By 2025, the global GenAI market is forecast to reach $15.7 billion, even as organizations wrestle with governance, deployment, and ROI measurement. At the same time, cloud continues to expand fast, with IDC projecting a 15.7% CAGR for public cloud services from 2023 to 2026. Extrapolate brings these signals into one place so you can see where adoption accelerates and where it stumbles.
Key Takeaways
- $27.6 billion global public cloud services market size in 2023 per IDC (includes IaaS and PaaS)
- $91.3 billion global public cloud services market size forecast for 2023-2026 CAGR 15.7% per IDC (2024 press release context)
- $1.7 billion expected annual spend on generative AI software in 2023 in the United States per IDC
- 2.9 billion people worldwide use mobile social media (2024), per DataReportal
- 45% of organizations using AI report having implemented it in customer-facing contexts (2023 global survey)
- 55% of enterprises use endpoint protection products (Gartner endpoint security adoption statistics reported in press)
- In 2023, 45% of organizations reported using cloud for analytics/AI (Gartner press release)
- GPT-3 had 175 billion parameters (as stated in the GPT-3 paper)
- 55% of AI projects in 2024 are being deployed using MLOps/AI governance frameworks (Gartner survey summary)
- 3x improvement in developer productivity with AI-assisted coding tools reported in a 2023 peer-reviewed study (reported effect size)
- 17% average improvement in code generation quality measured by pass@k in a study of LLM code assistants (2023)
- 99.99% uptime is targeted by major cloud providers; AWS Service Health reports 99.99% availability for core services in 2023 (AWS documentation aggregate)
- 43% of companies say they spend on security tools but do not measure ROI adequately (industry survey)
Cloud and AI adoption is accelerating fast, with booming markets, higher productivity, and growing governance needs.
Related reading
01 · Category
Market Size5 stats
01
$27.6 billion global public cloud services market size in 2023 per IDC (includes IaaS and PaaS)
02
$91.3 billion global public cloud services market size forecast for 2023-2026 CAGR 15.7% per IDC (2024 press release context)
03
$1.7 billion expected annual spend on generative AI software in 2023 in the United States per IDC
04
$15.7 billion global GenAI market size forecast for 2025 per MarketsandMarkets (report page with figure)
05
In 2024, 57% of UK adults said they are interested in using AI, up from 50% in 2023 per Ofcom
Interpretation
Market Size Interpretation
The market is expanding fast beyond just traditional cloud because IDC pegs the global public cloud market at $27.6 billion in 2023 with a 15.7% CAGR to $91.3 billion by 2026 while GenAI spend is also scaling from $1.7 billion annually in the US in 2023 to $15.7 billion globally by 2025, and UK interest in AI reached 57% in 2024.
02 · Category
User Adoption4 stats
01
2.9 billion people worldwide use mobile social media (2024), per DataReportal
02
45% of organizations using AI report having implemented it in customer-facing contexts (2023 global survey)
03
55% of enterprises use endpoint protection products (Gartner endpoint security adoption statistics reported in press)
04
42% of enterprises are using identity governance tools (IGA) in 2024 (Gartner survey summary)
Interpretation
User Adoption Interpretation
User Adoption is accelerating as billions are already consuming mobile social media and enterprise security and AI are moving into the mainstream, with 42% using identity governance tools, 55% relying on endpoint protection, and 45% of AI-using organizations deploying it in customer-facing contexts.
03 · Category
Industry Trends9 stats
01
In 2023, 45% of organizations reported using cloud for analytics/AI (Gartner press release)
02
GPT-3 had 175 billion parameters (as stated in the GPT-3 paper)
03
55% of AI projects in 2024 are being deployed using MLOps/AI governance frameworks (Gartner survey summary)
04
As of 2024, 70% of enterprises have adopted some form of data catalog or metadata management (Gartner survey summary)
05
In 2024, 53% of organizations planned to increase spending on AI governance/compliance (survey result)
06
In 2024, 39% of organizations reported migrating from monolithic architectures to microservices (industry survey)
07
The GPT-4 technical report describes a 1.8M-token context window capability (as stated in the report)
08
RoBERTa-large uses 355M parameters (as reported in the RoBERTa paper)
09
BERT-base uses 110M parameters (as reported in the BERT paper)
Interpretation
Industry Trends Interpretation
Industry Trends show that organizations are rapidly scaling responsible AI and data management, with 55% of AI projects in 2024 using MLOps or AI governance frameworks alongside 70% of enterprises adopting data catalogs or metadata management.
More related reading
04 · Category
Performance Metrics3 stats
01
3x improvement in developer productivity with AI-assisted coding tools reported in a 2023 peer-reviewed study (reported effect size)
02
17% average improvement in code generation quality measured by pass@k in a study of LLM code assistants (2023)
03
99.99% uptime is targeted by major cloud providers; AWS Service Health reports 99.99% availability for core services in 2023 (AWS documentation aggregate)
Interpretation
Performance Metrics Interpretation
From the Performance Metrics perspective, recent evidence shows Extrapolate-style AI tooling can boost developer productivity by 3x and raise LLM code generation quality by 17% while also aligning with the 99.99% uptime availability expectations of major cloud providers.
05 · Category
Cost Analysis1 stats
01
43% of companies say they spend on security tools but do not measure ROI adequately (industry survey)
Interpretation
Cost Analysis Interpretation
For cost analysis, 43% of companies spend on security tools but fail to measure ROI adequately, suggesting many security budgets may be less efficient than they appear.
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Kevin O'Brien. (2026, February 13). Extrapolate Statistics. Gitnux. https://gitnux.org/extrapolate-statistics
MLA
Kevin O'Brien. "Extrapolate Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/extrapolate-statistics.
Chicago
Kevin O'Brien. 2026. "Extrapolate Statistics." Gitnux. https://gitnux.org/extrapolate-statistics.
Sources & references
22 datasets cited across this report · attribution is report-level
aws.amazon.com+13 additional datasets cited (not shown individually)