In almost every conversation with CEOs right now about their go-to-market, I keep hearing about how the channels that used to fuel their sales pipeline predictably has seemingly dropped off a cliff.
One CEO noted that they hadn't closed a single deal from outbound in a year.
And PPC dropped off as well. What used to provide at least four qualified leads a month has gone to zero, despite having increased the spend recently.
They also tried offering a free steak dinner in cities where they had some relationships, and nobody came.
Our agency, and others we’ve talked to have had similar experiences. And in fact, one recently told us they had abandoned outbound altogether, building their pipeline instead around partnerships and events.
Something has definitely changed.
What used to work (outbound, advertising, content) has in some cases completely stopped working, and the problem is that most are hard pressed to figure out what to do instead.
The response from most companies has been remarkably consistent. If outbound isn't producing the pipeline it used to, the answer must be to send more emails, build more sequences, add more personalization, hire more SDRs, and now, increasingly, replace those SDRs with AI agents that can execute the exact same playbook twenty-four hours a day for a fraction of the cost.
That logic has never made much sense to me.
If buyers are already ignoring unsolicited outreach because they're overwhelmed by the sheer volume of it, why would flooding them with even more outreach suddenly change the outcome?
Has anyone stopped to think about what this looks like from the buyer's perspective?
The premise behind AI SDRs seems to be that the constraint was human capacity.
It wasn't. The constraint is buyer attention.
We've reached the point where the average executive has become extraordinarily efficient at filtering anything that looks like generic outbound, whether it was written by a human or a language model.
Increasing the volume of messages aimed at people who have already decided to ignore them is not a strategy. It's wishful thinking disguised as automation.
That's why I find so much of the excitement around AI SDRs misplaced. The technology is impressive, but it is being applied to a model that is already breaking down.
Making a broken system faster and less expensive doesn't fix the underlying problem. It simply allows more companies to contribute to the very noise that caused the problem in the first place.
Every morning, I open my inbox, and I delete sales emails.
Most of them are obviously templated. They know my name, my company, and maybe they scraped a recent LinkedIn post, but there's nothing in the email that suggests the sender understands what I'm trying to accomplish or why I should stop what I'm doing to respond.
The moment I recognize the pattern, I move on. I'm guessing you do too.
Cold calls aren't much different. I can remember exactly one unsolicited sales call in the last five years that made me think, I'm glad they called.
Every other one started the same way. They knew my title, assumed that was enough research, and launched into a pitch before they had earned the thirty-seven seconds of my attention.
Now we're seeing the same thing happen with AI voice agents, and I honestly don't understand the excitement. Buyers have become incredibly good at tuning out generic outreach, so our solution is to generate vastly more of it?
Have you gotten one of these AI calls yet?
The first few moments of a cold conversation have never been about delivering a script. They're about earning the right to keep talking.
That takes judgment, curiosity, and enough business acumen to recognize when someone is struggling to make progress. It also requires listening, asking thoughtful questions, and bringing a perspective the buyer doesn't already have.
The conversation stops being scripted almost immediately and starts becoming human. That's exactly where today's AI voice agents still fall apart.
What's interesting is that many of the same people predicting the future of sales also argue that selling will become more consultative and insight-driven, not less.
If they're right, then the future looks a lot more like The Challenger Sale than a machine executing a sequence.
The sellers who win won't be the ones sending the most messages.
They'll be the ones who can teach buyers something they didn't already know, challenge assumptions, connect business problems in unexpected ways, and create enough value in the first few minutes of a conversation that the buyer wants to keep listening.
If more outbound isn't the answer, and neither is replacing SDRs with AI, then what is?
Ironically, I think the answer is something we've known for years. Many of the people predicting the future of sales also believe it will become more consultative and insight-driven, not less.
That's essentially the premise behind The Challenger Sale: the best salespeople don't show up to discover whether a customer has a problem. They show up already understanding the problem, bringing a point of view, and helping the customer see something they hadn't recognized on their own.
The traditional SDR model was never designed for that.
It was designed to maximize activity. Give someone a list, measure calls, emails, and meetings booked, then hand the opportunity to an account executive. That worked when simply reaching prospects was enough to start a conversation.
Today, buyers expect much more than persistence. They expect someone who understands their business well enough to be worth interrupting their day for.
The irony is that AI is probably the best tool we've ever had to support this kind of selling, just not in the way most people are using it.
Most companies use AI to write emails faster. I'd rather use it to think before anyone sends the first email. That's where AI actually creates leverage.
Here's where I think AI has the potential to fundamentally change sales, and it has almost nothing to do with writing emails or replacing SDRs.
Its real value is helping us identify buying moments.
Most companies still organize outbound around personas and account lists. They decide who fits their ideal customer profile, load those companies into a CRM, and start working through them. The assumption is that if a company matches the profile, it's worth pursuing.
But companies don't buy because they fit an ICP. They buy because something changed.
Those are potential buying moments. They create urgency in ways that demographic filters never can. The mistake most teams make is treating those moments as the beginning of outreach instead of the beginning of research.
Take a Series A announcement. For most sales teams, that's the signal to launch a sequence. For me, it's the signal to start asking questions.
What is the funding supposed to accomplish? What expectations are the investors placing on management? How does the company plan to grow? Where is the pressure likely to show up first? Those are the questions that determine whether there's actually a conversation worth having.
Maybe the press release promises an AI-first customer experience, but the website never explains why customers should care. Maybe they're hiring salespeople aggressively while marketing remains lean. Maybe their positioning sounds indistinguishable from every competitor in the category. Maybe they're investing heavily in product while neglecting the messaging needed to support enterprise sales. Those observations are far more valuable than the funding announcement itself because they reveal where the business may actually be struggling.
Only then do I decide how to reach out.
Instead of introducing myself or asking for thirty minutes with an account executive, I can share an observation based on patterns I've seen helping similar companies and start a conversation around a problem that's likely already emerging inside the business.
That's where I think AI becomes genuinely transformational—not because it can generate another thousand emails, but because it can accelerate the research that makes every call, email, and LinkedIn message dramatically more relevant.
Everything I've talked about so far relies on public buying signals: funding announcements, executive hires, acquisitions, hiring patterns, press releases, and other events anyone can see.
Those are valuable, but they're also available to everyone. If you can see them, so can your competitors.
I think the real opportunity with AI is creating signals that nobody else is looking for because they're based on what you know about your customers.
Every company has patterns they recognize after working with enough clients. You start noticing the same problems showing up before customers ever reach out.
Maybe prospects begin hiring a certain role. Maybe they change the language on their homepage. Maybe they add a pricing page, launch a partner program, expand into a new vertical, or suddenly start talking about AI after years of ignoring it.
Those aren't generic buying signals. They're hypotheses built from your own experience.
Now imagine turning those hypotheses into AI agents.
Instead of waiting for a funding announcement, an agent could monitor the websites of every company in your ideal customer profile and alert you whenever messaging changes in a meaningful way.
It could compare yesterday's homepage to today's and flag shifts in positioning, new product launches, pricing changes, AI announcements, new customer segments, or subtle language that suggests a strategic change is underway.
For us, that's incredibly interesting. If a SaaS company suddenly rewrites its homepage, that's rarely just a copywriting project. Something inside the business changed first.
Maybe leadership has a new strategy. Maybe sales isn't converting. Maybe they're entering a new market. Maybe they're responding to competitive pressure. Whatever the reason, it creates a perfect reason to start researching before anyone else notices.
The same thinking applies in every industry.
A manufacturer might discover that customers typically redesign their website six months before investing in automation. A cybersecurity company might learn that certain hiring patterns consistently appear before organizations begin evaluating new security platforms. A law firm might recognize that companies rewriting their compliance pages often face new regulatory pressure.
Those patterns are invisible until you teach AI to look for them.
That's the shift I think most companies are missing.
The future isn't about using the same AI tools everyone else has. It's about teaching those tools to recognize the patterns that only your business understands.
Those become proprietary buying signals.
They're difficult to copy because they're built from your experience, your customer base, and your view of the market. Every time one of those signals appears, AI doesn't replace the salesperson. It hands them a better opportunity to create value.
That's the kind of advantage that's worth building.