The Desire for AI Advice in Retirement Plans: A Latent Class Analysis

Chet R. Bennetts; Eric Ludwig

doi:10.2478/fprj-2025-0007

Figures & Tables

Distribution of AI Adoption Segments in Financial Advice.

AI Retirement Tool Preferences by Latent Class.

Financial Professional Usage by Latent Class.

Socio-demographic Relationships by Latent Class.

Sample Demographics

Variable	n	%
Age
18–34	846	42.30
35–44	680	34.00
45–64	446	22.30
65+	28	1.40
Gender
Female	1247	62.35
Male	753	37.65
Education
High school or less	226	11.30
Trade/vocational/associate degree	290	14.50
Some college, no degree	205	10.25
College graduate (4-year degree)	630	31.50
Postgraduate work	121	6.05
Graduate/professional degree	528	26.40
Marital Status
Married	1080	54.00
Divorced	101	5.05
Separated	22	1.10
Living w/a partner	146	7.30
Single, never married	628	31.40
Widowed	23	1.15
Race
White	1533	76.65
Black	321	16.05
Asian American	61	3.05
Native American	36	1.80
Other	49	2.45
Ethnicity
Hispanic	270	13.50
Non-Hispanic	1730	86.50
Dependent Children
Yes	970	48.50
No	1030	51.50
Household Income (in U.S. dollars)
Under 20,000	122	6.10
20 to 34,999	146	7.30
35 to 49,000	188	9.40
50 to 74,999	392	19.60
75 to 99,999	452	22.60
100 to 149,999	263	13.15
150 to 199,999	180	9.00
200 to 249,999	150	7.50
Work with one or more Financial Professional?
Yes	846	42.30
No	1049	52.45%
Unsure	105	5.25%
Type
Tax preparer or accountant	663	33.15%
Financial planner/advisor	565	28.25%
Investment advisor/manager	494	24.70%
Insurance agent/broker	441	22.05%
Banking professional	603	30.15%
Estate planning attorney	180	9.00%
Other financial professional	13	0.65%

Descriptive Statistics of Indicator Variables

Variable	n	%
Use AI at Work
No	1034	51.70
Yes	966	48.30
Use AI to improve understanding of retirement savings options
No	1110	55.50
Yes	890	44.50
Interest in ER provided AI tools enhance financial literacy or retirement planning
Yes	1147	21.45
No	429	21.20
Unsure	424	15.35
Confidence in making decisions based on AI-generated output
Not at all confident	307	15.35
Slightly confident	401	20.05
Somewhat confident	634	31.70
Very confident	443	22.15
Extremely confident	215	10.75
Knowledge about using AI compared to your co-workers
Much less knowledgeable	132	6.60
Slightly less knowledgeable	215	10.75
About the same	732	36.60
Slightly more knowledgeable	621	31.05
Much more knowledgeable	300	15.00
Comfort using AI tools to assist with financial decision making
Not at all comfortable	494	24.70
Not too comfortable	930	46.50
Somewhat comfortable	347	17.35
Very comfortable	229	11.45

Predicted AI Demand Latent Class Probabilities

Class	*Probability (%)*	*S.E.*
1	18.87	0.015
2	27.71	0.023
3	9.13	0.022
4	13.48	0.029
5	30.8	0.038

Financial Advice Sources and AI Retirement Tool Preferences by Latent Class

Variable	Class
Variable	1	2	3	4	5
Financial Service Use
Tax prep (CPA)	38.06	39.49	22.16	34.57	27.41
Uses financial planner (CFP)	50.66	44.42	5.68	13.99	13.02
Uses investment advisor (WMCP)	45.14	40.77	2.27	7.82	11.64
Uses insurance agent/broker	30.97	31.81	7.39	15.23	15.16
In-Plan AI Retirement Tool Preference
Estimating retirement income needs	53.02	50.09	25.30	46.50	53.91
Track progress toward retirement goals	60.37	55.76	23.30	44.44	52.68
Investment advice or rebalancing recommendations	61.42	56.12	10.80	25.10	43.64
Tax-efficient withdrawal strategies	46.98	51.37	10.23	32.51	40.89

Goodness of Fit Statistics for Latent Class Models

Model	ll(null)	df	AIC	BIC	entropy
Two class	−13341.9	35	26753.84	26949.87	0.817
Three class	−13011.3	53	26128.57	26425.41	0.768
Four class	−12846.5	71	25835.03	26232.7	0.758
Five class	−12812.9	88	25801.83	26294.71	0.742

Demographics by Latent Class

*Demographic Characteristics*		Class 1 (%)	Class 2 (%)	Class 3 (%)	Class 4 (%)	Class 5 (%)
Age	18–34	50.92	47.35	29.55	27.16	42.11
	35–44	28.08	34.00	35.23	39.92	34.92
	45–64	20.21	18.10	32.95	30.45	21.13
	65+	0.79	0.55	2.27	2.47	1.84

Gender	Female	51.71	52.10	80.11	80.25	65.70
	Male	48.29	47.90	19.89	19.75	34.30

Education	High school or less	9.45	6.22	18.18	12.35	14.40
	Trade/Vocational school/Associate's degree	10.50	13.71	19.89	12.35	16.85
	Some college, no degree	7.87	9.14	13.07	9.47	12.10
	College graduate (4-year degree)	43.04	40.59	24.43	25.51	21.29
	Postgraduate work	8.66	7.13	1.70	5.76	4.90
	Graduate/Professional Degree	20.47	23.22	22.73	34.57	30.47

Marital Status	Married	60.37	57.59	41.48	48.56	52.68
	Divorced/Separated	2.10	4.02	17.05	11.11	5.51
	Living w/a partner	7.09	4.94	8.52	9.88	8.12
	Single, never married	30.45	32.54	30.11	28.81	32.31
	Widowed	0.00	0.91	2.84	1.65	1.38

Race	White	73.75	80.07	76.14	80.25	74.27
	Black	20.47	13.53	13.64	11.93	17.76
	Asian American	1.57	3.47	2.84	2.47	3.83
	Native American	3.15	0.91	0.00	3.29	1.68
	Other	1.05	2.01	7.39	2.06	2.45

Ethnicity	Hispanic	18.64	14.81	11.36	9.05	11.64
Ethnicity	Non-Hispanic	81.36	85.19	88.64	90.95	88.36

Dependent	Yes	48.56	52.10	40.91	45.68	48.55
Children	No	51.44	47.90	59.09	54.32	51.45

Financial Characteristics

Household Income (in U.S. dollars)	Under 20,000	3.15	2.74	13.64	5.76	8.73
	20 to 34,999	4.46	3.84	18.75	11.11	7.35
	35 to 49,000	6.04	5.67	16.48	9.88	12.40
	50 to 74,999	12.34	19.56	19.32	20.16	23.74
	75 to 99,999	30.18	25.05%	14.77	24.28	17.61
	100 to 149,999	8.92	14.26	10.23	16.87	14.09
	150 to 199,999	13.39	10.05	5.68	5.76	7.66
	200 to 249,999	11.81	10.97	0.57	4.53	5.05
	Over 250,000	9.71	7.86	0.57	1.65	3.37

Financial Professional Use

Work with one or more financial professionals?	Yes	71.39	69.84	15.34	24.69	16.08
	No	28.61	28.15	77.84	65.02	75.19
	Unsure	0.00	2.01	6.82	10.29	8.73

Type of financial professional used in the last 12 months	Tax preparer or accountant	38.06	39.49	22.16	34.57	27.41
	Financial planner/advisor	50.66	44.42%	5.68	13.99	13.02
	Investment advisor/manager	45.14	40.77	2.27	7.82	11.64
	Insurance agent/broker	30.97	31.81%	7.39	15.23	15.16
	Banking professional	46.98	43.51	13.07	14.81	19.45
	Estate planning attorney	16.80	13.53	1.14	3.29	4.90
	Other financial professional	0.26	0.18	1.70	1.23	0.77

Mean Proportion of Class Belonging

Conditional Probability (%)
Variable	1	2	3	4	5
Uses AI at Work
Yes	75.4	64.1	9.2	29.2	37.4
AI for Financial Decision Making
Very comfortable	76.4	22.7	0.1	0.5	12.7
Somewhat comfortable	22.4	74.3	8.3	14.9	61.4
Not too comfortable	1.2	3.0	19.5	57.8	21.9
Not at all comfortable	0.0	0.0	72.1	26.8	4.1
Used AI for Retirement Planning
Yes	95.5	79.8	3.8	2.5	12.1
Interest in Employer-Provided AI tools
Yes	87.0	85.4	8.8	19.2	45.0
No	10.9	11.2	52.8	30.8	23.8
Unsure	2.1	3.4	38.4	50.0	31.2
Currently Uses a Financial Advisor
Yes	72.0	66.2	15.4	23.5	18.8
No	28.0	31.6	77.2	66.2	72.8
Unsure	0.0	2.1	7.4	10.3	8.4
Confident Decision Making Using AI
Not at all confident	0.0	0.7	89.5	39.9	5.2
Slightly confident	3.8	20.8	3.5	41.5	24.9
Somewhat confident	4.9	43.6	2.7	18.3	51.8
Very confident	42.7	34.3	2.2	-	14.2
Extremely confident	48.6	0.6	2.1	0.3	3.8
AI Knowledge vs. Co-workers
Much less knowledgeable	0.8	0.3	53.3	6.8	2.0
Slightly less knowledgeable	0.7	11.3	4.1	26.5	11.4
About the same	4.8	30.1	33.2	58.5	53.3
Slightly more knowledgeable	28.3	57.0	6.5	7.3	27.0
Much more knowledgeable	65.4	1.2	2.9	0.9	6.3

The Desire for AI Advice in Retirement Plans: A Latent Class Analysis

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Sample Demographics

Descriptive Statistics of Indicator Variables

Predicted AI Demand Latent Class Probabilities

Financial Advice Sources and AI Retirement Tool Preferences by Latent Class

Goodness of Fit Statistics for Latent Class Models

Demographics by Latent Class

Mean Proportion of Class Belonging

Paradigm

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