As artificial intelligence (AI) becoming increasingly embedded across both R&D and GTM workflows, integration is varying significantly by the growth stage of the company..
That was one of the top findings from Georgian Partners and NewtonX’s 2025 AI Adoption Enterprise & Growth-Stage Benchmarks Report. The report part of Georgian’s AI, Applied Benchmark Research, which surveyed 600+ executives globally across 10 countries and 15 industry verticals.
Enterprise respondents report deploying AI across a broader range of R&D and GTM functions, with an average lead of 10 percentage points in in-production usage compared to their growth-stage peers. This gap is especially pronounced in areas such as customer support and cybersecurity, where 57% of enterprise respondents lead compared to 39% of growth-stage respondents.
AI Has Arrived
David Berkowitz, Founder, AI Marketers Guild (AIMG) who is one of the partners with Georgian Partners in creating global benchmarks of B2B AI adoption, said the report underscores the reality that AI is no longer a future concept for enterprises.
“It’s here, and the winners will be those who apply it with clarity, accountability, and measurable impact,” said Berkowitz in a statement. “Our members see firsthand that enterprise AI success depends as much on governance, skills, and cultural readiness as it does on technology. Applied AI is a business imperative.”
Growth-Stage Focus
For growth-stage companies, they are concentrating their investments in the adoption of advanced AI techniques and large language models (LLMs), signaling that focused efforts can deliver comparable technical sophistication.
In growth-stage companies, both R&D and GTM respondents report higher gains across business (ARR, LTV, and sales & marketing efficiency). Additionally, growth-stage R&D respondents report a more positive impact from AI on engineering metrics (code quality, commit frequency) despite lower deployment, suggesting leaner teams may realize more value, faster than enterprise peers.
The data shows AI maturity isn’t just about scale, according to GTM Partners CEO Sangram Vajre.
“Growth-stage companies, with fewer resources, are often realizing bigger and faster gains because they deploy AI with laser focus on impact,” said Vajre. “Enterprises may win on breadth, but agility is proving to be the real accelerator.”
Inside the Numbers
Among the other key findings in the report:
Enterprise firms favor advanced models, which come with a greater need for cost control as 58% of enterprise R&D teams use custom-trained or fine-tuned models (vs. 39% growth-stage) and are more likely to adopt cost management strategies like simplification.
GTM AI adoption is broader in Enterprise—except in content. Enterprise GTM respondents lead AI use in lead scoring and customer retention while growth-stage companies top use case were in marketing messaging and content.
Integration, risk, and responsibility concerns. Across both R&D and GTM functions, enterprise respondents are more likely to cite integration with existing systems (top-ranked by GTM teams), data security and privacy, regulatory compliance and ethical use as key barriers.
Report Overview
The overview of the report is that enterprise companies are leveraging AI more broadly across key operational functions than growth-stage firms, with a particular focus on customer success—where chatbots are already prevalent—and on cybersecurity to address emerging AI-driven threats.
“In contrast, growth-stage companies tend to be more risk-averse, concentrating their AI deployments on targeted go-to-market initiatives, including product features that maximize ROI and drive topline growth,” said James Lamberti, Head of Go-to-Market at Georgian.