The Tech Economy is a Mixed Bag. Adaptability is the Dividing Line.

Economic Performance & Market Adaptation

A friend in commercial lending asked me this morning, "What kind of economic performance are you seeing across your customer base?"

The honest answer is that it is a mixed bag.

Growth Molecules is about 95% focused on the business-to-business technology sector, but our customers serve industries ranging from education and pharmaceuticals to cybersecurity and energy. Their markets and business models vary widely, but they all have one thing in common: protecting and growing customer revenue is paramount.

What we are seeing, however, is a widening gap between companies that are willing to evolve and those that are still protecting yesterday's playbook.

The tech companies taking thoughtful risks seem to be gaining momentum. They are testing new revenue models, moving beyond traditional per-seat licensing, entering new addressable markets, and selling to new buyers. ICONIQ's 2026 State of Go-to-Market report supports this pattern. High-growth companies expect self-service revenue to represent roughly 20% of revenue in 2026, compared with about 10% for their peers. The report also found that hybrid pricing is now the most common primary model, with consumption-based structures continuing to gain ground.

In other words, the companies performing well are not simply waiting for demand to return. They are redesigning how they create, deliver, and monetize value.

On the other side, we have customers whose new bookings are down as much as 50% year over year and whose existing customer bases feel shaky at best. Some are dealing with repeated leadership turnover. Some watched what they believed was an AI moat become an AI tsunami. Others barely completed the transition to cloud computing before the next wave of disruption arrived.

AlixPartners describes mid-market software companies as being caught between nimble AI-native competitors and technology giants investing heavily in AI infrastructure. Its 2026 enterprise software outlook warns that this disruption is arriving faster than many established companies anticipated. Deloitte similarly expects financial pressure, agentic AI, and AI-first products to intensify competition and force software companies to reconsider how they operate and bring products to market.

So, I told my friend that our customers' economic performance is continually changing. There is no single story that represents the entire tech sector. But there is a pattern.

The organizations that remain curious, take informed risks, listen closely to their customers, and adapt their revenue engines are giving themselves a better chance to thrive. Those that delay difficult decisions may find that the market makes those decisions for them.

We are still in the middle of the AI revolution. None of us can fully control how quickly the technology, economy, or competitive landscape will change.

What we can control is how quickly we learn, how courageously we respond, and how we treat people along the way.

Roles on the Radar

• Head of Customer Success & Operations at Tebra
• Head of Customer Success Management at Cove
• VP of Client Success at Gifthealth

Molecule Maker: Featured Leader

Meet Ejieme Eromosele, VP, Customer Growth at Quiq.

Ejieme's fun fact: I saw a gap in Customer Success. Not enough spaces built for Black professionals to grow and be seen for the work they were already doing. So I built one myself, and it's called Success in Black. What started as a Slack community is now 600+ members strong.

Ejieme's current curiosity: As AI takes on more of what humans used to do, I keep coming back to one question. How do we double down on the things that make us human? Connection. Empathy. Judgment in the moments a script can't cover. Those skills don't become less important as AI scales, they actually become the differentiator. And I think that's what we should be coaching and leveling up on our teams, not just the tools.

A recent challenge Ejieme has solved: I built a Claude skill that changed how our AMs do account planning. What used to take 6 to 8 hours per account now runs in 10 minutes. It pulls from customer documentation, a whitespace dashboard (also something I built in Claude!), our renewals forecast, our customer health scoring framework, and competitive intel. Then it scores each account and produces a plan ready for review. We went from quarterly to monthly planning on our top 20 accounts. That gave us back nearly 480 hours of AM time a year, worth close to $47K in labor value. Time we now reinvest in higher-value work like deeper value measurement, value articulation, and relationship development.