Georgian, in Partnership with NewtonX, Unveils Inaugural 2024 AI, Applied Benchmarking Report

Report quantifies the impact of AI on growth-stage B2B companies sourced from 601 executives globally; highlights the 12% of companies seeing a 2x ROI in applied AI

Toronto, Canada, November 21, 2024 – Georgian, a growth-stage B2B investor helping companies scale faster via its AI Lab, today announced the findings of its inaugural AI, Applied benchmarking report. In partnership with research firm NewtonX, the report surveyed over 600 executives of growth-stage B2B software companies uncovering the state of AI in business today and how AI adoption affects business performance.

“Georgian is uniquely positioned to set industry benchmarks in AI, having evolved its 2008 Applied Analytics thesis to Applied AI in 2018—four years ahead of the ChatGPT launch,” said Leon Mishkis, COO at NewtonX. “What this new research shows is that the growth-stage companies leading in AI today—those achieving 2x ARR—aren’t necessarily the largest or best-resourced but are those taking a comprehensive, strategic approach. Georgian’s insights-led framework is a game-changer for those ready to shift from experimenting with AI to turning AI investments into tangible results.”

Insights from the AI, Applied benchmarking report, a summary of which can be downloaded here, include:

• Penetration: In just two years since ChatGPT launched, 81% of B2B Growth-stage companies are both building AI products and using AI in their operations
• Goals: Internal productivity gains is the #1 KPI (26%), highlighted across all functions. Competitive advantage ranks #2 (20%) driven by R&D teams. Revenue gains rank #3 (17%) driven by Go-to-Market teams. Surprisingly, cost savings is near the bottom (11%) and is prioritized by operational teams like IT, legal, finance, and HR.
• Top Use Cases in production for R&D leaders: Unlocking data & analytics insights is the number one use case (46%) out of 9 use cases analyzed. Cybersecurity (29%), tied for #3, is a logical reaction to the data & analytics finding.
• Production Status: Among those B2B companies committed to AI projects, 91% have at least one AI model in production, suggesting AI is progressing from pilot to production faster than previous technology evolutions. Across all models benchmarked, OpenAI has the most in production at 65%.
• Data Sources: First-party data and dark data make up approximately 58% of training data used in production.
• Barriers to Adoption: Costs (45%), unclear ROI (49%) and data security (60%) are among the top concerns or challenges for further deployment of AI. 
• ROI: While the deployment of applied AI is advancing quickly, only 12% of the B2B companies benchmarked are seeing up to a 2x increase in ARR. 

In 2023, Georgian released the Crawl, Walk, Run framework, which provides a comprehensive method for companies to gauge their progress toward achieving AI maturity and nativity. The 2024 AI, Applied benchmarking report found that companies that fall within the “run” category are excelling in a few key areas including: 

• Focus on building new products that link ROI to revenue. Runners (40%) more frequently build new product capabilities vs. Walkers (14%) and Crawlers (4%). Runners are far more likely (5x Walkers) to tie the ROI of their projects to revenue. 
• Allocate more team resources to AI. Runners have the same size team, but allocate a greater percentage of the team (35%) to AI vs. ~18% for others (Crawlers and Walkers). 
• Adopt AI more broadly & deeply. Runners have adopted AI more broadly across use cases than others (Crawlers and Walkers). While Runners are the most active users of sophisticated models, Crawlers are more likely to rely on simpler API calls. 

“Runners, who represent only 12% of the market, seem to show clear separation in AI ROI over the 49% walking,” said Ben Wilde, Head of Thesis and Innovation at Georgian. “Successful AI adoption appears to be marked by a unified effort among GTM and R&D teams, implementing AI broadly, not just in isolated projects, and being willing to engage in thoughtful experimentation rather than hesitant one-off projects. Companies committing to these areas are beginning to see improvements in ROI and marketing and sales metrics.”

Georgian is hosting a webinar on November 21 at 1:00 p.m. ET to explore these findings with companies looking to improve their AI maturity. Those interested in attending can register here. Additional virtual sessions, whitepapers, and live events will go deeper into the benchmarks over the next several months. For additional information on this report or Georgian, please visit https://georgian.io/

About Georgian

Georgian invests in high-growth B2B software companies and builds software to help those companies scale faster through our AI Lab. We seek to identify and accelerate leading growth-stage software companies in our thesis areas of Applied AI and Trust. Georgian’s AI Lab team works with portfolio companies to address
growth-stage product and go-to-market challenges. The AI Lab supports companies across the product development lifecycle through 1-1 engagements, the Transferred Learnings community and AI research. Based in Toronto, Georgian’s team brings together investors with machine learning professionals, software entrepreneurs and experienced operators. 

NewtonX Research Methodology

This study was conducted by Georgian in collaboration with NewtonX, a leading B2B research company. NewtonX employed a robust research methodology, involving 601 B2B executives, of which 27% were from the C-suite and 90% of which were key decision-makers. The study ensured a balanced perspective with equal representation from research and development (R&D) leaders and go-to-market (GTM) strategists. Participants were drawn from businesses with annual recurring revenues (ARR) ranging from ~$5 million to $200 million, with 84% of these companies experiencing annual growth of 5% or more.

This global study included respondents from ten countries and spanned across 15 different verticals, all primarily selling software. Conducted as a blind study through 15-minute online interviews collected between September 9th and October 1st, 2024, the research adhered to rigorous qualification and quality assurance processes. This approach aims to ensure the accuracy and reliability of the findings, providing a comprehensive overview of AI benchmarks within the B2B sector.

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