Global AI software spending is forecast to reach $80.5 billion in 2025. At the same time, 53% of firms report they cannot properly measure the return on their AI investments. These figures reveal a critical gap between rapid market growth and the maturity of enterprise AI programs.
Key Takeaways
- 1.6x the market size growth forecast for generative AI software from 2024–2028 (worldwide) compared with the prior 2023–2027 period
- 55% worldwide spend growth on generative AI software in 2024
- $78.9 billion worldwide spending on AI software is forecast for 2024
- 72% of organizations expect to use generative AI in at least one business unit within 12 months
- 58% of organizations report using AI for automation of processes
- 38% of AI adopters report using AI for customer service
- 15% lower cost per decision after implementing AI decisioning systems (case study meta-results)
- 45% of respondents reported data acquisition costs are a major AI budget line item (survey finding)
- 53% of firms say they struggle to quantify the ROI of AI (survey estimate)
- 15%–25% improvement in operational efficiency from AI-enabled automation (McKinsey estimate range)
- 2.5x faster inference latency after model optimization (quantization/pruning) in a benchmark report
- 10–20% accuracy lift achievable with hyperparameter tuning and data cleaning (industry benchmark range)
- 60% of AI projects require external expertise to deliver outcomes (survey finding)
- 70% of companies use AI-related tools but only 10% report AI scale (survey finding)
- 68% of data scientists and ML engineers report that production deployment is a key challenge (survey finding)
Generative AI and AI consulting are accelerating fast, with major global spending growth and enterprises racing to deploy.
Related reading
01 · Category
Market Size19 stats
01
1.6x the market size growth forecast for generative AI software from 2024–2028 (worldwide) compared with the prior 2023–2027 period[1]
02
55% worldwide spend growth on generative AI software in 2024[1]
03
$78.9 billion worldwide spending on AI software is forecast for 2024[1]
04
$80.5 billion worldwide spending on AI software is forecast for 2025[1]
05
$202 billion worldwide AI market revenue forecast for 2025[1]
06
$1.3 trillion projected global AI market value by 2032 (McKinsey Global Institute estimate for AI economic impact)[2]
07
$16.8 billion global spending on AI consulting and implementation services forecast for 2024[3]
08
$19.2 billion global spending on AI consulting and implementation services forecast for 2025[3]
09
$7.6 billion AI in healthcare consulting services market size in 2023[4]
10
$10.8 billion AI in healthcare consulting services market size forecast for 2030[4]
11
AI software and services represent a rapidly growing share of enterprise IT spend; in 2024, AI accounted for 8% of total analytics spend in survey estimates[5]
12
4.3% of global venture funding in 2022 went to AI (PitchBook-reported share summarized in public report)[6]
13
$19.1 billion global venture capital invested in AI companies in 2022 (PitchBook-reported figure)[6]
14
$37.8 billion global venture capital invested in AI companies in 2023 (PitchBook-reported figure)[6]
15
$10.2 billion US market size for AI professional services in 2023 (estimate from published market research)[7]
16
$15.6 billion US market size for AI professional services in 2031 (estimate from published market research)[7]
17
33.5% CAGR projected for AI consulting services market over 2024–2032 (estimate from published market research)[7]
18
$8.2 billion global AI consulting services market size in 2023 (estimate from published market research)[7]
19
$33.4 billion global AI consulting services market size forecast for 2032 (estimate from published market research)[7]
Interpretation
Market Size Interpretation
With global AI consulting and implementation services rising from $16.8 billion in 2024 to $19.2 billion in 2025 while generative AI software spend is forecast to grow 55% worldwide in 2024, the data points to accelerating enterprise demand for AI expertise and deployments at the same time the overall AI economy expands toward $1.3 trillion by 2032.
02 · Category
User Adoption10 stats
01
72% of organizations expect to use generative AI in at least one business unit within 12 months[8]
02
58% of organizations report using AI for automation of processes[9]
03
38% of AI adopters report using AI for customer service[10]
04
46% of enterprises report using cloud-based AI services[3]
05
43% of respondents say they used AI to automate software testing[1]
06
23% of organizations have an enterprise AI ethics policy[11]
07
20% of respondents reported using AI for legal/compliance work[12]
08
24% of organizations reported no current AI deployment but planning within 12 months (survey finding)[13]
09
54% of enterprises state their AI systems are monitored for drift and performance (survey finding)[14]
10
19% of organizations said they use AI for personalized healthcare treatment recommendations (survey finding)[15]
Interpretation
User Adoption Interpretation
With 72% of organizations expecting to use generative AI in at least one business unit within 12 months, the momentum is clear, even as adoption spans automation at 58% and customer-facing use at 38% while only 23% have an enterprise AI ethics policy.
03 · Category
Cost Analysis3 stats
Interpretation
Cost Analysis Interpretation
Across the industry, while AI decisioning can cut cost per decision by 15%, 45% of firms report data acquisition as a major budget line and 53% still struggle to quantify AI ROI.
More related reading
04 · Category
Performance Metrics8 stats
01
15%–25% improvement in operational efficiency from AI-enabled automation (McKinsey estimate range)[2]
02
2.5x faster inference latency after model optimization (quantization/pruning) in a benchmark report[17]
03
10–20% accuracy lift achievable with hyperparameter tuning and data cleaning (industry benchmark range)[14]
04
25% increase in customer satisfaction after deploying AI-driven customer service assistants (case findings)[1]
05
12% reduction in churn after implementing personalization models (industry survey finding)[18]
06
19% improvement in supply chain forecast accuracy after using machine learning (study result)[19]
07
28% improvement in maintenance prediction accuracy with AI-based condition monitoring (study result)[20]
08
33% reduction in incident response time using AI-driven threat detection (study result)[21]
Interpretation
Performance Metrics Interpretation
Across the board, AI adoption is driving measurable gains, with improvements ranging from a 12% churn reduction from personalization to a 33% faster incident response from threat detection.
05 · Category
Industry Trends8 stats
01
60% of AI projects require external expertise to deliver outcomes (survey finding)[8]
02
70% of companies use AI-related tools but only 10% report AI scale (survey finding)[5]
03
68% of data scientists and ML engineers report that production deployment is a key challenge (survey finding)[22]
04
23% of respondents said they are concerned about AI-related security risks (survey finding)[1]
05
17% of AI consulting engagements are in healthcare (survey estimate in industry report)[23]
06
24% of AI consulting engagements are in finance/banking (survey estimate in industry report)[23]
07
21% of AI consulting engagements are in retail/e-commerce (survey estimate in industry report)[23]
08
18% of AI consulting engagements are in manufacturing (survey estimate in industry report)[23]
Interpretation
Industry Trends Interpretation
Despite 70% of companies using AI tools, only 10% report scaling success, showing that the hardest gap is moving models into production where 68% of ML engineers say deployment is the key challenge.
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
Henrik Dahl. (2026, February 13). AI Consulting Industry Statistics. Gitnux. https://gitnux.org/ai-consulting-industry-statistics
MLA
Henrik Dahl. "AI Consulting Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-consulting-industry-statistics.
Chicago
Henrik Dahl. 2026. "AI Consulting Industry Statistics." Gitnux. https://gitnux.org/ai-consulting-industry-statistics.
Sources & references
23 sources cited across this report
gartner.com
mckinsey.com
statista.com
precedenceresearch.com
forrester.com
pitchbook.com
alliedmarketresearch.com
ibm.com
semanticscholar.org
salesforce.com
oecd.org
legaltechhub.com
idc.com
mlflow.org
jamanetwork.com
domo.com
research.google
epsilon.com
sciencedirect.com
ieeexplore.ieee.org
ncbi.nlm.nih.gov
survey.stackoverflow.co
fortunebusinessinsights.com