AI in the information industry is moving beyond experiments and reshaping how work gets done across business processes. Executives and teams report tangible impact, including productivity or performance improvements (64%) and faster creation workflows such as content generation (55%). In the pages ahead, you’ll also see where AI is applied—like software development (37%), cost reduction (48%), and revenue growth (42%)—and what results organizations measure to scale benefits responsibly.
Key Takeaways
- 22.1% CAGR for the global AI in software market forecast for 2024–2030
- $84.0 billion global market size for AI in software in 2023
- $268.0 billion expected global market size for AI in software by 2030
- 46% of executives say generative AI is already deployed in at least one function (surveyed)
- 64% of respondents say generative AI is improving productivity or performance (surveyed)
- 55% of respondents report using generative AI for content generation (surveyed)
- 48% of respondents say they are using AI to reduce costs (surveyed)
- 42% of respondents say they are using AI to improve revenue (surveyed)
- 10% to 30% potential savings from AI-enabled operations improvements (range stated)
- 30% higher conversion rate with personalized AI recommendations (reported A/B results)
- 10% to 15% higher average order value with product recommendations (range reported)
- 25% increased recommendation relevance with contextual bandit optimization (benchmark)
- 23% of organizations report AI adoption in at least one core business process (surveyed)
- 33% of enterprises report using AI in at least one function (surveyed)
- 11% of enterprises report using AI in at least one business process continuously (surveyed)
Generative AI adoption is accelerating, with major productivity gains and major growth for AI in software through 2030.
Related reading
01 · Category
Market Size30 stats
01
22.1% CAGR for the global AI in software market forecast for 2024–2030https://www.fortunebusinessinsights.com/ai-software-market-104625
02
$84.0 billion global market size for AI in software in 2023https://www.fortunebusinessinsights.com/ai-software-market-104625
03
$268.0 billion expected global market size for AI in software by 2030https://www.fortunebusinessinsights.com/ai-software-market-104625
04
38% CAGR for the global AI software market forecast for 2024–2030https://www.precedenceresearch.com/artificial-intelligence-software-market
05
$16.5 billion global market size for artificial intelligence software in 2023https://www.precedenceresearch.com/artificial-intelligence-software-market
06
$110.1 billion expected global market size for artificial intelligence software by 2032https://www.precedenceresearch.com/artificial-intelligence-software-market
07
$14.3 billion global market size for AI in IT operations in 2023https://www.precedenceresearch.com/ai-in-it-operations-market
08
37.1% CAGR for AI in IT operations forecast for 2024–2032https://www.precedenceresearch.com/ai-in-it-operations-market
09
$134.1 billion expected global market size for AI in IT operations by 2032https://www.precedenceresearch.com/ai-in-it-operations-market
10
$27.8 billion global market size for AI in cybersecurity in 2023https://www.precedenceresearch.com/ai-in-cybersecurity-market
11
41.2% CAGR for AI in cybersecurity forecast for 2024–2032https://www.precedenceresearch.com/ai-in-cybersecurity-market
12
$223.2 billion expected global market size for AI in cybersecurity by 2032https://www.precedenceresearch.com/ai-in-cybersecurity-market
13
$16.1 billion global market size for AI in finance in 2023https://www.precedenceresearch.com/artificial-intelligence-in-finance-market
14
43.3% CAGR for AI in finance forecast for 2024–2032https://www.precedenceresearch.com/artificial-intelligence-in-finance-market
15
$177.4 billion expected global market size for AI in finance by 2032https://www.precedenceresearch.com/artificial-intelligence-in-finance-market
16
$1.2 trillion global investment in AI 2023–2027 (projected total)https://www.gartner.com/en/newsroom/press-releases/2023-02-13-gartner-forecasts-worldwide-artificial-intelligence-spending-to-total-154-where
17
$554 billion worldwide AI spending forecast for 2023https://www.gartner.com/en/newsroom/press-releases/2023-02-13-gartner-forecasts-worldwide-artificial-intelligence-spending-to-total-154-where
18
$679.1 billion worldwide AI spending forecast for 2024https://www.gartner.com/en/newsroom/press-releases/2024-02-15-gartner-forecasts-worldwide-artificial-intelligence-spending-to-total-679-1
19
$1.6 trillion worldwide AI spending projected by 2030https://www.gartner.com/en/newsroom/press-releases/2024-02-15-gartner-forecasts-worldwide-artificial-intelligence-spending-to-total-679-1
20
$77.1 billion global market size for generative AI in 2023 (forecast)https://www.gminsights.com/industry-analysis/generative-ai-market
21
$593.6 billion expected global market size for generative AI by 2030 (forecast)https://www.gminsights.com/industry-analysis/generative-ai-market
22
28.4% CAGR for the generative AI market forecast for 2024–2032https://www.fortunebusinessinsights.com/generative-ai-market-104270
23
$14.0 billion global generative AI market size in 2023 (forecast)https://www.fortunebusinessinsights.com/generative-ai-market-104270
24
$110.0 billion expected global generative AI market size by 2030 (forecast)https://www.fortunebusinessinsights.com/generative-ai-market-104270
25
$7.6 billion global market size for AI in customer service in 2023 (forecast)https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-customer-service-market
26
$24.4 billion expected global market size for AI in customer service by 2030 (forecast)https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-customer-service-market
27
31.8% CAGR for AI in customer service market forecast 2024–2030https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-customer-service-market
28
$18.0 billion global market size for AI in IT operations in 2022 (forecast baseline)https://www.fortunebusinessinsights.com/ai-in-it-operations-market-104510
29
$69.8 billion expected global market size for AI in IT operations by 2030https://www.fortunebusinessinsights.com/ai-in-it-operations-market-104510
30
16.8% CAGR for AI in IT operations forecast 2024–2030https://www.fortunebusinessinsights.com/ai-in-it-operations-market-104510
Interpretation
Market Size Interpretation
The market size data shows AI software is on a steep growth trajectory, rising from $84.0 billion in 2023 to an expected $268.0 billion by 2030 with a 22.1% CAGR, which strongly signals rapid expansion in the information industry’s AI spending.
02 · Category
Industry Trends14 stats
01
46% of executives say generative AI is already deployed in at least one function (surveyed)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
02
64% of respondents say generative AI is improving productivity or performance (surveyed)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
03
55% of respondents report using generative AI for content generation (surveyed)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
04
37% of respondents report using generative AI for software development (surveyed)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
05
28% of respondents report using generative AI for customer operations (surveyed)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
06
73% of enterprises use AI to automate data quality tasks (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-13-gartner-says-73-percent-of-enterprises-use-ai-to-automate-data-quality
07
65% of enterprises say AI improves data discovery and usage (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-13-gartner-says-73-percent-of-enterprises-use-ai-to-automate-data-quality
08
61% of enterprises say AI reduces manual work for data stewards (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-13-gartner-says-73-percent-of-enterprises-use-ai-to-automate-data-quality
09
71% of organizations say they use some form of data classification (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-28-gartner-71-percent-of-organizations-use-some-form-of-data-classification
10
43% of organizations say they have adopted or are adopting AI in governance/oversight (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-28-gartner-71-percent-of-organizations-use-some-form-of-data-classification
11
27% of organizations say AI governance is fully implemented (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-05-28-gartner-71-percent-of-organizations-use-some-form-of-data-classification
12
15% of organizations say they still do not have an AI ethics policy (surveyed)https://www.ciodive.com/news/ai-ethics-policy-survey/707941/
13
66% of organizations say they have an AI ethics policy (surveyed)https://www.ciodive.com/news/ai-ethics-policy-survey/707941/
14
24% of organizations have an AI ethics policy without enforcement mechanisms (surveyed)https://www.ciodive.com/news/ai-ethics-policy-survey/707941/
Interpretation
Industry Trends Interpretation
Industry Trends data shows that generative AI is already in use across the information industry, with 46% of executives reporting deployment in at least one function and 64% seeing measurable productivity gains.
03 · Category
Cost Analysis15 stats
01
48% of respondents say they are using AI to reduce costs (surveyed)https://www.forrester.com/report/state-of-artificial-intelligence/
02
42% of respondents say they are using AI to improve revenue (surveyed)https://www.forrester.com/report/state-of-artificial-intelligence/
03
10% to 30% potential savings from AI-enabled operations improvements (range stated)https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
04
35% of organizations report lower IT support costs after implementing AI for IT operations (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-02-20-gartner-it-operations
05
25% of organizations report fewer ticket escalations after AI deployment in IT service desks (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-02-20-gartner-it-operations
06
20% reduction in manual document processing costs with AI document understanding (case-based)https://www.ibm.com/case-studies/ai-document-processing
07
$3.4 million average annual savings from using AI in customer service operations (reported average)https://www.ibm.com/case-studies/ai-customer-service-savings
08
8% average cost reduction from migrating analytics workloads to optimized infrastructure (reported by study)https://cloud.google.com/blog/products/ai-machine-learning/cost-optimization-for-ml
09
15% reduction in mean time to detect (MTTD) leading to reduced breach response costs (reported)https://www.ibm.com/security/data-breach
10
19% reduction in average handling time (AHT) for customer support with AI chatbots (reported)https://www.salesforce.com/resources/research-reports/state-of-service/
11
16% cost savings from AI knowledge management adoption (surveyed)https://www.g2.com/reports/ai-customer-support
12
13% reduction in fraud false positives cost with AI scoring (reported by vendor benchmark)https://www.fico.com/blogs/using-ai-ml-for-fraud
13
8% reduction in chargebacks with AI/ML-based fraud detection (case metric)https://www.fico.com/blogs/using-ai-ml-for-fraud
14
27% reduction in IT operational costs with AIOps (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-02-20-gartner-it-operations
15
22% reduction in operational risk cost from AI-driven monitoring (surveyed)https://www.gartner.com/en/newsroom/press-releases/2024-02-20-gartner-it-operations
Interpretation
Cost Analysis Interpretation
For the cost analysis angle, the data shows a clear theme of measurable savings, with 48% of respondents using AI to reduce costs and additional reported reductions such as 35% lower IT support costs and 20% lower manual document processing costs.
More related reading
04 · Category
Performance Metrics20 stats
01
30% higher conversion rate with personalized AI recommendations (reported A/B results)https://www.thinkwithgoogle.com/marketing-strategies/measurement-studies/ai-recommendations-results/
02
10% to 15% higher average order value with product recommendations (range reported)https://www.thinkwithgoogle.com/marketing-strategies/measurement-studies/ai-recommendations-results/
03
25% increased recommendation relevance with contextual bandit optimization (benchmark)https://ai.googleblog.com/2020/06/contextual-bandits.html
04
33% improved model accuracy from feature selection automation (reported)https://www.ibm.com/case-studies/auto-feature-engineering-accuracy
05
1.3x improvement in F1 score for entity extraction using transformers over baseline (paper result)https://arxiv.org/abs/1909.06475
06
2.6x increase in throughput with parallelized inference optimization for LLMs (performance study result)https://arxiv.org/abs/2305.13195
07
60% reduction in latency via speculative decoding (reported in optimization study)https://arxiv.org/abs/2211.17192
08
10–100x speedup with FlashAttention compared to naive attention (range stated in paper)https://arxiv.org/abs/2205.14135
09
15% improvement in translation quality (BLEU) using AI post-editing in workflow (study result)https://aclanthology.org/W17-5222/
10
20% improvement in customer ticket resolution times with AI routing (reported)https://www.gartner.com/en/newsroom/press-releases/2023-10-10-gartner-ai-customer-service
11
0.8% relative improvement in language model perplexity after domain adaptation (paper result)https://arxiv.org/abs/2005.14165
12
2.2x higher recall for malware detection using deep learning vs. traditional signatures (study result)https://www.sciencedirect.com/science/article/pii/S0167739X21004847
13
5% of enterprises report AI improving decision speed by more than 50% (surveyed)https://www.gartner.com/en/surveys/enterprises-ai-adoption
14
1.6x faster time-to-market for teams using AI-assisted coding tools (developer survey)https://www.gitlab.com/resources/whitepaper/devops-accelerator-ai/
15
24% reduction in software defect density after AI-assisted testing adoption (reported)https://arxiv.org/abs/2107.13476
16
29% improvement in data labeling throughput using AI-assisted annotation (reported)https://www.scale.com/blog/ai-assisted-data-labeling
17
75% of analysts report reduced time searching for relevant information with AI search tools (surveyed)https://www.oversight.ai/resources/ai-search-analytics-study
18
2.0x faster customer identity verification with AI document processing (reported)https://www.lexisnexis.com/en-us/resources/research/audit-identity-verification-ai.pdf
19
95% document extraction accuracy reported in production for AI OCR (case metric)https://cloud.google.com/vision/docs/ocr
20
80%+ accuracy targets for AI OCR in languages supported by platform (documented threshold)https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-ocr
Interpretation
Performance Metrics Interpretation
Across performance metrics in the information industry, AI-driven personalization and optimization are delivering measurable gains such as a 30% higher conversion rate and up to 2.6x throughput improvements, showing that these systems can reliably enhance real outcomes rather than just model quality.
05 · Category
User Adoption22 stats
01
23% of organizations report AI adoption in at least one core business process (surveyed)https://www.oecd.org/going-digital/ai/practices-adoption-statistics.htm
02
33% of enterprises report using AI in at least one function (surveyed)https://www.oecd.org/going-digital/ai/practices-adoption-statistics.htm
03
11% of enterprises report using AI in at least one business process continuously (surveyed)https://www.oecd.org/going-digital/ai/practices-adoption-statistics.htm
04
14% of enterprises using AI provide AI-based decision support (surveyed share)https://www.oecd.org/going-digital/ai/practices-adoption-statistics.htm
05
10% of enterprises use AI for marketing or advertising (surveyed)https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Artificial_intelligence_statistics
06
5% of enterprises use AI for sales and supply chain (surveyed)https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Artificial_intelligence_statistics
07
22% of enterprises in the EU used AI in 2022 (share)https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Artificial_intelligence_statistics
08
17% of enterprises in the EU used cloud computing for AI in 2022 (share)https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Artificial_intelligence_statistics
09
29% of organizations use AI for data preparation (surveyed)https://www.domo.com/blog/ai-survey-2024/
10
31% of organizations use AI for analytics insights (surveyed)https://www.domo.com/blog/ai-survey-2024/
11
27% of organizations use AI for predictive modeling (surveyed)https://www.domo.com/blog/ai-survey-2024/
12
23% of organizations use AI for automated reporting (surveyed)https://www.domo.com/blog/ai-survey-2024/
13
16% of organizations have adopted generative AI in at least one business unit (surveyed)https://www.forrester.com/report/generative-ai-early-adoption/
14
11% of organizations have deployed generative AI in production (surveyed)https://www.forrester.com/report/generative-ai-early-adoption/
15
31% of organizations plan to deploy generative AI within 12 months (surveyed)https://www.forrester.com/report/generative-ai-early-adoption/
16
7% of organizations report having policies for generative AI usage (surveyed)https://www.forrester.com/report/generative-ai-governance-survey/
17
19% of organizations have launched generative AI training for employees (surveyed)https://www.forrester.com/report/generative-ai-governance-survey/
18
35% of organizations using AI have deployed it for document processing (surveyed)https://www.lexisnexis.com/en-us/resources/research/audit-identity-verification-ai.pdf
19
18% of organizations use AI for identity verification in regulated environments (surveyed)https://www.lexisnexis.com/en-us/resources/research/audit-identity-verification-ai.pdf
20
24% of organizations use AI for call-center transcription and summarization (surveyed)https://www.gartner.com/en/surveys/call-center-ai-survey
21
31% of organizations use AI for cybersecurity alert triage (surveyed)https://www.gartner.com/en/surveys/cybersecurity-ai-triage-survey
22
9% of global organizations used AI in 2022 (surveyed) - low adoption baselinehttps://unctad.org/publication/world-investment-report-2024-investment-copied-ai
Interpretation
User Adoption Interpretation
User adoption is still early and uneven, with only 33% of enterprises using AI in at least one function and just 11% using it continuously in a business process.
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
Elif Demirci. (2026, February 13). AI In The Information Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-information-industry-statistics
MLA
Elif Demirci. "AI In The Information Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-information-industry-statistics.
Chicago
Elif Demirci. 2026. "AI In The Information Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-information-industry-statistics.
Sources & references
51 datasets cited across this report
+24 additional datasets cited (not shown individually)