a meeting that only fills a slot.

The same answers show where a person needs to make the call. AI can research accounts, draft messages and sort replies, and automation can connect those steps and keep them running. Deciding whether a reply is a real opportunity, or whether a segment should be dropped, depends on understanding how this specific business sells. That judgment needs a place in the system from the start.

Who is the human in the loop?

"Human in the loop" is a common answer to concerns about AI in sales. This is where the topic gets interesting for me: who is that person, and have they ever been responsible for what happens after the meeting gets booked?

AI and automation configured around a business need someone experienced enough to question what the system is doing. If the person reviewing the output has only been measured on sent emails and accepted invitations, they are likely to judge the system by those things: deliverability, reply rates, the number of meetings. Those things matter. They don't tell you whether the system is filling a salesperson's week with the right conversations.

I spent more than eight years on the front line of sales. Getting deeply into AI gave me a way to apply that experience to a problem I had struggled with myself: getting useful support in finding and starting conversations with potential customers. When I was selling, I wanted that support from someone who understood the rest of the job too.

What a calendar screenshot doesn't tell you

This is also why I'm skeptical when I see a screenshot of a packed calendar presented as proof that someone has figured out GTM.

I'm not dismissing the work it takes to book those meetings. A screenshot shows that the meetings exist. It doesn't show whether they were worth having.

The cost shows up later, on the sales side. If the salesperson spends the next month discovering that most of those conversations should never have been booked, the campaign has consumed selling time as well as generating activity.

What should you ask before trusting outbound advice or a partner?

I'm cautious about advice from people who have built outreach campaigns but never carried the resulting conversations through a full sales cycle. That says nothing about how well they run campaigns. It is about what they have been in a position to see.

Before you act on advice about outbound, or hand your outbound to a partner, these questions are worth asking:

• Who decides which accounts to contact and which to leave out, and on what basis?
• How does the system reflect what gives your customers a reason to buy?
• What counts as a good result: a booked meeting, or a conversation that can move toward a deal?
• Where does a person review or decide, and what sales experience does that person bring?
• What will you learn about the meetings after they happen: who attended, why, and what came next?
• Has the person advising you been responsible for what happens after the meeting?

We attended ApolloNEXT as an Apollo.io partner, and I'm excited about what we can build with the technology. My conviction is that it becomes far more useful when the system is tailored to the business and the people guiding it understand sales beyond the first meeting. That is what we keep building at MSGA.