Contributors (Left to Right): Tiger Henderson (VP, Software), Melanie Nabar (VP, Software), Emily Pawlak (Sr. Associate, I&C), Steve Achatz (Principal, I&C), Kyle Howard-Johnson (VP, Software).
With the first half of the year behind us, we caught up with five Volition Capital investors to reflect on what stood out to them in the growth equity landscape — and what they will be watching for the remainder of the year.
1. In today’s market, what differentiates the companies that are breaking out from those that are falling behind?
Emily Pawlak (Sr. Associate, I&C): Honestly, speed of execution is everything today. AI has really turned the dial way up on how fast products and technology are evolving — especially in a lot of the sectors we look at where things were already moving quickly (like adtech for example). What we’re seeing is that the teams who are building fast, testing nonstop, and getting to market ahead of others are the ones breaking out or best setting themselves up for success. And AI’s a big part of that — not just as a product trend, but as a tool to actually move faster.
Steve Achatz (Principal, I&C): A common thread I see in breakout companies is some form of embedded distribution. It’s a broad term, but in essence, it means a business grows meaningfully on its own, just by the nature of how it’s built — even without heavy marketing or outbound sales efforts. One test I like to use is: if the company stopped all new initiatives and paused sales and marketing spend today, would it still grow in a meaningful way? More often than you’d think, the answer is yes.
This shows up in a number of ways, often in familiar business models. Examples include B2B2C sales, product-led growth, community-driven engagement, hardware-plus-software models, or high-trust markets that have natural network effects. Examples in our own portfolio, just to name a few, are Petscreening, which grows alongside tenant lease turnovers and US Mobile, which benefits from highly engaged Reddit communities that fuel product conversations and rapid iteration. Others include ButterflyMX, HAAS Alert, and HALOS, which all use hardware as a distribution advantage to unlock software sales.
These models aren’t new per se, but the difference is how early companies are leaning into them. In the past, startups often turned to outbound sales teams in a B2B setting or paid acquisition on Google and Meta in a B2C setting much earlier in their growth cycles. Those channels still matter, but they’re coming later now. The beauty of embedded distribution is optionality and flexibility. Even if you pause everything and “stand still” you’ll gain leverage over your existing overhead simply as a function of time and have a nicely profitable, healthy, growing business. I simply love seeing that and try to always play out that scenario as a thought exercise in my investment evaluation of new prospects.
2. Among the companies in your portfolio that are seeing success with AI, what specific use cases or approaches have proven most effective?
Kyle Howard-Johnson (VP, Software): The most effective use cases I’ve seen are ones that keep a human in the loop. These companies are using AI to take a task 80–90% of the way to completion and then relying on a human to confirm accuracy, make a judgment call or more generally push it across the finish line. That’s a pragmatic model — especially in regulated industries — where full automation simply isn’t yet realistic. But there’s still immense value in reducing the workload and giving workers more leverage to increase throughput or focus on other high-value judgment calls.
Another powerful application we’ve seen is at the top of the funnel, especially in industries that have historically been offline or low-tech. AI can scrape huge datasets, identify potential buyers that would’ve otherwise been challenging to pinpoint, and engage with them at scale. It’s like giving old-school sales processes a data-driven upgrade, and it’s driving measurable improvements in pipeline efficiency.
Melanie Nabar (VP, Software): The companies seeing the most success with AI are meeting their customers where they are in terms of the adoption cycle of AI. Over the last six months, our portfolio AI-based companies have seen a rapid increase in “AI task forces” as part of the buying cycle. These task forces are doing broad market tests and generally slowing purchase cycles. Solutions that are meeting customers where they are comfortable with AI are moving through these buying groups faster, with stronger support from key stakeholders.
One of our portfolio companies, Zenarate, has had notable success navigating these groups. With highly regulated customers in industries like banking and healthcare, Zenarate begins their customer journeys with their AI simulation training software that does not require system integrations or proprietary customer information. It builds trust in its platform and then expands to increase the solution’s stickiness with additional AI offerings more intertwined within existing systems.
3. What sectors or areas currently excite you from an investment perspective? Where do you think the best opportunities currently lie?
Steve Achatz (Principal, I&C): I’m really intrigued by the rise of lean startups, including solo founder companies, that are scaling with virtually no overhead. The $80 million acquisition of Base44 by Wix sparked a lot of conversation around the idea of “solo unicorns,” but this trend goes beyond one or two buzzy examples.
We’re seeing more founders, whether they’re college students in dorm rooms or seasoned entrepreneurs looking to “do things differently this time around,” building legitimate businesses that are hitting Series A/B-level traction. What’s most interesting is how they’re doing it. Many are taking an AI-first approach to building and operating, often telling us they set a goal to automate themselves out of a job every couple of months. Then, they move on to the next challenge. It feels like the modern version of growth hacking.
The other major factor is that many of these companies were born in tougher capital markets over the past few years. Without access to easy funding, they had to be disciplined by necessity. Even though that journey came with a lot of scar tissue, many founders now say they wouldn’t have it any other way with the benefit of hindsight. They’ve built real operational muscle that shows up in product velocity, team efficiency, and clear focus.
I think we’re still in the early innings of this shift. These businesses are already in market, and more are coming. There’s a lot to be excited about.
Kyle Howard-Johnson (VP, Software): To take the question in a slightly different direction, I’ll tell you what I’m wary of right now – experimental run-rate revenue (ERR), a phrase I first saw used by Jamin Ball at Altimeter that captures this recent phenomenon nicely. We’ve seen lots of businesses experiencing explosive growth, going from zero to millions of ARR in a matter of months with low CAC, quick payback periods and profitable unit economics. They tend to be tools with low barriers to adoption, leveraging product-led growth to scale incredibly quickly. However, these tools are being adopted by individuals or teams at companies and are propped up by hype, pilots, or trials with limited commitment from the customer. That can create a misleading signal of traction that doesn’t necessarily translate into sustained usage or true product-market fit.
As a growth equity investor, I’m looking for more than momentum — I’m looking for evidence that a product is solving a critical problem and has the differentiation and durability to scale. Many of these AI companies are solving narrow problems, but they lack the moat or operational infrastructure to sustain long-term value creation.
On the flip side, what I am excited about are services-centric businesses that already have deep customer trust and are incorporating AI in practical and durable ways. These are companies using AI as a lever to automate manual processes, enhance customer interactions, improve margins and drive real scalability. That combination of trust, efficiency, and defensibility is where I believe the most compelling opportunities lie right now.
4. What is something you will be watching closely in the back half of the year and into ’26?
Tiger Henderson (VP, Software): The excesses of 2020/2021 are coming home to roost. In a zero-interest rate environment, new funds flooded the market, dry powder ballooned, and valuations soared. Inevitably, a surge of overcapitalized, overvalued startups that failed to reach escape velocity followed, and as investors hit their 5YR hold periods, we’ve seen more “venture orphans” arise.
What does this mean for founders? In the coming years, I’d anticipate opportunities to 1) recruit top-tier talent displaced by orphaned startups, 2) benefit from lower CAC due to higher switching urgency from customers of unsupported solutions, and 3) acquire distressed (but strategic) assets at attractive valuations. Markets are cyclical by nature. For the savvy, capital-efficient founder, the current environment provides an opportunity to absorb the lessons of peak bull market exuberance.
Emily Pawlak (Senior Associate, I&C): I’ll be curious to see how some of the AI-native companies sustain growth after what, for many, was a rocketship Year 1. We saw breakout launches — particularly on the B2C side — that scaled rapidly on the back of virality. But now the real test begins: driving strong retention, testing acquisition channels for efficiency, and building sustainable unit economics. It’ll be interesting to see which companies evolve to find long-term product-market fit beyond the initial hype. I believe the ones that endure will be those fundamentally rethinking workflows — not just layering in AI as a feature, but rebuilding the core product experience around it.
5. What would you recommend to founders who are trying to raise capital in this environment?
Tiger Henderson (VP, Software): In an AI-dominated landscape, think critically on communicating your startup’s defensibility. The advent of generative AI has proven a double-edged sword – barriers to building have lowered, but so too has durable competitive advantage. With technology alone becoming less of a sustainable differentiator, founders need crisp, data-backed answers to this paradox. Does your business benefit from network effects, regulatory moats, data flywheels, deep localization, distribution advantages, steep switching costs, or otherwise? Can you support the efficacy of those strategies with hard data or case studies? In this environment, I’d prioritize defensive clarity, with particular emphasis on how your moats deepen with scale.
Melanie Nabar (VP, Software): The dichotomy of top tier companies vs mid-tier companies is the largest it has been in several years. At the same time, the technology landscape is shifting faster than ever. Of course, this creates immense opportunity for founders – particularly where you fall in what investors consider “top tier.” However, it also means that the delta in outcomes is more drastic than ever. I think we will see smart, and still bullish, founders take more secondary as a part of Series A investments. One could call this “making hay while the sun shines,” but moreover, I think smart founders will be looking to diversify themselves on the personal front in order to make the risk-forward decisions that will be required to stay ahead of the pack.
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