HubSpot beat Wall Street's revenue and earnings expectations in the second quarter, with revenue rising 17.5% in constant currency, although guidance pointed to slower customer growth and longer buying cycles, with net customer additions of around 7,000, well below market expectations. AI adoption, credit consumption and autonomous resolution rates featured prominently alongside those headline figures.

This balance is indicative of a wider pattern across enterprise software this earnings season as AI usage is increasingly presented as a predictor of future growth rather than another product capability. The financial results still matter, but the AI metrics may be the more revealing part of the earnings story.

HubSpot chief executive Yamini Rangan told analysts that changes made in April, including free trials for AI agents and a shift towards outcome-based pricing with lower entry points, were designed to let customers "prove value before buying." This philosophy helps explain why HubSpot is reporting AI metrics so prominently. Customers increasingly expect evidence that AI delivers measurable value before committing to wider deployment.

While traditional CRM software generated fairly predictable subscription revenue through per-seat licences, AI is beginning to complicate that model. HubSpot's commentary pointed to AI credit purchases, consumption-based pricing, autonomous work completed and pricing linked more closely to AI usage and customer value as new revenue levers, alongside licence fees rather than instead of them.

The shift is gradual, but it seems that as AI takes on more customer-facing work, vendors are increasingly required to demonstrate measurable value before customers are willing to pay for it.

The emphasis on AI adoption continued throughout the discussion of business performance. The company said its Customer Agent now resolves 72% of support tickets without human escalation, up from 65% earlier in the year. Data Agent customers rose 80% quarter-on-quarter to 16,000, Prospecting Agent customers grew 28% to 17,000, and deals over $120,000 in annual recurring revenue jumped 38% year-on-year.

What stands out is not simply that HubSpot's AI products are attracting customers. Resolution rates, credit consumption and agent adoption are now routinely appearing alongside revenue and customer counts, in the same way SaaS companies once highlighted seat growth. HubSpot is not the only company highlighting these kinds of measures. Microsoft's recent results told a similar story, pointing to rising AI adoption across its commercial business as evidence that years of investment are starting to pay off. The same pattern was evident at 8x8, which recently reported that enterprise AI usage more than doubled year on year as customers moved AI into production, reinforcing the wider move from experimentation towards enterprise-wide deployment.

HubSpot's latest earnings matter not simply because the company beat expectations, but because they offer another indication that AI adoption is becoming a business metric in its own right alongside revenue and customer growth. The growing emphasis on resolution rates, AI usage and operational outcomes reinforces the importance of measuring AI performance through meaningful business KPIs. Whether this proves to be a lasting change in how enterprise software companies communicate performance, or simply reflects the current prominence of AI, will become clearer over future earnings reports.