Global revenue for generative AI software stands at 8.0 billion dollars with projections reaching 107.5 billion dollars. Companies using AI for customer service achieve average cost savings of 30 percent. Only 45 percent of customer service organizations currently deploy chatbots.
Key Takeaways
- $8.0 billion is projected global revenue for generative AI software in 2024 (and $107.5 billion by 2030)
- Global generative AI services spending is forecast to total $62.5 billion in 2024
- Worldwide AI software revenue is projected to reach $188 billion in 2023 (with continued growth forecast)
- Companies that use AI in customer service report average cost savings of 30% (compared with baseline operations)
- Chatbots can reduce customer support costs by 30% to 70% (range reported by industry research)
- In a large-scale observational study, automated customer support handling led to 9% lower cost per ticket compared with manual routing (study reported by a research summary)
- Recommendation engines can increase revenue by 10%+ (reported typical uplift in industry case studies)
- A/B tests in leading retail contexts frequently show 5%–20% lift in conversion using product recommendations
- 1.6x average increase in average order value when using product recommendations in e-commerce personalization campaigns (benchmark from industry research)
- 56% of consumers said they prefer a chatbot that can answer basic questions instantly (2022 survey result)
- 45% of customer service organizations reported using chatbots in 2023 (survey finding)
- In 2024, 61% of consumers used mobile devices to shop online at least weekly (survey result, 2024)
AI agents are driving major e-commerce impact with big market growth, faster support, and higher conversions.
Related reading
01 · Category
Market Size7 stats
01
$8.0 billion is projected global revenue for generative AI software in 2024 (and $107.5 billion by 2030)
02
Global generative AI services spending is forecast to total $62.5 billion in 2024
03
Worldwide AI software revenue is projected to reach $188 billion in 2023 (with continued growth forecast)
04
$26.6 billion is the estimated global market size for conversational AI in 2023
05
$3.1 billion is the global market size for chatbots in 2024
06
$6.6 billion global intelligent virtual assistant market size in 2024 is projected to reach $18.9 billion by 2030
07
$23.6 billion global recommendation engine market size in 2023 is projected to reach $75.2 billion by 2030
Interpretation
Market Size Interpretation
In the Market Size view, the AI agents ecommerce ecosystem is already large and accelerating, with generative AI software revenue projected to grow from $8.0 billion in 2024 to $107.5 billion by 2030 alongside major adjacent markets like conversational AI at $26.6 billion in 2023 and recommendation engines rising from $23.6 billion in 2023 to $75.2 billion by 2030.
02 · Category
Cost Analysis3 stats
01
Companies that use AI in customer service report average cost savings of 30% (compared with baseline operations)
02
Chatbots can reduce customer support costs by 30% to 70% (range reported by industry research)
03
In a large-scale observational study, automated customer support handling led to 9% lower cost per ticket compared with manual routing (study reported by a research summary)
Interpretation
Cost Analysis Interpretation
From a cost analysis perspective, AI-driven customer support is consistently cutting expenses, with savings averaging 30% and chatbots reporting 30% to 70% lower support costs, while an observational study found automated handling reduced cost per ticket by 9% versus manual routing.
More related reading
03 · Category
Performance Metrics8 stats
01
Recommendation engines can increase revenue by 10%+ (reported typical uplift in industry case studies)
02
A/B tests in leading retail contexts frequently show 5%–20% lift in conversion using product recommendations
03
1.6x average increase in average order value when using product recommendations in e-commerce personalization campaigns (benchmark from industry research)
04
A 2024 experiment found that adding a chatbot to a retail website increased conversion by 11% (study result reported by the publisher)
05
In a field study, AI-generated product recommendations increased click-through rate (CTR) by 16% versus a non-personalized baseline
06
In a peer-reviewed study of conversational recommender systems, the proposed approach improved ranking metrics (NDCG) by 0.07 absolute points over the baseline model
07
Retailers using AI-driven pricing and promotions reported average revenue lift of 3% in 2023 (survey result by a retail analytics publication)
08
In 2024, the average retail chatbot resolution rate target is 30–50% for Tier-1 intents (range reported in customer support AI implementation benchmarks)
Interpretation
Performance Metrics Interpretation
Performance metrics across AI agent e-commerce show that personalization and agent-driven experiences are consistently delivering measurable gains, with conversion lifting by 5% to 20% from recommendations, about a 1.6x increase in average order value, and chatbot-driven improvements reaching 11% in 2024 while aiming for 30% to 50% resolution on Tier-1 intents.
04 · Category
User Adoption4 stats
01
56% of consumers said they prefer a chatbot that can answer basic questions instantly (2022 survey result)
02
45% of customer service organizations reported using chatbots in 2023 (survey finding)
03
In 2024, 61% of consumers used mobile devices to shop online at least weekly (survey result, 2024)
04
In 2023, the EU had 92% smartphone penetration among individuals aged 16–74 (Eurostat ICT usage indicator)
Interpretation
User Adoption Interpretation
For user adoption, the strongest signal is that 56% of consumers already prefer instant answers from chatbots while 45% of customer service organizations are using them in 2023, showing mainstream momentum but still room for broader uptake.
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
Thomas Lindqvist. (2026, February 13). AI Agents Ecommerce Industry Statistics. Gitnux. https://gitnux.org/ai-agents-ecommerce-industry-statistics
MLA
Thomas Lindqvist. "AI Agents Ecommerce Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-agents-ecommerce-industry-statistics.
Chicago
Thomas Lindqvist. 2026. "AI Agents Ecommerce Industry Statistics." Gitnux. https://gitnux.org/ai-agents-ecommerce-industry-statistics.
Sources & references
22 datasets cited across this report · attribution is report-level
+5 additional datasets cited (not shown individually)