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If you've been anywhere near a stock screen in 2026, you already know: software is getting massacred. |
The iShares Expanded Tech-Software Sector ETF (IGV) is down over 20% year-to-date. Salesforce has been cut roughly 30%. Adobe is off 27%. Even Microsoft — the company that is arguably winning the AI race — has seen hundreds of billions in market cap evaporate. The BVP Nasdaq Emerging Cloud Index, the benchmark for cloud software stocks, has cratered from its 2025 highs. Analysts are calling it a "generational repricing." Some are calling it the SaaSpocalypse. Pick your metaphor — they all describe the same thing: a sector-wide panic that has compressed software multiples to levels we haven't seen since the mid-2010s. |
Software price-to-sales ratios have compressed from roughly 9x to around 6x. Enterprise names that were trading at 15-20x forward revenue a year ago are now at 10x or below. Adobe trades at roughly 12.5x forward earnings. PagerDuty at 14x. Salesforce at 18x. Some of these are companies still growing double digits. None of that matters right now. The market doesn't care. |
The question is: should you care? |
We think you should care a lot — but not for the reason most people think. |
What's Actually Happening |
Let's be honest about what's driving this. It's not a recession. It's not a credit crisis. It's not even that software companies are posting bad numbers — many of them are still growing. The problem is narrative. The narrative has shifted from "software eats the world" to "AI eats software." And when narratives shift on Wall Street, multiples follow. |
Here's the story the market is telling itself: AI agents are going to replace entire categories of enterprise software. Why buy a CRM seat when an AI agent can manage customer relationships? Why pay for a data integration platform when a foundation model can do it natively? Why license workflow automation software when agentic AI handles it end-to-end? CIOs are consolidating vendors, slashing seat counts, and redirecting budgets from application software toward AI infrastructure. IT budget growth is decelerating — forecast at just 3.4% — but the internal reallocation is much more dramatic. The money that used to flow into SaaS licenses is increasingly flowing toward GPU compute, foundation model deployments, and AI infrastructure. |
This is real. We're not going to pretend it isn't. The per-seat SaaS pricing model is under genuine structural pressure. AI coding assistants are reducing the need for some categories of developer tooling. Generative AI is challenging incumbents in creative software, customer service, and data management. About 70% of software providers now acknowledge that the cost of delivering AI features is eating into their margins. The "best-of-breed" era — where enterprises bought specialized point solutions for every function — is giving way to platform consolidation. |
So yes, there is real disruption happening. But here's what the market is getting wrong: it's pricing all software companies as if all of them are going to zero. |
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The Baby in the Bathwater |
Let's zoom out. Software is not going away. Not even close. |
The fundamental characteristics that made software one of the best asset classes of the last two decades haven't changed. These businesses still have recurring revenue. They still have high gross margins. They still have low capital intensity. They still have enormous switching costs. The customers who rely on vertical ERP systems, compliance platforms, cybersecurity infrastructure, and mission-critical workflow tools are not ripping them out and replacing them with ChatGPT. That's a fantasy dreamed up by people who have never managed enterprise IT procurement. |
What is changing is which software companies will thrive and which will struggle. And that distinction is exactly where the opportunity lives. |
Think about it this way: if AI is going to be embedded into every business process — and it will be — then the software platforms that serve as the connective tissue of the enterprise are going to become more valuable, not less. The data layer, the identity layer, the security layer, the compliance layer, the vertical workflow layer — these aren't going to be replaced by AI. They're going to be amplified by it. |
And here's the real kicker: AI is not just a threat to software companies. It's also the single greatest cost-reduction and margin-expansion tool these companies have ever had access to. |
The AI Margin Story Nobody Is Talking About |
While the market obsesses over the revenue threat AI poses to software, almost nobody is talking about the cost opportunity. This is where we think the real alpha lives. |
Software companies are, by their nature, operationally leveraged businesses. Their cost structures are dominated by three things: engineering headcount (R&D), sales and marketing, and general overhead (G&A). All three of these are about to get dramatically more efficient. |
Engineering and R&D. AI coding assistants are already increasing developer productivity by 30-50% at leading software companies. This means you can ship the same product roadmap with fewer engineers — or ship a more ambitious roadmap with the same team. Either way, R&D as a percentage of revenue comes down. For a company spending 25-30% of revenue on R&D, even a modest efficiency gain drops multiple points of margin straight to the bottom line. |
Sales and marketing. AI is transforming the go-to-market motion. Intelligent lead scoring, automated SDR outreach, AI-assisted demos, and predictive churn models are reducing customer acquisition costs. Companies that lean into AI-powered sales motions will see their S&M spend as a percentage of revenue decline meaningfully. This is especially powerful for companies with product-led growth motions that can leverage AI to reduce their reliance on expensive enterprise sales teams. |
General and administrative. Finance, legal, HR, customer support — all of these functions are being transformed by AI. Support ticket resolution is being automated. Contract review is being accelerated. Financial close processes are being streamlined. G&A leverage is the least sexy part of the story, but it's real and it compounds. |
Add it all up and you get a picture that the market is completely ignoring: many software companies are about to see 500-1000+ basis points of margin expansion over the next 2-3 years, driven almost entirely by AI-enabled cost efficiencies. Companies that were operating at 15-20% free cash flow margins could be at 25-30%. Companies already at 25% could be approaching 35-40%. |
And here's the punchline: the market isn't giving them credit for any of it. It's pricing these stocks as if margins are going to compress, when in many cases they're about to expand. |
That's a setup. |
Not All Software Is Created Equal |
Now, we need to be clear: not every software stock that's been beaten down is a buy. Some of these companies genuinely face existential risks. The point-solution customer service platform that does nothing but route tickets? That's probably in trouble. The basic data integration tool that AI can replicate natively? Probably in trouble. The horizontal SaaS product with no differentiated data moat, no switching costs, and commoditized functionality? Yeah, that one's going to struggle. |
But many software companies are being painted with the same brush when they have fundamentally different risk profiles. A vertical software company with deep domain expertise, proprietary data assets, regulatory moats, and 95%+ gross retention is not the same animal as a horizontal point solution with 85% retention and a product that an LLM can approximate. |
The market is not making this distinction right now. And that's the opportunity. |
The Underwriting Checklist: What to Look for in Undervalued Software Stocks |
We've spent the last several weeks building our framework for evaluating beaten-down software stocks. Here's what we're looking for — a checklist for investors who want to separate the real opportunities from the value traps. |
Revenue Quality and Durability |
Gross retention rate above 90%, ideally above 95%. This is the single most important metric. Gross retention tells you how much revenue sticks around before any upselling. A company with 95%+ gross retention has a product that customers genuinely depend on. That's a moat. If gross retention is below 85%, the product may be discretionary or easily replaceable — exactly the kind of thing AI disrupts. |
Net revenue retention above 110%. This tells you the existing customer base is expanding. It means the product is becoming more embedded, not less. In a world where CIOs are consolidating vendors, companies with strong NRR are the survivors — they're the platforms customers are consolidating onto, not away from. |
Recurring revenue above 85% of total revenue. We want subscription or consumption-based revenue, not one-time license or services revenue. Predictable, recurring cash flows are what underpin a software valuation premium. |
Low customer concentration. No single customer should represent more than 5-10% of revenue. Concentration risk amplifies in downturns. |
Competitive Position and AI Resilience |
Proprietary data advantage. Does the company sit on unique, proprietary datasets that get better with more usage? Software companies that own the data layer — customer transaction data, compliance records, industry-specific operational data — have natural moats that AI cannot replicate. In fact, AI makes this data more valuable because it can be used to train models that further differentiate the product. |
Workflow embeddedness. Is the software a "system of record" that sits at the center of a critical business process? If removing the software would require retraining teams, migrating years of data, and redesigning processes, that's a real switching cost. These companies are not getting ripped out. |
Vertical specialization. Vertical software companies — those serving specific industries like healthcare, financial services, real estate, construction, government — tend to have deeper moats than horizontal players. Regulatory expertise, industry-specific workflows, and domain knowledge are hard to replicate with general-purpose AI. |
AI as tailwind, not headwind. Is the company using AI to make its product better, or is AI making the company's product obsolete? The best opportunities are companies where AI integration enhances the value proposition — think AI-powered anomaly detection in cybersecurity, AI-assisted diagnostics in healthtech, or predictive analytics in supply chain software. These companies aren't being disrupted by AI; they're weaponizing it. |
Competitive moat beyond the software itself. Does the company have network effects, regulatory certifications, integration ecosystems, or distribution advantages that would take years to replicate? A platform with 500 pre-built integrations into an industry's ecosystem isn't getting replaced by a chatbot. |
Financial Health and Capital Efficiency |
Rule of 40. Revenue growth rate plus free cash flow margin should exceed 40%. This is the classic efficiency metric for software companies. In the current environment, we're especially focused on companies that achieve the Rule of 40 through a combination of healthy growth (10-20%+) and strong margins, rather than high growth masking poor unit economics. |
Positive and growing free cash flow. Cash is king, especially in a risk-off environment. We want to see companies that are actually generating free cash flow — not burning it. Free cash flow yield is becoming an increasingly important metric as the market shifts from rewarding growth to rewarding cash generation. |
Free cash flow margin trajectory. Look for companies where FCF margins are expanding or have clear line of sight to expansion. This is where the AI cost story comes in — companies that can articulate how AI will drive operating leverage are going to re-rate faster than those that can't. |
Clean balance sheet. Low or no net debt. Ideally a net cash position. In a higher-rate environment with compressed multiples, leverage is a killer. Companies with fortress balance sheets can weather the storm and even go on offense with opportunistic acquisitions. |
Capital allocation discipline. Is management returning cash to shareholders through buybacks? In a down market, accretive share repurchases at compressed valuations are massively value-creating. Companies buying back 3-5%+ of their float annually at these prices are compounding shareholder value in a way the market isn't pricing in. |
Valuation and Setup |
EV/FCF below 20x on current-year estimates. In a world where the S&P 500 trades at 19x forward earnings, a software company with durable recurring revenue, high gross margins, and expanding FCF margins trading at or below market multiples is likely mispriced. |
EV/Revenue relative to growth. Look for companies where the EV/Revenue multiple has compressed significantly below its 5-year average, but where the underlying growth rate has not deteriorated proportionally. That gap between multiple compression and fundamental deterioration is your margin of safety. |
Earnings revisions stabilizing or inflecting. The worst time to buy is when estimates are still falling. Look for names where consensus estimates have stabilized — or better yet, where analysts are starting to nudge numbers higher. Estimate revisions are one of the most powerful drivers of stock prices. |
Insider buying. When management is buying stock with their own money at these levels, it's a signal. Not a guarantee, but a signal. Pay attention to cluster buys from multiple insiders, especially C-suite and board members. |
Management and Execution |
Credible AI strategy. Does management have a clear, articulated plan for how AI will be integrated into the product and the cost structure? Companies with vague "AI-powered" buzzwords slapped on their marketing are not the same as companies that can quantify the impact of AI on their margins and competitive position. |
Track record of operational discipline. Has management demonstrated the ability to manage costs in a downturn? Look at how the company navigated 2022-2023. Did they cut costs quickly and protect margins, or did they burn cash and hope for a recovery? Past behavior is the best predictor of future behavior. |
Aligned incentive structures. Is management compensation tied to FCF and margin metrics, not just revenue growth? This matters enormously in the current environment. You want teams that are incentivized to generate cash, not just grow at all costs. |
High insider ownership. Founders and executives with significant personal stakes in the company tend to make better long-term decisions. Skin in the game matters. |
The Intangibles |
Platform optionality. Can the company become a platform that others build on? Software companies that evolve from point solutions into platforms with developer ecosystems and marketplace effects tend to see their multiples expand dramatically as they scale. |
M&A upside. Is the company a potential acquisition target? In a world of compressed public multiples and record private equity dry powder, profitable software companies with strong retention metrics are attractive targets. Strategic acquirers are also looking to buy AI capabilities and customer bases. A takeout premium provides a natural floor on the stock. |
International expansion runway. Is the company primarily domestic with a large untapped international opportunity? Geographic expansion can drive years of incremental growth without the same competitive dynamics facing the core market. |
Regulatory tailwinds. Is the company in a sector where increasing regulation drives demand for compliance software? Cybersecurity, healthcare IT, financial compliance, and data privacy are all areas where regulatory requirements are increasing, not decreasing — creating durable, non-discretionary demand. |
The Bottom Line |
Here's what we believe: the 2026 software selloff is real, but it's been taken too far. The market is pricing the sector as if AI is going to destroy all software companies when, in reality, AI is going to destroy some software companies, leave many perfectly intact, and make quite a few significantly more valuable. |
The names trading at 10-15x forward earnings with 90%+ gross retention, expanding free cash flow, clean balance sheets, and genuine AI tailwinds are not going to zero. They're going to compound. And they're going to compound from a starting valuation that hasn't been this attractive in nearly a decade. |
The setup is remarkably similar to buying quality tech stocks in late 2022, when the market was convinced rising rates would permanently impair every growth company. That turned out to be one of the best buying opportunities in years. We think this moment has the same potential — but only if you're disciplined about separating the winners from the losers. |
That's exactly what we intend to do. |
What Comes Next |
Over the coming weeks and months, we're going to be rolling up our sleeves and digging through the wreckage. We'll be running every software stock we can find through the checklist above — analyzing retention metrics, FCF profiles, competitive positioning, AI strategies, and valuation. When we find names that pass the test, we'll write them up in detail: the bull case, the bear case, the risks, the valuation, and our honest assessment of whether the stock is genuinely cheap or just cheap for a reason. |
Some of these will be well-known large caps that have been unfairly punished. Some will be mid-caps that most investors have never heard of. Some might be small-cap names trading at absurd valuations because they've been caught in the indiscriminate selling. |
We don't know exactly what we'll find yet. That's the point. The work hasn't been done, and most of the market is too scared or too lazy to do it. We're not. |
If you believe, as we do, that software is not dead — that recurring revenue still matters, that margins still matter, that cash flow still matters, and that the best software companies in the world are about to get meaningfully better because of AI — then stick around. The next few months are going to be interesting. |
The market is giving us a gift. Let's not waste it. |
If you found this useful, subscribe so you don't miss the deep dives coming over the next few months. We'll be publishing our first individual stock analysis soon. |
