Last year, I was in a room with a group of dental support organization (DSO) executives — operators managing anywhere from 20 to 200 practices — and one of them said something that has stayed with me. “We’re not looking for vendors anymore. We’re looking for people we’d want sitting across the table from us when things get hard.”
That comment stuck with me because we spend so much time focused on product features, roadmaps, and integrations that it’s easy to lose sight of the people and the service behind them. As AI continues to lower the barrier to building and replacing software functionality, that human dimension becomes a real differentiator.
That dynamic points to something larger reshaping how revenue organizations need to operate in 2026.
We’re past growth-at-all-costs. Capital is no longer cheap. Investors are no longer rewarding topline expansion that bleeds cash. For the first time in over a decade, revenue leaders are being measured as much on efficiency as on bookings. That pressure is forcing a reckoning in how we sell, how we deploy technology, and what we actually value in the people we hire.
Here’s what I’m seeing on the ground.
1. Efficiency Will Beat Expansion
The old playbook: hire more reps, open more territories, close more deals. If growth stalls, scale headcount. That worked when capital was cheap, and investors didn’t ask hard questions about payback periods.
That playbook is done.
In 2026, the primary growth lever won’t be expansion, but efficiency. This isn’t the tired “do more with less” conversation. That framing is defeatist and misses the point. The real opportunity is to do more differently — to use the constraints of a tighter environment as forcing functions to find better ways of working. The companies getting this right aren’t just cutting costs. They’re redesigning how their revenue engine operates.
That means getting ruthless about what’s actually working. The most useful question any revenue leader can ask right now isn’t “what should we add?” It’s “what should we stop doing?”
Maybe it’s the trade show that hasn’t sourced a qualified opportunity in three years. Maybe it’s a comp plan that rewards bookings instead of collected revenue, quietly creating a misalignment between what sales celebrates and what the business actually needs. Maybe it’s a tech stack where half the tools overlap, and none of them talk to each other cleanly.
The efficiency mandate also changes the hiring calculus. When you can’t solve growth problems by adding headcount, you have to invest differently in the people you already have with better coaching, clearer role definitions, and honest conversations about fit. Replacement costs are real. You exhaust every development option before making changes. But when changes are necessary, you make them without hesitation.
The winners in 2026 won’t have the largest sales teams. They’ll have the most effective ones.
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2. AI Is Only as Good as the Problem You Point It At
Everyone is talking about AI in sales. Most of that conversation is still aspirational. A lot of what I see in the market is AI theater — tools that look impressive in a demo and create friction in production.
The pattern I keep seeing: AI gets you 80% of the way there. The last 20% still requires human judgment. If that gap isn’t accounted for in how the tool is designed and deployed, you end up with more process complexity, not less.
At Planet DDS, we’ve stopped waiting to see what the market figures out. We’ve been building directly into our revenue engine. We use Gong across the full sales organization to surface conversation patterns, identify where deals stall, and coach reps on what’s actually happening in calls versus what gets logged in the CRM. We use Fyxer to eliminate the administrative drag that follows every customer interaction, such as the follow-up emails, the meeting summaries, and the next-step documentation that eats into the hours reps should be selling.
The more significant investment has been in how we prepare for sales conversations. We built a Narrative Demo Briefing Engine, which is a system that transforms discovery data into a customized briefing for the AE before the demo. Not a generic script. A narrative framework specific to that practice group’s operational pain, growth stage, and decision-making structure. The brief tells the rep what to lead with, what to prove, and what to avoid. We have seven frameworks mapped to different buyer types and deal dynamics.
The connective tissue across all of it is Claude and Claude Code, which our team uses not just for individual productivity but to build and iterate on the systems themselves. We’re not waiting for a vendor to productize this for us.
What makes any of this work isn’t the technology. It’s the specificity of the problem definition. Before we built anything, we named the actual failure mode: our demos were becoming feature showcases instead of outcome narratives. AI pointed at a vague goal produces vague results. AI pointed at a specific, named problem produces leverage.
One more thing worth flagging: consolidation is coming in the AI space. A lot of the point solutions out there are features, not businesses. Before you build a workflow around one of them, ask whether it will exist in three years.
3. In a Finite Market, Relationships are the Strategy
Cold outbound isn’t dead. For horizontal SaaS companies with massive, undifferentiated addressable markets, volume-based outbound still works. But we don’t operate in a horizontal market.
In dentistry, specifically in the DSO and group practice segment, the buyer universe is finite and interconnected. Decision-makers know each other. Consultants compare notes. PE firms share deal flow and operator references. The M&A activity compressing the market means that a relationship with a 10-location group today might be a relationship with a 60-location group in 18 months. Reputation compounds in ways that are hard to model but impossible to ignore.
In that environment, the reps who win aren’t the ones with the highest dial counts. They’re the ones who are already trusted when the buying window opens. And buying windows in this segment doesn’t follow a predictable cadence — they open when a group hits a growth inflection, closes an acquisition, or loses confidence in their current vendor. You either have the relationship when that happens, or you’re starting from zero.
This is where the Account Intelligence work we’ve built becomes most valuable. We’re not using it primarily as a pre-call research tool, though it does serve that purpose. We’re using it to map relationships across an organization over time: who the decision-makers are, how authority is distributed, and where influence lives that doesn’t show up on an org chart. By the time a buying conversation becomes real, we’ve already been building meaningful touchpoints throughout that organization for months. The intelligence infrastructure is what makes that systematic rather than accidental.
Brand and content play the same long game. Thought leadership matters, but so does earned media, and I’d argue earned media is becoming more strategically important, not less. More and more buyers, especially in early-stage research, are turning to AI tools to orient themselves on a market before they ever talk to a vendor. What those tools surface isn’t paid placements or SEO-optimized landing pages. It’s the body of credible, third-party coverage and commentary that exists about you in the market. Earned media, including analyst mentions, industry press, podcast appearances, and peer recommendations, is increasingly what determines how your brand shows up in those AI-driven research conversations. You can’t buy your way into that. You have to earn it, over time, by owning the conversation in your market.
Small, high-quality events that put the right people in a room together consistently outperform broad conference presence. Strategic partnerships with advisors and consultants who already have your buyers’ trust are worth more than additional SDR capacity.
At a recent conference, we heard the same message repeatedly from customers, partners, and prospects: yes, the product has to work. But what tips the decision is the team. Enterprise buyers in vertical markets aren’t just evaluating software. They’re evaluating the people they’ll be aligned with when something goes wrong — because something always does.
Hire for that. Compensate for that. Measure for it.
What Comes Next
None of these trends are temporary. They represent a recalibration that’s been coming since the growth-at-all-costs model started showing its limits, and they won’t reverse when rates drop or market conditions shift.
The revenue organizations that navigate 2026 well will have made hard choices about where to invest, been honest about what’s not working, and built AI into their process in ways that actually change outcomes. They’ll have teams built for relationships, not just activity. And they’ll understand that in a market this interconnected and this skeptical, the most durable competitive advantage is being the team that people genuinely want to work with.
The ones that don’t figure this out will keep doing what they’ve always done — and keep wondering why it’s getting harder.
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