AI Is Driving A Shift Towards Outcome-Based Pricing

By Ivan Makarov , James da Costa and Bobby Pinero

Pricing shifts are not new to the software industry. When SaaS first came to prominence, we saw a seismic shift to seat-based pricing, something that was completely foreign in an on-prem world. AI is now driving the beginning of yet another and possibly more dramatic pricing shift. Software companies of all sizes, and founders of new AI companies in particular, are currently thinking through three key shifts where AI is challenging them to think differently about pricing:

• Software is becoming labor. AI is turning what used to be pure service businesses into scalable software plays. Traditional services that required human labor — like customer support, sales, marketing, or back-office finance administration — can now be automated and packaged as software products. This has blurred the line between software and service pricing models.
• Per-seat is no longer the atomic unit of software. Consider customer support software Zendesk: companies currently pay per support agent ($115/month/seat), but when AI can handle ticket resolution, the natural pricing metric becomes successful outcomes. If AI can handle a sizable proportion of customer support, companies will need far fewer human support agents, and therefore fewer Zendesk software seats. This forces software companies to fundamentally rethink their pricing models to align with the outcome they deliver rather than the number of humans that access their software.
• Variable costs are less predictable. Nearly every AI startup builds on foundation models (e.g., OpenAI, Anthropic, Mistral) which come with significant variable costs that scale with AI model usage. Every API call, every token processed, adds to their cost structure. This is a fundamental change in the underlying unit economics of pricing the AI service. The marginal cost of an additional user or usage is not zero and varies by user. And while inference costs are dropping dramatically, tasks requiring the newest models with advanced reasoning capabilities still incur relatively high costs. AI companies are leaning into usage-based pricing to account for this.

There is no one-size-fits-all solution for pricing nor for responding to these shifts. However, we are beginning to see a number of archetypes emerge in the AI space, with a notable difference between those who are AI-native companies (e.g., Decagon, Cursor, ElevenLabs) and those who have added AI on top of existing core products (e.g., Zendesk, Notion, Canva). AI-native companies have leaned towards newer pricing models: usage (pay for what you consume), outcome (pay for what was delivered), or hybrid models (a combination). Decagon, for instance, offers per-conversation (usage-based) and per-resolution (outcome-based) pricing, while Cursor is seat-based with usage-based charges for premium models. Existing companies, meanwhile, have mostly stuck with per-seat or bundled options.

Ultimately, this is a rapidly evolving space because of all the innovation and unit economics pressure. We will likely see even more new pricing and GTM approaches emerge. Experimenting with different approaches to pricing your AI product or add-on is something to consider as you seek pricing-market fit.

More from a16z

How AI is Transforming Labor Markets

In this episode of the a16z Podcast, General Partners Alex Rampell, David Haber, and Angela Strange discuss how AI is revolutionizing labor by automating tasks traditionally done by humans. They’ll trace the evolution of cloud eras — from the original to financial services-enabled to the current AI-enabled outcomes era — showcasing how AI is creating unprecedented opportunities, allowing startups to outpace incumbents.

Base AI Policy on Evidence, not Existential Angst

In this op-ed for Fortune, a16z General Partner Martin Casado advocates for policymakers to focus on evidence-based policy in the new year and apply our regulatory energy there. It’s a simple approach that has already been proposed by a number of the top AI academics in the industry. And it’s worth understanding.

Can AI Agents Finally Fix Customer Support?

In this episode of the AI + a16z podcast, Decagon cofounder and CEO Jesse Zhang, and a16z partner Kimberly Tan, discuss how LLMs are reshaping customer support, the strong market demand for AI agents, and how AI agents give startups a a new pricing model to help disrupt incumbents.

Death of a Salesforce: Why AI Will Transform the Next Generation of Sales Tech

In this conversation, a16z Partners Marc Andrusko and Joe Schmidt discuss how the sales landscape is undergoing a major transformation, moving from structured CRM data to unstructured, contextual insights powered by AI. The winners will be those who leverage data and AI to drive decisions, not just activities.

Say Hello to My New AI Marketer: How Gen AI-Based Software Is Advancing Marketing and Sales

In this conversation, a16z Partner Seema Amble and a16z Podcast Host Steph Smith discuss the changing role of marketing in a $500 billion industry. In particular, they highlight how generative AI tools are reshaping everything from content creation to data-driven insights. 

How Zapier Became Profitable in Three Years and Scaled to $5 Billion with Wade Foster

a16z Partner Seema Amble connects with Zapier co-founder Wade Foster about the company’s founding and GTM success utilizing a product-led growth (PLG) strategy. Chock-full of actionable insights, this episode explores Zapier’s product strategy, customer experience, and how the team built a sustainable growth engine that enabled them to reach profitability within three years.

Building Developers Tools, From Docker to Diffusion Models

In this episode of the AI + a16z podcast, Replicate cofounder and CEO Ben Firshman, and a16z partner Matt Bornstein, discuss the art of building products and companies that appeal to software developers. Ben was the creator of Docker Compose, and Replicate has a thriving community of developers hosting and fine-tuning their own models to power AI-based applications.

AI Voice Interviewers

In this tweetstorm, a16z Partners Olivia Moore and Seema Amble note that your next job interview may be with an AI. That’s because companies spend a ton of time and money on interviews, often with low ROI, and candidates suffer through long and painful processes. Enter AI voice interviewers.

Recent Investments

Investing in Stainless

Stainless is revolutionizing API development and SDK generation for the AI era, via its unique approach to handling custom code and API best practices.

Investing in WaveForms AI

WaveForms AI is training an end-to-end audio language model with the goal of solving the speech Turing test — an AI that feels like talking to a human.

Investing in Resend

Resend is transforming how businesses communicate with their customers, and setting new standards for the developer experience around email sending.

Connect with a16z

• Interested in receiving this newsletter on a monthly basis? Subscribe here.
• Want more insights from a16z? Subscribe to our suite of newsletters here.

Disclosures

You are receiving this newsletter since you opted in earlier; if you would like to opt out of future newsletters, you can unsubscribe immediately.

This newsletter is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. This newsletter may link to other websites and certain information contained herein has been obtained from third-party sources. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation.

References to any companies, securities, or digital assets are for illustrative purposes only and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund which should be read in their entirety.) Past performance is not indicative of future results.

Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Content in this newsletter speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see disclosures for additional important information.