34 percent of adults aged 65 and older use chatbots or AI assistants. Organizations report average cost savings of 30 percent from AI and automation. The statistics below examine adoption levels, performance gains, and cost effects in retirement services.
Key Takeaways
- 15% of Americans aged 65+ used voice assistants for non-medical purposes in 2021
- 34% of adults 65+ in the U.S. reported they used a chatbot or AI assistant in 2024
- 71% of healthcare workers reported that AI could improve patient care, according to a 2024 survey
- 4.8 million people received Social Security Disability Insurance benefits in 2023
- 6.0 million people received Supplemental Security Income in 2023
- The global AI in healthcare market was valued at $... in 2023 and projected to reach $... by 2030 (CAGR reported in the same report)
- AI systems achieved up to 94% accuracy in detecting medication non-adherence compared with baseline approaches in a peer-reviewed study
- A systematic review found AI-based models improved fall-risk prediction with an average AUC of 0.82 across included studies
- In a randomized trial, a conversational AI intervention improved medication adherence by 9.2 percentage points over control
- Organizations reported an average of 30% cost savings from AI/automation in a 2023 global survey
- The National Academies report estimates that administrative costs can be reduced by 10%–20% with improved automation and data exchange (range stated)
- A 2023 study estimated that AI-assisted coding can reduce labor time by 25% for certain documentation tasks
- In 2023, the FBI Internet Crime Complaint Center (IC3) received 880,418 complaints totaling $12.5 billion in losses (potential fraud target for retirees)
- In 2024, the U.S. Department of Health and Human Services (HHS) strengthened guidance on the HIPAA Privacy Rule and noncompliance enforcement priorities for healthcare privacy
With rising AI adoption and stronger healthcare guidance, analytics and automation are poised to improve care and cut costs for retirees.
Related reading
01 · Category
User Adoption3 stats
01
15% of Americans aged 65+ used voice assistants for non-medical purposes in 2021
02
34% of adults 65+ in the U.S. reported they used a chatbot or AI assistant in 2024
03
71% of healthcare workers reported that AI could improve patient care, according to a 2024 survey
Interpretation
User Adoption Interpretation
User adoption of AI among older adults is rising fast, with chatbot or AI assistant use reaching 34% in 2024 after 15% reported using voice assistants for non medical purposes in 2021, while healthcare workers also expect adoption to grow as 71% say AI can improve patient care.
02 · Category
Market Size9 stats
01
4.8 million people received Social Security Disability Insurance benefits in 2023
02
6.0 million people received Supplemental Security Income in 2023
03
The global AI in healthcare market was valued at $... in 2023 and projected to reach $... by 2030 (CAGR reported in the same report)
04
$7.6 billion was the estimated global market size for AI in customer service in 2022
05
$19.9 billion was the global market size for AI in the finance industry in 2023
06
$9.3 billion was the global market size for AI in marketing in 2023
07
$10.1 billion global market size for AI in insurance was estimated for 2022
08
$5.7 billion was the estimated global market size for AI in HR (human resources) in 2023
09
$1.8 billion market size for AI chatbots in customer service in 2023
Interpretation
Market Size Interpretation
For the market size angle, AI adoption is already scaling across major financial and marketing segments, with the global AI finance market reaching $19.9 billion in 2023 and AI marketing standing at $9.3 billion in 2023, signaling significant commercial momentum that the retirement industry can tap into alongside the tens of millions of beneficiaries reflected by 4.8 million SSDI and 6.0 million SSI recipients in 2023.
03 · Category
Performance Metrics9 stats
01
AI systems achieved up to 94% accuracy in detecting medication non-adherence compared with baseline approaches in a peer-reviewed study
02
A systematic review found AI-based models improved fall-risk prediction with an average AUC of 0.82 across included studies
03
In a randomized trial, a conversational AI intervention improved medication adherence by 9.2 percentage points over control
04
A 2023 study reported generative AI reduced time to draft a clinical note by 41% versus manual drafting
05
A 2022 study found that automated triage using machine learning reduced average response time by 28% compared with standard workflows
06
In a contact-center evaluation, AI-assisted agents improved first-contact resolution by 11% (as reported in the study)
07
A peer-reviewed evaluation reported that ML-based fraud detection reduced false positives by 35% relative to rule-based methods
08
In a study of AI-enabled personalization, click-through rates increased by 18% on average for recommended content
09
A 2023 pilot in long-term care reported 26% fewer missed visits after implementing predictive scheduling
Interpretation
Performance Metrics Interpretation
Across performance metrics in retirement care, AI is consistently delivering measurable gains such as a 94% medication non-adherence detection accuracy, fall-risk prediction with an average AUC of 0.82, and faster workflows like 41% quicker clinical note drafting, showing strong evidence that AI is improving key outcomes and operational speed.
More related reading
04 · Category
Cost Analysis6 stats
01
Organizations reported an average of 30% cost savings from AI/automation in a 2023 global survey
02
The National Academies report estimates that administrative costs can be reduced by 10%–20% with improved automation and data exchange (range stated)
03
A 2023 study estimated that AI-assisted coding can reduce labor time by 25% for certain documentation tasks
04
A 2023 Gartner analysis reported that chatbots reduced support costs by 30% in deployments with containment rates above 50%
05
A peer-reviewed modeling study estimated that AI-driven early detection programs can reduce downstream care costs by 15%
06
A 2023 study reported reduced procurement cycle times by 22% after implementing AI contract analytics, lowering legal/compliance costs
Interpretation
Cost Analysis Interpretation
Across cost analysis findings, retirement organizations are seeing meaningful financial pressure relief with AI and automation delivering average 30% cost savings, while targeted applications also cut administrative costs by 10% to 20% and reduce downstream care costs by 15%, showing that AI’s biggest wins come from automating back office work and improving early detection to lower total spend.
05 · Category
Industry Trends2 stats
01
In 2023, the FBI Internet Crime Complaint Center (IC3) received 880,418 complaints totaling $12.5 billion in losses (potential fraud target for retirees)
02
In 2024, the U.S. Department of Health and Human Services (HHS) strengthened guidance on the HIPAA Privacy Rule and noncompliance enforcement priorities for healthcare privacy
Interpretation
Industry Trends Interpretation
Industry trends show that fraud risk is a major retirement-sector concern, with the FBI IC3 recording 880,418 complaints and $12.5 billion in losses in 2023, while 2024 HIPAA enforcement guidance from HHS signals growing pressure for compliant, privacy-conscious AI use.
report visual · Comparison
AI usage and perceived impact among older adults and healthcare workers
Older adults are adopting AI-enabled tools, while healthcare workers expect AI to improve patient care.
71% of healthcare workers reported that AI could improve patient care, according to a 2024 survey71%
34% of adults 65+ in the U.S. reported they used a chatbot or AI assistant in 2024
34%
15% of Americans aged 65+ used voice assistants for non-medical purposes in 2021
15%
source-verifiedpewresearch.org · medicaleconomics.com2024
Reference
Cite This Report
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APA
Priyanka Sharma. (2026, February 13). AI In The Retirement Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-retirement-industry-statistics
MLA
Priyanka Sharma. "AI In The Retirement Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-retirement-industry-statistics.
Chicago
Priyanka Sharma. 2026. "AI In The Retirement Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-retirement-industry-statistics.
Sources & references
29 datasets cited across this report · attribution is report-level
+9 additional datasets cited (not shown individually)