TLDR: Georgian has released its ‘AI, Applied Benchmarks Report,’ conducted with NewtonX, detailing the state of AI adoption among over 600 B2B growth-stage and enterprise executives. The report highlights AI as a top strategic priority for 83% of respondents, with internal productivity being the primary driver. It also uncovers distinct adoption patterns and challenges, such as linking AI investments to revenue growth and overcoming scaling hurdles.
Toronto, Canada – Georgian, a prominent growth-stage B2B investor, has unveiled the findings of its comprehensive ‘AI, Applied Benchmarks Report,’ developed in collaboration with NewtonX. The report offers an in-depth analysis of AI maturity across more than 600 growth-stage B2B and enterprise executives, providing critical benchmarks for companies aiming to lead in AI-driven innovation. The study equally represents research and development (R&D) and go-to-market (GTM) leaders, examining AI’s profound impact on productivity, costs, and revenue growth.
The report underscores the rapid transition of AI from an emerging trend to a core strategic imperative, with a striking 83% of respondents now identifying AI as a top five strategic priority. AI-related initiatives account for three of the top four corporate priorities when ranked by executives. Internal productivity gains emerged as the number one motivator for AI strategy, selected in the top three motivators by all nine functional areas surveyed.
However, the report also reveals significant differences in AI deployment strategies between enterprise and growth-stage companies. James Lamberti, Head of Go-to-Market at Georgian, noted, ‘Enterprise respondents leverage AI more broadly across key operational functions than growth-stage respondents, 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 designed to maximize ROI and drive top-line growth.
Despite the widespread adoption and strategic importance, challenges persist. The report indicates a hurdle in progressing from intermediate to advanced stages of AI maturity, suggesting difficulties in effectively scaling and operationalizing AI initiatives. While AI is viewed as promising for cost savings and efficiency, definitively linking AI investments to revenue growth and comprehensive ROI remains a significant challenge. Only 25% of R&D respondents currently tie the ROI of their AI product initiatives directly to revenue, though this figure has risen by 5 percentage points since 2024. Over half (51%) of R&D respondents acknowledge they are not yet linking their AI efforts to concrete Key Performance Indicators (KPIs). Security and privacy concerns are also identified as potential contributors to lower AI maturity rates.
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The ‘AI, Applied Benchmarks Report’ serves as a vital resource for businesses navigating the complexities of AI integration, offering insights into current adoption trends, motivations, and the critical areas requiring further development to fully harness the transformative power of artificial intelligence.
