ARR in the AI Era

Annual Recurring Revenue has long been the North Star for SaaS valuation and financial discipline. Yet as business models evolve with usage based pricing, consumption billing, managed services, and AI powered products, many companies treat ARR loosely, and in some cases incorrectly. Ben Murray’s presentation at the Usage Economy Summit 2025 offered a detailed and practical roadmap for restoring rigor to ARR while adapting it to the realities of modern software and AI monetization.

ARR Is Not Broken. Revenue Models Are Evolving. 

Ben’s central argument is straightforward. ARR remains one of the strongest indicators of predictable value creation, but companies often undermine their own numbers through poor revenue categorization. He emphasizes that metrics are not failing. It is the business models that have become more complex.

Subscription, usage, consumption, processing, overages, and recurring managed services now sit side by side. Without proper segmentation, a CFO cannot understand gross margins, retention behavior, or the true quality of recurring revenue. Ben stresses that the modern tech P&L must clearly separate revenue streams and map COGS to each stream with precision. Only then can leadership understand profitability dynamics and defend their numbers during valuation or due diligence.

What Public Companies Reveal About ARR Construction

To understand current practices, Ben reviewed 167 SEC filings and 92 global press releases. Patterns emerged that are increasingly important for private companies preparing for future rounds or acquisition.

Pure subscription ARR remains the cleanest model. Many companies continue to calculate ARR as MRR multiplied by twelve or last quarter’s revenue multiplied by four. Hybrid models, such as subscription plus usage, are becoming more common. Companies often annualize usage revenue by taking the last ninety days or the last thirty days of usage and extending it to a twelve month run rate.

A growing number include recurring managed services in ARR. While Ben considers this a debatable move, he notes that many CFOs choose to include it if the services are contracted and recurring. Pure usage companies, however, rarely attempt to transform usage revenue directly into ARR due to volatility and limited predictability.

The takeaway is clear. If revenue streams are not separated and ARR is not constructed with care, companies risk misleading themselves and their investors.

ARR Quality, Margin Visibility, and Business Model Discipline

Ben encourages leadership teams to ask hard questions about the nature of their recurring revenue. Is the revenue IP powered or people powered? Does scale require significant human effort? How do margins differ across streams?

With the rise of AI, these distinctions matter more than ever. Serving AI products can carry significant variable costs, particularly when relying on third party LLMs. Gross margin analysis must be tied to the structure of each revenue category, or the company will not know whether it is scaling profitably.

AI Monetization: What Public Tech Leaders Are Actually Doing

Investors have moved past AI hype. They now look for evidence of revenue contribution, adoption, and measurable outcomes. Wall Street’s questions consistently focus on five areas: AI revenue, adoption rates, usage tied to value, margin impact, and product readiness for monetization.

Murray showcases several strategies that leading enterprises are using to turn AI from a buzzword into a revenue engine.

• Charging price uplifts for AI features and driving higher ACV
• Moving to metered work units instead of token consumption
• Demonstrating outcomes such as reduced call abandonment or faster wrap times
• Creating new security categories around AI risk
• Defending data moats by embedding AI into established networks and systems
• Bundling AI within existing product families to bypass lengthy procurement cycles

These examples illustrate that AI monetization is no longer theoretical. It is measurable, traceable, and increasingly tied to concrete operational improvements. 

Reporting AI ARR and Proving Real Traction

Some public companies now report AI ARR separately, especially when it grows faster than total ARR. This transparency gives investors confidence that AI initiatives are contributing to retention, expansion, and new logo acquisition. Ben notes that companies able to demonstrate AI driven expansion or pipeline acceleration are receiving stronger market recognition.

For private companies, this signals a shift. Boards and prospective investors will soon expect similar clarity.

Outcome Based Pricing: Slow but Emerging

Despite frequent debate, outcome based pricing is still early. Only one public company explicitly described moving from seat based to outcome based pricing in its filings. Ben advises teams to be realistic. Unless outcomes can be quantified and trusted, outcome based pricing will remain limited and selective.

What Finance Leaders Must Do Next

Ben closes with a disciplined framework for ARR in the AI era. CFOs and CEOs must:

• Define revenue streams clearly and publish an internal ARR policy
• Track margins by revenue stream to understand scale and sustainability
• Monetize AI with purpose through uplift pricing, work unit billing, or embedded SKUs
• Measure adoption and usage to prove real customer value
• Track AI contributions to pipeline velocity, ACV, retention, and expansion
• Prepare for deeper due diligence as investors scrutinize ARR quality and AI economics

Final Thoughts

Ben’s presentation is a reminder that the fundamentals of finance still matter. ARR remains a powerful signal of value, but only when constructed with integrity and supported by a clean revenue architecture. AI presents an opportunity for meaningful growth, provided companies can measure and monetize it with discipline.

For teams preparing for their next stage of scale, the message is simple. Bring clarity to revenue, prove real adoption, and show how AI drives measurable impact. The companies that do this well will earn investor confidence and expand their valuation advantage in the years ahead.