The generative AI market stands at 27.4 billion dollars with an expected 18 percent compound annual growth rate. Related segments such as virtual try-on and natural language processing show similar expansion that reaches design and construction tasks. Only 17 percent of organizations report using AI at scale.
Key Takeaways
- $27.4 billion generative AI market size in 2023 (market forecast)
- 18% CAGR forecast for generative AI market from 2024 to 2032 (market forecast)
- $12.0 billion global AI in retail market projected by 2032 (market forecast)
- 73% of organizations using AI report it creates value (survey finding)
- 1,500+ AI tools and vendors were identified for the retail and CPG sector in a 2024 industry scan (catalog figure)
- 66% of respondents in Adobe’s 2024 “State of Create” report said they feel generative AI will change how they create content.
- In the US, 18% of adults reported using AI chatbots in 2024 (survey finding)
- 17% of organizations say they are using AI at scale (survey finding)
- 26% of organizations report using generative AI for customer service (survey finding)
- 12% average reduction in marketing costs from AI adoption (survey finding)
- 10-25% reduction in energy usage with AI-based energy management (study finding range)
- 3-5% yield improvement using AI process control in semiconductor manufacturing (study finding)
- $1.6 million estimated annual savings from predictive maintenance deployment (case study)
- $1.0 billion estimated savings potential from AI automation in customer service (industry estimate)
- $600 billion potential value in software engineering from generative AI (McKinsey estimate)
Generative AI is rapidly scaling across industries, driving measurable value, savings, and massive market growth.
Related reading
01 · Category
Market Size12 stats
01
$27.4 billion generative AI market size in 2023 (market forecast)
02
18% CAGR forecast for generative AI market from 2024 to 2032 (market forecast)
03
$12.0 billion global AI in retail market projected by 2032 (market forecast)
04
$19.2 billion global AI in construction market projected by 2032 (market forecast)
05
$2.2 billion creative design software market size in 2023 (market forecast)
06
$61.6 billion global CAD software market projected by 2030 (market forecast)
07
$61.3 billion global 3D printing services market projected by 2032 (market forecast)
08
$16.6 billion global virtual try-on market projected by 2032 (market forecast)
09
$15.2 billion global computer vision market projected by 2027 (market report figure)
10
$39.3 billion global NLP market projected by 2027 (market report figure)
11
$34.9 billion global speech recognition market projected by 2028 (market report figure)
12
$267.0 billion global AI software market projected by 2030 (market report figure)
Interpretation
Market Size Interpretation
The market size signals strong, cross-segment momentum for AI in the craft industry, with generative AI reaching a $27.4 billion market in 2023 and projected to grow at an 18% CAGR through 2032 alongside large adjacent opportunities like AI in construction growing to $19.2 billion and AI in retail to $12.0 billion by 2032.
02 · Category
Industry Trends4 stats
01
73% of organizations using AI report it creates value (survey finding)
02
1,500+ AI tools and vendors were identified for the retail and CPG sector in a 2024 industry scan (catalog figure)
03
66% of respondents in Adobe’s 2024 “State of Create” report said they feel generative AI will change how they create content.
04
72% of respondents in Adobe’s 2024 “State of Create” report said they expect to use generative AI at least as much as they do today over the next 12 months.
Interpretation
Industry Trends Interpretation
Under industry trends, the data suggests AI is quickly becoming a mainstream lever in creative and retail workflows, with 73% of organizations reporting AI creates value and a rapidly expanding vendor landscape of 1,500+ tools, while 66% and 72% of Adobe’s 2024 “State of Create” respondents say generative AI will change how they create and that they expect to use it at least as much going forward.
03 · Category
User Adoption5 stats
01
In the US, 18% of adults reported using AI chatbots in 2024 (survey finding)
02
17% of organizations say they are using AI at scale (survey finding)
03
26% of organizations report using generative AI for customer service (survey finding)
04
22% of manufacturing firms report using AI for predictive maintenance (survey finding)
05
43% of marketing professionals say they have used AI in some way in 2024 (survey finding)
Interpretation
User Adoption Interpretation
User adoption in the craft industry is still emerging but gaining momentum, with 18% of US adults using AI chatbots in 2024 and 17% of organizations already using AI at scale, while nearly 43% of marketing professionals report having used AI in some way that year.
04 · Category
Performance Metrics7 stats
01
12% average reduction in marketing costs from AI adoption (survey finding)
02
10-25% reduction in energy usage with AI-based energy management (study finding range)
03
3-5% yield improvement using AI process control in semiconductor manufacturing (study finding)
04
15-20% improvement in OEE from AI-enabled maintenance and control in industrial operations (study finding range)
05
10-30% reduction in rework costs with computer-aided quality inspection using AI (study finding range)
06
In a 2023 arXiv study on AI-based damage detection for building inspection, the authors reported an F1 score of 0.84 using their model on their test set (task-specific metric).
07
In a 2022 peer-reviewed study in Construction and Building Materials, an AI-based crack detection model achieved a mean average precision (mAP) of 0.79 on crack detection benchmarks.
Interpretation
Performance Metrics Interpretation
Across performance metrics in the craft industry, AI adoption is consistently delivering measurable gains, with reported cost reductions of about 12% in marketing and 10 to 30% cuts in rework costs while also improving efficiency through 15 to 20% higher OEE and 3 to 5% better semiconductor yields.
More related reading
05 · Category
Cost Analysis6 stats
01
$1.6 million estimated annual savings from predictive maintenance deployment (case study)
02
$1.0 billion estimated savings potential from AI automation in customer service (industry estimate)
03
$600 billion potential value in software engineering from generative AI (McKinsey estimate)
04
$50 billion savings from AI in customer service and support (industry estimate)
05
3.5% reduction in project costs with AI-driven schedule and risk analytics (study finding)
06
25% lower cost per unit produced with automated quality inspection using AI (study finding range)
Interpretation
Cost Analysis Interpretation
Across cost analysis in the craft industry, AI is poised to cut expenses at scale, with estimates like $1.6 million in annual savings from predictive maintenance and broader industry figures such as $50 billion in customer service savings, alongside measurable study results showing 3.5% lower project costs and 25% lower cost per unit through AI inspection.
06 · Category
Market Dynamics1 stats
01
In 2023, USPTO received 65,000 AI-related patent applications (applications citing at least one AI technology category under USPTO’s AI initiatives taxonomy).
Interpretation
Market Dynamics Interpretation
In 2023, USPTO received 65,000 AI related patent applications, signaling strong market momentum for AI technologies within the craft industry as innovators actively seek legal protection for adoption and differentiation.
07 · Category
Risk & Compliance3 stats
01
The EU AI Act sets an obligation for certain AI systems to comply with transparency requirements, including providing information to users that they are interacting with an AI system, effective for many provisions starting 2024.
02
The U.S. Copyright Office reported in its 2023 guidance that works created with generative AI without sufficient human authorship are not eligible for copyright protection, affecting registration outcomes.
03
NIST’s AI Risk Management Framework (AI RMF 1.0) emphasizes governance and risk controls; NIST categorizes AI risks into four functions: Govern, Map, Measure, and Manage.
Interpretation
Risk & Compliance Interpretation
Across EU and US guidance plus NIST’s AI RMF 1.0, risk and compliance for AI is tightening around transparency and governance, with the EU AI Act requiring user-facing information and the U.S. Copyright Office signaling that generative AI content without sufficient human authorship may not qualify, while NIST organizes AI risks into four core governance and control functions.
report visual · Key figures
Generative AI is expanding rapidly—and craft-related markets are projected to grow too
Market forecasts point to strong growth for generative AI, with compounding momentum alongside expansion across adjacent craft-industry segments.
$27.4 billion
$27.4 billion generative AI market size in 2023 (market forecast)
18%
18% CAGR forecast for generative AI market from 2024 to 2032 (market forecast)
$12.0 billion
$12.0 billion global AI in retail market projected by 2032 (market forecast)
$19.2 billion
$19.2 billion global AI in construction market projected by 2032 (market forecast)
$2.2 billion
$2.2 billion creative design software market size in 2023 (market forecast)
$61.6 billion
$61.6 billion global CAD software market projected by 2030 (market forecast)
source-verifiedfortunebusinessinsights.com · precedenceresearch.com · globenewswire.com · grandviewresearch.com2032
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). AI In The Craft Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-craft-industry-statistics
MLA
Kevin O'Brien. "AI In The Craft Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-craft-industry-statistics.
Chicago
Kevin O'Brien. 2026. "AI In The Craft Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-craft-industry-statistics.
Sources & references
38 datasets cited across this report · attribution is report-level
+17 additional datasets cited (not shown individually)