These reports are derived from Superintelligent's proprietary AI use case dataset, built from thousands of structured enterprise interviews and insights from The AI Daily Brief, the leading podcast for enterprise AI leaders. Each report distills real-world adoption data into actionable intelligence for AI planning and execution.
The most comprehensive study of AI ROI to date. We analyzed 5,124 use cases from 1,245 practitioners in Q4 2025. These use cases were key in identifying trends in the AI space including:
4 in 5 AI users report positive ROI with 95% predicting positive ROI in the next 12 months. Only 0.2% believe ROI will decrease.
Orgs that only focus on efficiency gains see overall lower ROI, while those who take a portfolio approach (use cases that provide 2-4 measurable benefits) see a 16% increase.
Only 14% of organizations report using specific tools to solve specific problems. The vast majority rely on popular LLMs for basic time saving.
Superintelligent integrates these use cases into its client analysis, enabling pattern-matched recommendations with specific tools to support each identified opportunity.
Based on our AI Readiness Audits with over 1,000 executives, this report uncovers the real blockers, enablers, and patterns that determine AI success. Here are the four distinct organizational archetypes we typically encounter:
Vision-rich, plumbing-poor. Strong executive intent and modern SaaS systems, but weak data infrastructure and fragmentation issues.
Regulated or conservative industry. Prioritizes governance, risk management, and security above experimentation. Has formal AI policies but struggles to move quickly.
Broad support for AI experimentation, but no central strategy. Employees use GPTs and copilots, but without roadmap, upskilling, or coordination.
Deliberate infrastructure-first approach. Strong central IT/data team focused on consolidating data, establishing AI gateways, and building enterprise agent platforms.
Usage metrics tell you nothing about value. Our framework, developed by our head of research and based off of 1,000's of executive level interviews, provides a systematic approach to measuring and proving AI ROI beyond vanity metrics. In other words, if login counts and message volumes don't prove value, what does?
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