# How AI is changing software pricing

DevFeed: [How AI is changing software pricing](<https://devfeed.tech/articles/how-ai-is-changing-software-pricing-92444.md>)

Original publisher: [Read original article](<https://www.infoworld.com/article/4237997/how-ai-is-changing-software-pricing.html>)

Author: Nicole Segerer

Published: 2026-10-21T09:00:00Z

Content type: article

Language: en

Sources: [InfoWorld](<https://devfeed.tech/sources/infoworld.md>)

Topics: [API Business Models](<https://devfeed.tech/topics/api-business-models.md>), [AI Integration Strategies](<https://devfeed.tech/topics/ai-integration-strategies.md>), [product analytics](<https://devfeed.tech/topics/product-analytics.md>), [Product Management](<https://devfeed.tech/topics/product-management.md>)

Tags: [2026](<https://devfeed.tech/tags/2026.md>), [adoption](<https://devfeed.tech/tags/adoption.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-features](<https://devfeed.tech/tags/ai-features.md>), [ai-leaders](<https://devfeed.tech/tags/ai-leaders.md>), [ai-native](<https://devfeed.tech/tags/ai-native.md>), [ai-pricing](<https://devfeed.tech/tags/ai-pricing.md>), [ai-pricing-models](<https://devfeed.tech/tags/ai-pricing-models.md>), [anthropic](<https://devfeed.tech/tags/anthropic.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [artificial-intelligence-software-providers-technology-industry](<https://devfeed.tech/tags/artificial-intelligence-software-providers-technology-industry.md>), [based](<https://devfeed.tech/tags/based.md>), [capabilities](<https://devfeed.tech/tags/capabilities.md>), [chatbots](<https://devfeed.tech/tags/chatbots.md>), [contracts](<https://devfeed.tech/tags/contracts.md>), [cost](<https://devfeed.tech/tags/cost.md>), [customers](<https://devfeed.tech/tags/customers.md>), [device](<https://devfeed.tech/tags/device.md>), [disruption](<https://devfeed.tech/tags/disruption.md>), [language-en](<https://devfeed.tech/tags/language-en.md>), [pricing](<https://devfeed.tech/tags/pricing.md>), [software](<https://devfeed.tech/tags/software.md>), [software-providers](<https://devfeed.tech/tags/software-providers.md>), [storytype-feature](<https://devfeed.tech/tags/storytype-feature.md>), [technology-industry](<https://devfeed.tech/tags/technology-industry.md>)

## AI overview

AI pricing at established software firms is evolving around customer cost predictability and existing products, rather than shifting wholesale to pure usage billing. In a survey of 415 product and technology leaders, AI use in products rose from 80% to 96%, yet almost half reported limited or low adoption of their AI features. Only 7% reported AI-related seat losses, while nearly half saw downward pricing pressure. Common approaches include placing AI in a higher-priced subscription tier, including it at no extra charge, or combining subscriptions with usage or outcome pricing; firms expect predictability-oriented models to grow faster than pure usage pricing over the next 18 months. AI can raise revenue while delivery and cloud costs pressure margins. Many firms also lack clear usage data, making it harder to choose pricing metrics and assess feature value. The article describes a possible staged approach--from free inclusion to higher tiers with usage limits and, as usage becomes predictable, hybrid pricing--while emphasizing that products may move at different rates.

## Source excerpt

In 2026, the AI monetization conversation has shifted quickly from one concern to the next. Early in the year, fears that AI agents would erode software seats helped trigger a selloff of software stocks dubbed the "SaaSpocalypse." Since then, attention has turned to a different disruption, as AI leaders including Anthropic, OpenAI, and GitHub lean heavily on usage-based pricing to better align revenue with the cost of delivering AI. It would be easy to conclude that software monetization is shifting wholesale from seats and subscriptions to tokens, credits, and consumption. But look across a broader cross-section of the software industry, and a different picture emerges. Most software companies aren't AI-native businesses designing pricing from scratch. They have existing products, customers, contracts, and pricing structures. They're adding AI to portfolios that may already span dozens of products and multiple monetization models. And they have to balance the economics of AI with something customers still value enormously: predictability. That tension came through clearly in our new Revenera Monetization Monitor: Software and AI Pricing Models and Strategies 2027 report of 415 product and technology leaders at established software producers and intelligent device manufacturers. Nearly all are adding AI capabilities to at least some products. The way they're monetizing those capabilities, though, is considerably more pragmatic than the headlines might suggest. AI features are widespread, but adoption is lagging AI capabilities have gone mainstream. The share of software producers incorporating AI into their products jumped from 80% last year to 96% today. Getting AI into the product, however, is only the first step. The widespread use of chatbots can create the impression that everyone is using AI. That isn't yet true inside established software products. Almost half of respondents say that adoption of their AI features is limited or low. For many vendors, that make