Source Research:
Key Trends and Forecasts
Methodology
The generative AI software & services market valuation is built using a top-down methodology and validated using a bottom-up methodology, alongside industry interviews.
Top-Down Methodology: Assess enterprise vertical total market revenue, Information and Communication Technology (ICT) spending percentage, and estimated adoption of generative AI across different frameworks.
Bottom-Up Methodology: Using an assessment of vertical adoption of generative AI software and services to estimate the price of software/services (based on yearly subscription to leading AI platforms, e.g., H20AI, DataIKU, DataRobot, Ikigai) and the average size of companies using platforms.
Each enterprise vertical has been assessed separately to understand the scope and timeline for generative AI adoption.
Each enterprise vertical has been assessed based on various factors: new technology adoption rate, current generative AI adoption and use cases, available use cases across AI frameworks, growth of Information Technology (IT) spending, internal talent, and partnership with IT/AI leaders.
Generative AI software/services are split out by understanding how different verticals will deploy solutions in-house versus utilizing third-party services. This estimate is based on an assessment of various factors: AI talent, time to market considerations, data security/sovereignty considerations, and case studies.
Definitions
ABI Research defines Generative AI as Deep Learning (DL) models that can generate text, images, and other content based on training data and prompts