HubSpot Research Finds a Gap Between AI Use and Results

Nearly all marketing teams use artificial intelligence in some form, but relatively few say it has transformed their results, according to HubSpot’s 2026 State of AI in Marketing research. The research puts AI use among marketing teams at 98%, while 10% report transformational results.

HubSpot frames the difference as a question of AI maturity: how consistently a customer-facing team converts AI use into measurable business outcomes. For marketers, that shifts the focus from the number of tools in use or experiments launched to whether AI contributes to outcomes such as revenue and customer experience.

The company identifies four maturity levels: Early, Emerging, Established and Transformational. It groups the latter two as advanced use. In the research, 42% of marketers reported advanced AI use, compared with 27% of people in sales and 23% in service. Those figures describe reported maturity levels across functions, rather than the share reporting transformational results alone.

HubSpot’s definition emphasizes repeatable work rather than isolated pilots. A marketing team may run several experiments, for example, without reaching a higher maturity level if the work is not connected to its customer relationship management system, does not have an owner or lacks a comparison showing results before and after implementation.

More mature use, as described by HubSpot, incorporates AI into documented workflows and draws on clean customer data. It also retains human oversight and connects activity to measures such as marketing-qualified leads, customer acquisition cost and revenue. The same broad definition applies to sales and service, although their workflows and performance measures differ.

HubSpot’s guide recommends assessing a team’s current position before deciding how to progress. It also discusses data readiness, responsible AI governance and measurement across the funnel. The distinction is between adopting AI and building a consistent process for showing what that adoption contributes to the business.

What this means for marketers

Teams assessing their AI work can start by looking beyond the number of pilots. Documenting workflows, assigning ownership and comparing outcomes before and after implementation can help establish whether existing AI activity is producing measurable marketing results.