For 30 years, enterprise software has sold access. You paid for a licence, a seat, and a login. The moat was the product itself: years of engineering, an ecosystem of integrations, workflows teams had learned to rely on, and switching costs high enough that renewing a contract often felt easier than replacing it. It was an extraordinarily successful model and, arguably, one of the strongest business models the technology industry has produced.
That moat is beginning to thin.
Artificial Intelligence (AI) has dramatically changed the economics of building software. Features that once took months to develop can now be recreated in days, sometimes hours. Internal applications that previously justified dedicated product teams are increasingly being assembled with the help of AI. Enterprise software will always demand security, governance, compliance, and deep integration with business systems, but creating functionality is no longer as expensive or as time-consuming as it once was.
When building software becomes significantly easier, the software itself becomes less scarce. The question for customers shifts as well. They are no longer paying simply because a product exists or because it is difficult to recreate. They are paying for the business result the software helps deliver. Software was never the destination; it was always the mechanism. The real value lies in the outcome.
That has important implications for the commercial model that has defined enterprise software for the past two decades.
{{/usCountry}}That has important implications for the commercial model that has defined enterprise software for the past two decades.
{{/usCountry}}Software-as-a-Service (SaaS) pricing was never really about the software. It was a practical workaround. Measuring the contribution of every application to revenue growth, customer retention, or operational efficiency was difficult, so the industry priced the things it could easily count: seats, storage, usage tiers, and feature gates. That was a sensible compromise when software itself was expensive to build, and business outcomes were difficult to measure.
Those constraints are steadily disappearing.
Consider a company paying for a customer support platform on a per-agent basis. If AI now resolves 80% of incoming tickets without human intervention, what exactly is the customer paying for? Certainly not effort, because much of that effort has shifted to the system. Nor is it access, because access was never the scarce part of the equation. The business is paying for customer issues to be resolved quickly and accurately. The contract, however, still reflects a world in which humans performed the work. Many finance leaders are already beginning to question that mismatch during renewal conversations, even if they have not yet given it a name.
A subscription prices inputs, such as seats, storage, API calls, rather than the business result those inputs are intended to create. AI changes that relationship because it increasingly produces the outcome directly instead of simply helping people achieve it. If a support platform consistently resolves customer issues, the commercial conversation naturally shifts towards the value of those resolutions rather than the number of people logged into the system. This is more than a pricing adjustment. It represents a different commercial relationship, one in which accountability is shared differently.
That shift in accountability is the real story.
Under the SaaS model, vendors are paid for delivering reliable software. Whether that software improves customer satisfaction, reduces costs, or increases revenue depends largely on how well the customer implements and uses it. The execution risk sits primarily with the buyer.
Outcome-linked pricing redistributes that risk. If vendors are paid for resolved tickets, qualified leads, reconciled invoices, or successful fulfilments, they assume greater responsibility for delivering those results. Their incentives become more closely aligned with the customer’s business performance.
That is a significant transition for an industry built on predictable recurring revenue, which explains why many SaaS companies are approaching it cautiously. At the same time, it is becoming easier to understand why customers are asking for it. As software becomes easier to build and AI becomes more capable of executing work, pricing models that are disconnected from business outcomes become harder to justify.
Some enterprise software companies are already experimenting with success-based incentives, guarantees, and commercial models that combine subscriptions with performance-linked fees. Those experiments point towards an emerging category that can reasonably be described as outcome-as-a-service.
The software itself does not disappear. It simply fades into the background. Nobody buys electricity because the wiring is elegant. They buy the machine it runs. Enterprise software is likely to follow a similar path. Customers will continue investing in sophisticated technology, but they will increasingly judge it by the business outcomes it enables rather than the features it contains.
This shift could have particular significance for India.
Much of India’s enterprise software success over the past decade has been built on delivering competitive products at a lower cost than global incumbents. Competing on price was an effective strategy because buyers were comparing products through licences, feature parity, and implementation costs. As value shifts towards outcomes, the basis of competition changes as well. Customers begin asking who consistently improves fulfilment, reduces operating costs, increases conversion, or shortens response times, and they become less concerned with who offers the lowest cost per seat.
There is another reason this transition may favour Indian software companies. Years of operating with lean teams and disciplined unit economics have created organisations that understand efficiency exceptionally well. That discipline transfers naturally to outcome-based models, where commercial success depends on understanding the economics of the customer’s business as well as your own. Companies that redesign contracts around delivered outcomes instead of software access will be well positioned to shape this next phase of enterprise software.
AI is also changing the nature of enterprise products themselves.
SaaS was built around standardised products that could be configured but only customised within defined limits. That approach reflected the economics of software development at the time. Building and maintaining customer-specific workflows at scale was expensive.
AI changes those economics.
For decades, businesses adapted to fit the software they bought because custom systems were too expensive to build. That trade-off is disappearing with the rise of malleable enterprise software. The underlying data remains stable, while workflows, interfaces, and decision logic continuously adapt to how each business operates. Two retailers can use the same platform yet optimise for entirely different goals, whether reducing returns or enabling same-day delivery. The software evolves alongside the business, making adaptability itself part of the value proposition.
For SaaS leaders, the defensible asset has never been the code alone. It has always been a deep understanding of which business outcomes matter and the confidence to stand behind them commercially. Renewing the same seat-based contract year after year preserves a commercial model that belongs to a different stage in the industry’s evolution.
For enterprise buyers, the next renewal conversation is unlikely to revolve around seat discounts alone. It is increasingly an opportunity to ask whether pricing reflects the business outcome the software was acquired to deliver.
For India, this represents a rare opening. A software ecosystem that learned to compete through efficiency, operational discipline, and cost optimisation enters a market that increasingly rewards exactly those capabilities. Software itself is becoming easier to build. Delivering measurable outcomes at scale is becoming the hardest challenge.
The companies that recognise that shift early will do more than build the next generation of enterprise software. They will help define how the industry creates value in the decade ahead.
(The views expressed are personal)
This article is authored by Farooq Adam, founder, Fynd.