# 73% of AI Pricing Professionals Favor Flexible Models. Blanket Premiums Are Collapsing

G2 Research examines why buyers now demand measurable value, visible spend, and flexible pricing before approving an AI premium. Based on 588 in-depth interviews with business professionals, the report finds that AI buying is moving away from blanket premiums and toward proof-based, usage-aware commercial models.

**Analyst:** Anubha Garg

## Key Findings

Seventy-four percent of respondents treat AI as recurring operating expense or subscription spend rather than a one-time capital purchase.

Sixty-six percent accept only a modest AI premium when value is justified, while 14% treat any premium as a dealbreaker.

Sixty-four percent point to efficiency and workflow gains as the leading reason to approve AI spend, with 31% requiring hard ROI or another measurable business impact.

Seventy-three percent prefer usage-based or hybrid consumption pricing over flat bundled subscriptions.

## Executive Perspective

Alex David, GM of AI Solutions at G2, explains that buyers want control over AI spend without being locked into tools that could become redundant quickly. Vendors face the opposite pressure because token and inference costs make unpredictable usage risky. Usage-based pricing is therefore not just a packaging preference; it reflects a structural shift toward economics that can work better for both buyers and vendors.

## Chapter 1: How AI Spend Gets Approved

AI enters the budget most often as recurring software spend. That makes adoption easier to start and forecast, but it also puts usage, renewal proof, and cost visibility under continuous scrutiny. A premium has to remain legible after the first purchase.

## Chapter 2: What Makes a Premium Defensible

Efficiency opens the AI business case, but financial proof keeps it alive. Workflow improvements, measurable ROI, quality improvements, risk reduction, cost savings, revenue impact, and margin protection all shape whether an AI premium survives budget review.

## Chapter 3: Pricing That Scales With Value

The preferred AI pricing model combines a predictable base with a visible usage layer. Buyers want pricing that reflects understandable usage and realized value, while vendors need a model that preserves margin as compute and token costs scale.

## Chapter 4: Where Buyers and Vendors Diverge

A supplementary classification of the same interview set shows buyer and vendor expectations diverging. Buyers with a clear preference lean toward usage-based or hybrid pricing, while vendors commonly describe bundling AI into enterprise tiers. The mismatch creates renewal risk when customers cannot connect the bundle to actual value.

## Strategic Patterns

The interviews show that buyers treat pricing, governance, workflow proof, and renewal as one decision. Low-friction pilots still need a path to scalable spend, visibility before expansion, and evidence before the next approval.

## Recommendations

AI vendors should prove impact at the workflow level, make usage visibility part of the product, and pair a predictable base with transparent metering. Pricing power improves when customers can see, forecast, and defend the variable cost of AI.

## FAQ

### How are most organizations budgeting AI today?

Most organizations budget AI as ongoing software spend. In G2's AI pricing research, 74% classify AI as recurring Opex or subscription cost, compared with 5% who frame it as CapEx.

### Are buyers willing to pay more for AI features?

Yes, but the acceptable range is narrow. Sixty-six percent accept only a modest premium when value is justified, 14% pay more for clearly better AI, and 14% reject a premium.

### What kind of value justifies AI spend?

Efficiency opens the business case. Sixty-four percent cite efficiency and workflow gains as the leading justification, while 31% require hard ROI or another measurable impact.

### Why are governance and visibility important in AI buying?

Governance keeps recurring AI spend legible. Fifty-eight percent want visibility into usage and spend, 32% prefer vendors to manage backend costs, and 10% want direct internal control.

### Which pricing models best fit buyer expectations?

Usage-based or hybrid pricing best fits current buyer expectations. Seventy-three percent prefer consumption-linked structures, compared with 25% who prefer a bundled flat subscription.

### Does pricing preference differ between AI buyers and vendors?

Yes. A supplementary classification finds that 76% of buyers with a clear preference want usage-based or hybrid pricing, while 68% of vendors describe bundling AI into an enterprise tier.

## Methodology

G2 Research interviewed 588 business professionals across roles, industries, and company sizes, including technology, financial services, healthcare, manufacturing, and retail. Interviews lasted up to 31 minutes and covered AI pricing structure and packaging, tolerance for AI premiums, outcomes used to justify spend, and AI cost governance, visibility, and operating control. G2 used AI to analyze the transcripts for semantic understanding, then ran multi-iteration validation and cross-verification. G2's AI Custom Research team independently reviewed each transcript to inform the narrative, context, and conclusions.

**Topics covered:** Software Buying, Pricing & Monetisation