The SaaS Tools You Pay For Are in Trouble. Here's What That Means for Your Business.
By Warren Schuitema, Founder | Matchless Marketing | The AI Dad
The software industry just had one of its worst years on record, and most small business owners haven't noticed yet.
Public SaaS companies have shed nearly two trillion dollars in market value in 2026. That's not a dip. That's a structural shift, and the thing driving it is the same thing sitting in your browser right now: AI agents.
TechCrunch Disrupt 2026, running October 13–15 in San Francisco, just published their AI Stage agenda. The sessions are aimed at enterprise founders and VCs, but the topics they're debating behind those doors land directly in your lap. The SaaS reckoning. The agent security gap. What pricing even looks like when AI does the work your software used to do.
You don't need a conference ticket to act on this. You need to understand what's actually happening.
The Per-Seat Model Is Breaking
Most of the software you pay for right now charges you per user. One seat for you, one for your assistant, one for your VA, one for whoever else needs access. That model made sense when humans were doing the work.
AI agents don't need seats. They log in, they complete tasks, they don't take vacations, and they don't need a dedicated license. When one AI agent can handle what used to require three people accessing three separate tools, the per-seat pricing model collapses.
This is forcing SaaS providers to rethink whether to price plans based on actual value delivered rather than the number of users logging in. Some won't figure it out fast enough. Others will pivot and survive. Either way, the tools you're counting on for your business operations are in the middle of an identity crisis.
The practical implication for you: any tool you're paying for on a per-seat basis is worth auditing right now. Are you paying for seats you're not fully using? Are you paying for features an AI agent could replace entirely? This isn't theoretical. It's a real line item on your monthly expenses.
Agent Security Is the Gap Nobody Warned Small Business Owners About
Here's the part that actually concerns me for people running lean operations.
AI agents have moved from experimental demos to production systems faster than security teams can keep up. According to the Gravitee State of AI Agent Security 2026 report, over 80% of technical teams have pushed past planning into active testing or production, but only 14.4% of those agents went live with full security and IT approval.
That data is about enterprise teams. Now think about the solo operator or small business owner who installed an AI automation last month because a YouTube video made it look easy. Nobody audited those permissions. Nobody reviewed what data that agent can access. Nobody set boundaries on what it's allowed to do.
Agentic AI is powerful, but it was never built to be secure. Enterprises trying to harness it are now learning to rebuild the basic elements of cybersecurity from scratch.
The specific risk is prompt injection. A single injected instruction can drive an agent through thousands of automated actions, and in multi-agent setups, a compromised agent can pass false outputs downstream, cascading the failure across permission boundaries. In plain terms: if your AI agent reads your email and takes action based on what it reads, a malicious email could theoretically instruct that agent to do something you never authorized.
This isn't a reason to stop using agents. It's a reason to be deliberate about how you set them up.
What This Actually Means for a Small Business Running AI Tools
I'm not here to scare you. I'm here to give you the version of this conversation that actually applies to a business your size.
The enterprise world is scrambling to build governance frameworks, observability layers, and security audits around their AI deployments. You don't need all of that. But you do need a version of it.
Here's what that looks like at the small business level:
Know what your agents can touch. If you've connected an AI tool to your email, your calendar, your CRM, or your payment processor, you need to know exactly what permissions that tool has. Not roughly. Exactly. Go look at the connected apps in your Google account, your Notion workspace, your email provider. If you see permissions you don't recognize or don't use, revoke them.
Don't over-permission your automations. When you build a workflow in n8n or a similar tool, give it the minimum access it needs to do the job. If the automation only needs to read emails from one folder, don't give it access to your entire inbox. Least-privilege is the principle. It applies to you even if you've never heard the term.
Run AI agents on data you'd be comfortable losing. This sounds counterintuitive, but it's a useful mental test. If your agent makes an error or gets manipulated, what's the worst case? If the answer involves client payment data, proprietary contracts, or anything that would cost you a relationship if it leaked, that agent needs tighter controls before it touches that data.
If you use AI tools that read your email, web content, or customer messages and take action, ask how the vendor isolates that input from its instruction set. Most vendors have a support page for this. Most people never look at it.
The Bigger Picture: A Better Way to Think About Your Software Stack
The SaaS reckoning isn't just a Wall Street story. It's a signal that the software layer underneath your business is being renegotiated.
The real questions being debated right now are about how to price AI products when models become commoditized, why agent security has to be rebuilt from the infrastructure up, and what it actually means to have a go-to-market plan in an AI-native world. Those are enterprise questions, but they trickle down fast.
What I'd encourage you to do is look at your software stack right now as two distinct categories. First: tools that do something AI can't yet replace reliably, things like bookkeeping compliance, legal document management, specialized industry software with deep integrations. Keep those. Second: tools that are essentially just a UI on top of tasks that AI can now do natively. Think scheduling assistants, basic CRM automation, social media schedulers, template-heavy content tools. Those are the ones worth questioning.
I'm not saying cancel everything. I'm saying the next time a renewal lands in your inbox, ask the question. Is this tool solving a real problem, or is it solving a problem that no longer requires dedicated software?
That question is worth more than a conference ticket.
One Thing to Do Before Your Next Software Renewal
Pull up your bank statement or your credit card from last month. Find every SaaS subscription you're paying for. For each one, write down one sentence: what problem does this tool solve that I couldn't solve with an AI agent and a basic workflow?
If you can't write that sentence in 30 seconds, you've found your audit target.
The tools worth keeping will be obvious. The ones that aren't will surprise you. And the money you recover is money you can put into building the AI systems that actually move your business forward, instead of maintaining software that was built for a world that's changing faster than its pricing model.
The SaaS reckoning is real. Your job is to get ahead of it before it shows up on your P&L.