From health care to hospitality, nearly every industry relies on people to handle critical, repetitive, or administrative tasks that keep operations running. Nurses, compliance officers, call-center agents, and countless other professionals have been indispensable—yet in many cases, the software they use has barely scratched the surface of their actual, day-to-day work.
In a wide-ranging conversation at a16z, General Partners Alex Rampell, David Haber, and Angela Strange explored how advances in artificial intelligence are enabling software to do more than merely store data or reduce paperwork. Today’s AI tools can act on that data in ways once reserved for humans, unlocking what they call a massive new market at the intersection of software and labor.
Below are the key takeaways from their conversation, distilled into five major insights.
The Digital Filing Cabinet
Historically, the most common enterprise software replaced physical filing cabinets with databases, digitizing and centralizing record-keeping. Over decades, organizations transitioned from scribbling entries on paper to using local servers and software installed in-house. This was a huge leap forward, but it didn’t eliminate the need for people to manage those files, interpret them, and perform the next steps.
The Cloud Revolution
A second major wave arrived when software moved “to the cloud.” Early innovators like Salesforce, Netsuite, and ZenDesk took traditional enterprise software and hosted it online. Companies no longer needed huge IT teams to maintain on-premise servers, and it became more cost-effective for smaller businesses—like mom-and-pop restaurants or specialty shops—to adopt software services.
Financial Services-Enabled Cloud
Then came the era of vertical SaaS (software-as-a-service), where companies like Toast (for restaurants) or ServiceTitan (for contractors) bundled in payments, insurance, and other financial services. This expanded the total addressable market dramatically, making software relevant to businesses that previously couldn’t justify big tech expenditures.
The AI-Enabled Outcomes Era
Now, AI is unleashing an entirely new set of capabilities: software that not only stores or surfaces data, but that acts upon it—executing the tasks humans used to do. It’s no longer just about managing your “filing cabinets” in the cloud; it’s about automated agents that can interpret a request and complete the work end to end.
Healthcare: The $600 Billion Nurse Market
Nursing in the U.S. is a $600+ billion annual labor market—but the software developed exclusively for nurses is near zero. AI could automate tasks like pre-appointment instructions or post-procedure follow-ups, freeing clinicians to focus on hands-on, patient-facing care. Software that can support nurses in 45 different languages or manage everyday communications is a new frontier—and that’s just one profession.
Compliance Officers: An Overlooked Trillion-Dollar Need
Another example is compliance in financial services. Until now, banks have hired full-time compliance officers to process endless streams of data and paperwork—often using tools as basic as Microsoft Excel. AI-based systems that can automate compliance checks and handle huge volumes of data in seconds represent a massive opportunity. Because there’s essentially no existing incumbent software for compliance officers, new AI-native players can step in and build the system of record from scratch.
The Co-pilot Approach
Many established software products like Salesforce or ZenDesk have historically been sold per “seat”—they get paid for each human using the platform. AI “co-pilots” can now make these workers far more productive by suggesting replies or analyzing data. But there’s a twist: if each worker becomes 10 times more productive, you don’t need as many seats. Incumbent software players risk losing revenue under seat-based pricing.
The Autopilot Approach
Alternatively, “autopilot” style AI might reduce the need for certain roles entirely. Rather than empowering one support agent to handle 10X more customer queries, advanced AI could handle those queries directly—meaning zero seats in some cases. While AI copilot is a partial step, autopilot is the next level that could radically reshape entire business models.
Pricing Shakeups
Incumbent players built on per-seat or subscription models face a dilemma: to adopt AI aggressively and risk cannibalizing their seat-based revenue, or to cede the wave of AI-native startups that might undercut them by bundling labor and software in a single product.
Expanding the Market Size
AI-driven products can chase opportunities that once seemed too small for traditional software. Companies can begin by automating the “messy inbox problem” (unstructured communication like emails, faxes, voice transcripts) and then expand into full-fledged systems of record. Freed from costly or scarce human labor, software can scale into markets that once had no budget at all.
Same Metrics, Bigger Potential
Even in AI, fundamental business metrics remain the same: retention, margins, profitability, and the potential for expansion or upsell. What’s changed is the market opportunity itself—suddenly, capturing labor budgets could 10X or more the revenue that was historically limited to “software budgets.”
Full-Stack Approaches
In some industries, it may be easier to build a full-stack AI-based solution than to sell AI modules to incumbents. Consider an “AI-native Law Firm” that charges via contingency fees, or an “AI-based Healthcare Agency” that handles patient referrals from end to end. Because they align AI’s cost savings and outcome-based pricing, these new entrants can be much nimbler—and more profitable.
Human Connection Becomes More Valuable
As AI takes on monotonous tasks, the remaining human roles will emphasize creativity, empathy, and relationship-building. Far from eliminating all jobs, the panel suggests AI will shift them—similar to how farming’s evolution freed people for new, higher-value pursuits.
Defense and Offense for Incumbents
Big players like Salesforce could either see their revenues collapse—or skyrocket. It all depends on how quickly they adapt to AI’s potential. Meanwhile, entrepreneurial startups can use AI as a wedge, solving messy workflows and building new systems of record from the ground up.
A Future of Growth and Deflation
Technology is fundamentally deflationary: it drives cost savings, speed, and efficiency. Over time, tasks that used to cost thousands of dollars (like launching a legal case or adding specialized nursing staff) may be streamlined to mere dollars. At the same time, these lower costs often expand demand, growing entire markets.
Far from a narrow disruption, the AI-enabled era marks a pivot from record-keeping to outcome-producing software. Whether AI is used as a co-pilot to assist workers or transforms into full-blown autopilot handling entire workflows, the potential to unlock productivity is vast. For venture-backed startups and incumbents alike, figuring out how to integrate AI in a defensible, value-aligned way remains the critical challenge.
Yet where others see risk and displacement, many entrepreneurs and investors see possibility. After all, it’s precisely when technology jumps to a new performance curve that foundational business assumptions can flip upside down—opening fertile ground for the next wave of “generationally defining” companies.
If the panel’s insights are correct, AI won’t just expand the possibilities of traditional software; it will redefine the very relationship between technology and work—creating an era in which the size and scope of markets could soar beyond what we once imagined.
