Nearly half of all professional services firms already use AI. This article details the adoption rates, performance gains, and market forecasts shaping its implementation across the sector.
Key Takeaways
- 4.9 million workers in the U.S. used AI tools at work in 2024 (as reported by a U.S. government survey of computer/AI tool use).
- In 2023, 31% of enterprises used machine learning for customer insights (Gartner survey findings reported in Gartner press materials).
- AI adoption is highest in professional services: 49% of firms in that sector reported using AI in 2023 (European Commission Digital Economy and Society statistics summarized in EC report).
- 29% of IT organizations reported AI usage for IT operations/automation in 2023 (Gartner Insights survey, summarized in Gartner research brief).
- 90% of customer service operations are projected to use generative AI by 2028 (Gartner forecast).
- 40% of enterprises will use AI for security operations by 2025 (Gartner forecast on AI in security operations).
- The worldwide AI software market is forecast to grow at a 20.8% CAGR from 2024–2028 (IDC).
- The AI services market is forecast to reach $1.0T by 2030 (IDC long-term forecast).
- The contact center AI market is projected to grow from $6.7B in 2024 to $18.9B by 2030 (MarketsandMarkets forecast).
- Organizations using AI reported paying an average 12% higher cloud infrastructure cost attributable to AI workloads (AWS/industry benchmark cited in AWS Well-Architected AI workloads whitepaper).
- A 2024 IDC case study reports up to 30% reduction in cloud spend after optimizing AI workloads with autoscaling and right-sizing (IDC optimization case study).
- 62% of service professionals say AI helps improve customer service quality (Salesforce State of Service 2024).
- 48% of organizations reported improved first-contact resolution with AI (ServiceNow State of Service 2024).
- 64% of organizations say AI is enabling faster turnaround times for customer requests — from an operations and service performance benchmark report (2024)
- The EU estimates that AI adoption can increase labor productivity by 0.8% to 1.4% annually for adopters in the services sector — from an EU policy and impact assessment report
AI adoption is accelerating in services, boosting productivity, customer service, and security while driving major market growth.
Related reading
01 · Category
User Adoption7 stats
01
4.9 million workers in the U.S. used AI tools at work in 2024 (as reported by a U.S. government survey of computer/AI tool use).
02
In 2023, 31% of enterprises used machine learning for customer insights (Gartner survey findings reported in Gartner press materials).
03
AI adoption is highest in professional services: 49% of firms in that sector reported using AI in 2023 (European Commission Digital Economy and Society statistics summarized in EC report).
04
In the EU, 17% of enterprises used AI for customer interactions in 2023 (Eurostat enterprise AI module).
05
53% of customer service organizations report that they use AI-enabled customer interaction tools — from a 2024 customer service benchmark survey
06
63% of contact-center leaders report plans to adopt generative AI for customer service within the next 12–24 months — from a 2024 contact center technology survey
07
AI adoption in professional services is concentrated in internal knowledge management and automation, with 41% of surveyed firms reporting AI use in knowledge/workflow copilots — from a 2024 professional services technology survey
Interpretation
User Adoption Interpretation
User adoption of AI in services is accelerating, with 4.9 million US workers using AI tools in 2024 and adoption reaching 49% of professional services firms in 2023 while 63% of contact center leaders plan to adopt generative AI for customer service in the next 12 to 24 months.
02 · Category
Industry Trends7 stats
01
29% of IT organizations reported AI usage for IT operations/automation in 2023 (Gartner Insights survey, summarized in Gartner research brief).
02
90% of customer service operations are projected to use generative AI by 2028 (Gartner forecast).
03
40% of enterprises will use AI for security operations by 2025 (Gartner forecast on AI in security operations).
04
By 2030, cost reductions from AI are expected to drive $1.3T in productivity gains across industries (OECD estimate).
05
By 2025, 35% of organizations expect AI to be embedded in customer service journeys (Gartner forecast).
06
The U.S. Bureau of Labor Statistics reports that the number of AI and ML specialists employed was about 258,000 in 2023 (BLS occupational employment series for related occupations).
07
The BLS projects 23% employment growth for computer and information research scientists from 2022 to 2032 (strong link to AI research labor demand).
Interpretation
Industry Trends Interpretation
For Industry Trends in the services sector, the data points to rapid AI adoption that by 2028 is expected to touch 90% of customer service operations with generative AI, while AI security use is projected to reach 40% of enterprises by 2025.
03 · Category
Market Size8 stats
01
The worldwide AI software market is forecast to grow at a 20.8% CAGR from 2024–2028 (IDC).
02
The AI services market is forecast to reach $1.0T by 2030 (IDC long-term forecast).
03
The contact center AI market is projected to grow from $6.7B in 2024 to $18.9B by 2030 (MarketsandMarkets forecast).
04
The generative AI market is projected to grow to $1.3T by 2032 (MarketsandMarkets forecast).
05
The AI in fintech market is projected to grow to $304.7B by 2033 (Precedence Research estimate).
06
The AI cybersecurity market is forecast to reach $152.4B by 2032 (Fortune Business Insights).
07
The speech analytics market is expected to reach $15.2B in 2030 (MarketsandMarkets forecast).
08
AI value at stake for the services sector is estimated at $9.4T by 2030 (PwC AI analysis).
Interpretation
Market Size Interpretation
Across the services sector, AI market sizing is accelerating fast, with projections showing the AI software market growing at a 20.8% CAGR from 2024 to 2028 and the broader AI services market reaching $1.0T by 2030.
More related reading
04 · Category
Cost Analysis2 stats
01
Organizations using AI reported paying an average 12% higher cloud infrastructure cost attributable to AI workloads (AWS/industry benchmark cited in AWS Well-Architected AI workloads whitepaper).
02
A 2024 IDC case study reports up to 30% reduction in cloud spend after optimizing AI workloads with autoscaling and right-sizing (IDC optimization case study).
Interpretation
Cost Analysis Interpretation
For cost analysis in the services industry, using AI can raise cloud infrastructure costs by an average of 12% due to AI workloads, but targeted measures like autoscaling and right sizing can cut cloud spend by as much as 30%, showing that AI cost impact is highly controllable.
05 · Category
Performance Metrics6 stats
01
62% of service professionals say AI helps improve customer service quality (Salesforce State of Service 2024).
02
48% of organizations reported improved first-contact resolution with AI (ServiceNow State of Service 2024).
03
64% of organizations say AI is enabling faster turnaround times for customer requests — from an operations and service performance benchmark report (2024)
04
In a large-scale field study, organizations using machine learning-based fraud detection reported a median fraud loss reduction of 30% — from an academic evaluation of ML fraud detection systems
05
Retail and services firms report that AI personalization improves conversion rates by 10% on average — from a peer-reviewed marketing analytics study (2022)
06
In service-sector healthcare operations, AI-assisted administrative coding reduces claim processing errors by 27% — from a 2020–2021 healthcare AI evaluation study
Interpretation
Performance Metrics Interpretation
Across performance metrics, AI is showing measurable service impact, with results like 64% of organizations reporting faster customer request turnaround times and 48% seeing improved first-contact resolution.
06 · Category
Labor & Skills1 stats
01
The EU estimates that AI adoption can increase labor productivity by 0.8% to 1.4% annually for adopters in the services sector — from an EU policy and impact assessment report
Interpretation
Labor & Skills Interpretation
In the Labor and Skills lens, the EU’s estimate suggests that when services firms adopt AI they can raise labor productivity by about 0.8% to 1.4% each year, underscoring how AI is translating into measurable workforce gains.
report visual · Key figures
AI adoption & momentum in services (customer service, professional services, and adoption plans)
AI usage in services spans current adoption and forward-looking intent, with especially strong presence in professional services and customer interaction use cases.
49%
AI adoption is highest in professional services: 49% of firms in that sector reported using AI in 2023 (European Commiss
17%
In the EU, 17% of enterprises used AI for customer interactions in 2023 (Eurostat enterprise AI module).
53%
53% of customer service organizations report that they use AI-enabled customer interaction tools — from a 2024 customer
63%
63% of contact-center leaders report plans to adopt generative AI for customer service within the next 12–24 months — fr
90%
90% of customer service operations are projected to use generative AI by 2028 (Gartner forecast).
source-verifieddigital-strategy.ec.europa.eu · ec.europa.eu · mckinsey.com · frost.com · gartner.com2028
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
Leah Kessler. (2026, February 13). AI In The Services Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-services-industry-statistics
MLA
Leah Kessler. "AI In The Services Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-services-industry-statistics.
Chicago
Leah Kessler. 2026. "AI In The Services Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-services-industry-statistics.
Sources & references
31 datasets cited across this report · attribution is report-level
+11 additional datasets cited (not shown individually)