According to a new report by Menlo Ventures, business spending on generative Al experienced a massive 500% increase this year, soaring from $2.3 billion in 2023 to $13.8 billion.
The report highlights a notable shift in enterprise Al’s market dynamics. Menlo projects this figure will nearly double to $297.9 billion by 2027, driven by a compound annual growth rate of 19.1%.
The report further reveals that OpenAl’s market share dropped from 50% to 34%, while Anthropic’s share doubled, rising from 12% to 24%. These findings are based on a survey of 600 enterprise IT decision-makers from companies with at least 50 employees.
Tekedia Mini-MBA edition 16 (Feb 10 – May 3, 2025) opens registrations; register today for early bird discounts.
Tekedia AI in Business Masterclass opens registrations here.
Join Tekedia Capital Syndicate and invest in Africa’s finest startups here.
Tim Tully, a partner at Menlo Ventures, explained that enterprises increasingly adopt multiple large Al models tailored to specific use cases. “Developers are pretty savvy they know how to go back and forth between models fairly quickly,” Tully said, adding that this flexibility has likely bolstered Claude 3.5 popularity.
Meta maintained a 16% market share, while Cohere held steady at 3%. Google experienced growth rising from 7% to 12%, whereas Mistral saw a slight decline from 6% to 5%. Foundation models, including OpenAl’s ChatGPT, Google’s Gemini, and Anthropic’s Claude, accounted for $6.5 billion of enterprise Al investment.
The report also highlights the growing investment in Al agents, a technology poised to surpass traditional chatbots. Companies like Google, Microsoft, Amazon, OpenAl, and Anthropic are betting on Al agents, which can perform multistep tasks, create autonomous workflows, and operate with minimal user input.
Code generation emerged as the leading use case for generative Al. Other common applications included support chatbots (31%), enterprise search and retrieval, data extraction and transformation, and meeting summarization.
The rapid acceleration of business spending on generative Al underscores a pivotal shift in enterprise priorities, with companies racing to integrate advanced Al tools to stay competitive. Presently, the global Artificial Intelligence market stands at nearly $235 billion, with projections indicating a rise to over $631 billion by 2028. The three leading industries in terms of Artificial Intelligence spending are Software and Information Services, Banking, and Retail. Combined, these sectors are projected to allocate approximately $89.6 billion towards Al in 2024, representing 38% of the global Al market.
Notably, Generative Al accounts for more than 19% of the total investment across these three industries, highlighting its growing significance in the Al landscape. With a spending of $33 billion in 2024, companies are using Al to make the software development lifecycle more efficient and error-resistant through Al lifecycle software and predictive models. Enhancing information services by personalizing content delivery based on user data, thus improving user engagement. Artificial Intelligence is also driving innovation by creating new products and tools for data analysis and market trend prediction, helping businesses stay competitive.
Additionally, Al is augmenting and automating operational processes, increasing efficiency, and reducing costs by allowing functions such as human resources to focus on strategic tasks. This comprehensive integration of Al is not only streamlining operations but also fostering the development of high-quality, adaptive software and services.
The Banking industry, a market with approximately $31.3 billion in investments in Al in 2024, is using the technology to enable banks to offer personalized customer experiences through machine learning and data analytics, allowing banks to tailor services to individual preferences. As generative Al continues to evolve, the data underscores its growing importance in enterprise ecosystems and signals significant competition among providers to meet diverse business needs.