Enterprise software vendors are transitioning from per-seat pricing to consumption-based and agent-interaction pricing models
The old model, licensing software based on the number of people using it, is being retired. Fast. Blame the rise of AI automation. Tasks once handled by employees are now carried out by algorithms and autonomous agents. When fewer humans do the work, “per-seat” pricing makes less sense. Software vendors are adjusting. What we’re seeing now is pricing tied directly to activity, what gets done, how often, and at what scale. Units like API calls, agent interactions, and tokens are becoming the new pricing currency.
This shift is happening across the big players. Salesforce has already moved in this direction with Agentforce, and others like Workday are close behind. The transition isn’t a maybe, it’s active and accelerating. A recent IDC report confirms it: by 2028, pure seat-based models will be obsolete. Around 70% of vendors are projected to refactor their pricing strategies to reflect digital labor, not human headcount.
This new reality demands a new mindset from CIOs, CFOs, and procurement leaders. If your organization doesn’t have clear metrics to track AI activity, usage patterns, and output volume, you’ll be flying blind in negotiations. What used to be a static license fee becomes a living, breathing cost structure, impacted day-to-day by how software is used, not simply by who uses it.
The more autonomous the system, the harder it becomes to connect effort to expense. That’s a problem if you don’t track consumption accurately. But it’s also an opportunity. Done right, paying for performance can align spending with business outcomes. Bigger efficiencies mean more room for innovation. It starts with vertical alignment in your team, from IT ops to finance, so everyone understands the operational behaviors driving spend.
Bottom line: the shift to consumption-based pricing is happening fast. Ignore it, and your costs will spiral. But if understood and leveraged properly, this change creates tighter control, real scalability, and long-term operational momentum. Don’t wait for renewal cycles to start figuring it out, by then, your pricing model will already be obsolete.
New pricing models create cost unpredictability and transfer significant risk to enterprise customers
Here’s what’s happening behind the scenes. Software vendors are redesigning pricing models to push risk onto customers. Instead of fixed, predictable licensing, they’re introducing new billing units like “credits,” “interactions,” and “events.” The problem? Most of these units are loosely defined, if at all. You won’t know exactly what you’re paying for until the invoice shows up, and by then it’s too late.
Costs are no longer tied to user count. They’re tied to system activity, some of which your teams might not even realize is metered. AI interactions, for instance, can scale fast. Without guardrails, it’s easy to overshoot thresholds. When a vendor doesn’t disclose the limit, or build-in alerts, and you cross that line, you’re hit with overages. These extra charges aren’t minor either. Some are significant enough to blow past departmental budgets in a matter of weeks.
Sanchit Vir Gogia, Chief Analyst at Greyhound Research, explains it clearly: vendors are offloading the cost volatility of running AI infrastructure onto customers. Meanwhile, they keep the upside, monetizing the productivity gains triggered by that same automation. That’s a structural shift. What used to be stable, linear billing is being replaced with variable-rate systems built to preserve vendor margins and limit customer visibility.
These revenue models are growing faster than enterprise procurement or finance teams are adapting. That imbalance creates a gap vendors can exploit. Without deep knowledge of AI systems, telemetry, or usage signals, your teams won’t catch risky usage patterns in real time. Contracts don’t account for this misalignment yet. That’s a problem, especially as more compute-intensive tools hit the market under similar consumption terms.
If you can’t directly measure the new billing units, you can’t contain the cost. Risk migrates to you, and your visibility erodes. It’s unnecessary if tackled early. You need clear pricing logic, usage transparency, and contractual protections that match the speed and complexity of modern software operations. Otherwise, budgets become estimates, and CFOs are left reacting to unexpected escalations.
CIOs need to negotiate contracts more aggressively and clarify usage definitions to safeguard against cost overruns
Enterprise software contracts are changing. The terms that used to be straightforward, like per-user pricing, no longer apply. Now, usage determines cost. That shift demands a different negotiation strategy. The priority is definition. You can’t control what you can’t define. Clarify exactly what “usage” means in your agreement: Is it triggered when a user logs in? Does background activity count? What about automated backups or AI agent tasks performed at night?
Ambiguity is a cost multiplier. Adam Mansfield, advisory leader at UpperEdge, has seen multiple cases where companies unknowingly exceeded volume caps. The issue? Their contracts didn’t specify what constituted a “conversation” or other vital unit of measurement. Without explicit terms, many firms triggered higher charges they didn’t anticipate, or could have avoided through up-front planning.
Another practical step: negotiate usage ceilings. Put accountability on the vendor to notify you, formally, in writing, if consumption is nearing contractual limits. Unless you authorize it, they can’t charge for overages. This isn’t about pushing back hard; it’s about setting the rules of engagement early and exactly. Defined ceilings, with written thresholds and review periods, help you stay in control of unpredictable billing cycles.
Timing also matters. Jason Andersen, Principal Analyst at Moor Insights & Strategy, recommends negotiating a one-year deferral before new pricing models activate. That window gives CIOs the data they need to track current usage, simulate future scenarios, and adjust internal systems. It also allows investment in FinOps and observability tools without operating under immediate cost pressure. You’re buying time to build visibility and control.
Aaron Perkins, CEO of Market-Proven AI, notes that switching software providers isn’t often realistic. The costs and risks are too high for most enterprises. More importantly, if all major vendors shift in the same direction, there’s nowhere else to go. That makes negotiations even more critical. You won’t solve this with leverage. You solve it with precision, starting by defining usage in terms your team tracks on day one.
Executives should treat contract language the same way they treat financial controls. Every term must be actionable, measurable, and enforceable. The contract sets the structure, but operational discipline determines the outcome. When procurement, finance, and tech leadership align early on these principles, they avoid budget surprises later.
Autonomous AI agents introduce unique pricing risks, potentially leading to financial exploitation if not properly managed
Autonomous software agents change how enterprise systems operate, and how they generate cost. In a consumption-based model, these agents don’t just carry out tasks; they trigger charges every time they act. The more activity they generate, the more revenue for the vendor. That creates a clear incentive misalignment if the agent’s behavior isn’t strictly defined, controlled, and monitored.
Jason Andersen, Principal Analyst at Moor Insights & Strategy, points out that agents configured by the vendor in a consumption model have a built-in incentive to produce excessive usage. If the contract doesn’t include safeguards, your system will pay more without necessarily producing more business value. Most enterprises aren’t tracking this type of activity with enough granularity. Without usage thresholds or automated triggers, financial exposure becomes a near certainty.
Technical and contractual protections need to evolve in sync with autonomy. Organizations should implement real-time observability tools to monitor agent behavior and put hard ceilings in place. That means programming alerts and enforcement policies directly into systems, policies that stop agents from exceeding pre-approved token or interaction volumes. These are not just operational best practices, they are essential controls in a billing environment that moves fast and rarely pauses for human oversight.
Per Andersen’s insights, the risk surface isn’t limited to internal misuse. Autonomous agents also present an attack vector. If a competitor or malicious actor spams your customer service systems or initiates repetitive requests, it could result in artificial overages. In a usage-based contract without fraud protection or contingency clauses, that cost still lands on your balance sheet.
The solution? Build circuit-breakers into your contracts. Make it clear that in cases of proven attack or fraud, the vendor absorbs those costs. This has to be explicitly written into the agreement and backed by measurable auditing capabilities. Without this, usage-based pricing opens the door to cost volatility that has nothing to do with genuine enterprise demand.
For C-suite decision-makers, this is where operations, risk, and legal strategies intersect. If AI agents are driving business processes, then their behavior must be verifiable and bounded. Cost discipline doesn’t come only from smart purchasing, it comes from designing pricing-aware systems that don’t expose the organization to variable, untracked usage. You’re not negotiating just for features anymore; you’re negotiating for control.
Main highlights
- Software pricing is shifting fast: CIOs should prepare for a broad industry move away from seat-based pricing toward usage and AI-driven models. This will require close monitoring of system activity and a deep understanding of how consumption drives cost.
- Vendors are offloading risk to you: Usage-based pricing models shift cost volatility to customers through vague billing units like credits or interactions. Leaders should demand transparency and push back on undefined metrics that obscure total cost of ownership.
- Contracts now require precision: Seat-based leverage is gone, and switching vendors is costly. CIOs must negotiate clear usage definitions, enforce ceilings, and ask for implementation delays to build monitoring capabilities and protect budgets.
- Autonomous agents can inflate your costs fast: AI agents increase system activity, leading to unpredictable charges. Organizations should enforce usage caps at the system level and require fraud protection clauses that cover cost spikes due to abuse or attacks.
