Why Enterprise Software Is Becoming Harder – Not Easier – to Buy

Enterprise software has never been especially simple to buy, but the commercial side is becoming harder to untangle. AI features can introduce new consumption charges and vendor-specific pricing metrics, while expanding software suites make it harder to isolate the cost and value of individual capabilities. To understand how the buying process is changing, ITPro spoke to Haritha Khandabattu, VP Analyst at Gartner, Mickey North Rizza, Group VP for Enterprise Software at IDC, and Faram Medhora, Principal Analyst at Forrester. All three describe a market in which the relationship between licence counts and eventual spend is becoming less predictable. IT leaders now have more to work out before they can judge whether a deal will still make sense once the software is in use. The unit of software is changing For many seat-based enterprise products, the basic maths was relatively easy to follow: multiplying the number of users by the licence price gave buyers a reasonable estimate of spend across the contract term. AI consumption models make that calculation trickier. Khandabattu says pricing has shifted towards vendor-specific units such as tokens, credits, work units, and currency multipliers, often layered on top of existing seat or subscription charges; those units rarely translate neatly between suppliers. “One vendor’s token isn’t another’s, credits get repriced, and metrics get renamed mid-contract,” she says. Consumption pricing also weakens the traditional relationship between user numbers and software spend, according to Khandabattu. A single AI agent can trigger chains of API calls and other metered activity, with usage varying considerably according to the task. “A seat is a budget line; an agent is a behavior pattern,” Medhora says. “If buyers do not model the behavior pattern, they have not modeled the cost.” Procurement teams can enter negotiations with little production data on how heavily an AI service will actually be used. Forecasting lifetime spend becomes much harder when they have yet to see that consumption at scale. Something as simple as a misconfigured agent could burn through many more tokens than procurement teams were expecting, and stopping agents in the act is difficult. It’s becoming harder to know what you’re actually buying Pricing is only part of the problem. AI capabilities are being added to software that businesses already use, and organizations are consolidating more functions into larger software suites. Procurement teams need a clear picture of what a new feature adds before paying for another licence or upgrading an existing one. Medhora suggests judging AI add-ons by the business outcome they produce, including whether they measurably improve an existing process or provide something the current software estate cannot. “If the answer is only a better-looking prompt box, it is not a value case; it is a packaging exercise,” he says. The same capability may already exist elsewhere in a sprawling software estate. North Rizza points to the continued accumulation of tools across organizations, often without a complete view of which products are being used or where their functions overlap. IDC’s research also shows businesses consolidating around larger software suites, which can reduce the number of separate vendors while leaving individual capabilities inside those bundles harder to price and track. North Rizza highlights moves from perpetual licences towards subscription bundles and AI capabilities folded into renewals. She also points to the importance of preserving portability and exit rights when software is acquired through a wider services contract. Buyers also need to consider how the product might be repackaged or renewed, and what replacing it would involve if the commercial terms change. Procurement has to adapt to uncertainty Khandabattu recommends setting an internal measure of value before comparing vendors, then translating each supplier's pricing units into it. For example, a token, credit, message, or seat can then be expressed as a cost per support ticket resolved, invoice processed, or another meaningful business outcome. Khandabattu distinguishes that internal benchmark from vendor-defined outcome pricing, which she says remains immature and can tie buyers to measures whose value is difficult to establish. She also advises buyers to test representative workloads rather than relying on vendor calculators. Running production-like tasks can expose how quickly consumption builds up, including cases where what looks like a single action triggers several separately metered steps. Modelling that usage over two or three years gives procurement teams a firmer basis for comparing suppliers. Khandabattu also recommends looking at fully loaded costs, including integration, governance, and human oversight, rather than the metered charge alone. North Rizza puts estate rationalisation ahead of another purchase or renewal. IT teams should first identify what is already deployed and where functionality overlaps, a process that can also reveal products that can be retired or replaced. IDC also recommends treating AI cost governance as an ongoing responsibility shared across IT, finance, engineering, and FinOps rather than a one-off procurement exercise. Contract negotiations need to account for that uncertainty as well. Khandabattu recommends defining billing units clearly in the contract and pushing for protections against unilateral changes to pricing metrics, alongside measures such as credit rollover where appropriate. North Rizza points to modular licensing, meaningful evaluation periods, portability, and exit rights as ways to reduce exposure if usage or vendor strategy changes after deployment. “Don’t wait for pricing models to settle down – build your forecasting discipline now, because the volatility is the new normal, not a transition phase,” North Rizza says. Medhora says procurement teams should put greater weight on metering rights and usage visibility, while modelling different commercial scenarios and preserving leverage if they need to exit. Keeping control after the contract is signed The buying process increasingly extends through the life of the contract. IT leaders need to see how costs develop in production and whether the promised benefits survive real-world use. They also need enough visibility to identify capabilities that are no longer worth paying for. A large discount at signing offers limited protection if usage is opaque or the contract is difficult to unwind; a better deal gives the buyer enough visibility to keep measuring value, with room to change course if costs move beyond the original business case.