Source: https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-4-c017/
Author: Phil Hatch
Publisher: Akholi

Where did you gain your AI knowledge?

Study Data · Part 4 · Indicator Deep-Dive Analysis

# Where did you gain your AI knowledge?

Indicator C017 · By Phil Hatch · Akholi · October 9, 2026

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## On this page

25 sectionsIndicator SpecificationSummary of FindingsDistribution of ResponsesCoverage and Origin of Written ResponsesDistribution of Written SentimentDescriptive Statistics by SegmentTests of Difference Between SegmentsWritten Sentiment by SegmentAssociation with Cancellation RateAssociation with Customer SatisfactionAssociation with the Engagement Indicator MeanAssociation with Intent to LeaveAssociation of Written Sentiment with the Study MeasuresComparison of Associations Across the Four MeasuresClustering and Effective Sample SizeEquivalence Tests of Null ResultsRobustness ChecksMeasure Independence and Part-Whole CorrectionComparison with the Study NormComparison of Written Sentiment with Other Part 4 IndicatorsCo-Occurring Indicators and ThemesInterpretation of the DataLimitationsDefinitionsSources and Provenance

## Indicator Specification

Table 1. Indicator specificationTable

| Field | Value |
| --- | --- |
| Indicator code | C017 |
| Question as asked | Where did you gain your AI knowledge? |
| Failure category | Not one of the 100 rated indicators |
| Place in the survey | Respondent Demographics > 1.2 Experience and Expertise > Credentials |
| Indicator class | Respondent level |
| Indicator type | Categorical |
| Response scale | Levels: Vendor and partner training, On the job, Online courses, University coursework, Self-taught, Employer training program |
| Answering base | 800 of 850 respondents gave one of the listed answers, across 150 of 150 engagements. None answered I do not know or I prefer to not answer |
| Non-answers | I do not know 0, I prefer to not answer 0, blank 50 |
| Written responses addressing the indicator | 37 responses from 37 respondents on 33 engagements (0 primary, 37 secondary) |

## Summary of Findings

Table 2. Key results: association of the indicator with the four study measuresTable

| Measure | Effect size | n | Value | p |
| --- | --- | --- | --- | --- |
| Cancellation rate | Omega squared, 0 or 1 flag | 94 engagements | −0.030 | 0.792 |
| Customer satisfaction | Omega squared | 22 engagements | −0.027 | 0.521 |
| Engagement indicator mean | Omega squared | 94 engagements | −0.040 | 0.940 |
| Intent to leave | Omega squared | 94 engagements | −0.033 | 0.871 |

Of the 850 respondents, 800 answered the question. The answers spread almost evenly across the six sources, from 125 to 140 respondents each: vendor and partner training, on the job, online courses, university coursework, self-taught and the employer's training program. The source did not differ by role, vendor type or any segment family recorded at engagement level.

The source assigned to each engagement was not associated with cancellation (chi-square 2.39, p = 0.792, n = 94 engagements), customer satisfaction among active engagements (Welch F 0.43, p = 0.521, n = 22 engagements), the engagement indicator mean (Welch F 0.24, p = 0.940, n = 94 engagements) or intent to leave (Welch F 0.36, p = 0.871, n = 94 engagements). The engagement indicator mean and intent to leave were equivalent to zero, and every robustness check held.

The written responses addressing the indicator numbered 37, all from individual contributors, on 33 engagements. Every response was secondary. Of the 37 responses, 19 (51.35%) were negative and 14 (37.84%) positive. Whatever source they named in the answer, the respondents who wrote described learning the agents from colleagues, from outside material and on live work, after training of slides and videos.

## Distribution of Responses

Table 3. Distribution of responses, respondent levelTable

| Answer | Respondents | Share of answered (base 800) | Cumulative share | Engagements with at least one | Share of 150 engagements | Distressed |
| --- | --- | --- | --- | --- | --- | --- |
| Vendor and partner training | 140 | 17.50% | 17.50% | 97 | 64.67% | Not applicable |
| On the job | 136 | 17.00% | 34.50% | 92 | 61.33% | Not applicable |
| Online courses | 136 | 17.00% | 51.50% | 103 | 68.67% | Not applicable |
| University coursework | 132 | 16.50% | 68.00% | 89 | 59.33% | Not applicable |
| Self-taught | 131 | 16.38% | 84.38% | 85 | 56.67% | Not applicable |
| Employer training program | 125 | 15.63% | 100.00% | 88 | 58.67% | Not applicable |
| Answered, total | 800 | 100.00% | | 150 | 100.00% | |

Each engagement was assigned the source given by the largest number of its respondents. Fifty-six engagements were tied and carry no assigned source, and 94 carry one. Every source was the assigned answer on 10 or more engagements.

## Coverage and Origin of Written Responses

All 37 responses were secondary. They came from 2 questions outside the indicator's own survey section (C135 with 28 responses and C030 with 9 responses). Each of the nine responses to C030, on what the respondent loves most about the job, listed agentic skill picked up on the job or firsthand.

The 28 responses to C135, the comment field on the employer, described how the respondents learned the agents. Eleven described the training as slides, recorded videos or a recorded session and a PDF, in several cases followed straight by live work, and one said the course came three months after the respondent had started the work. Eleven said the respondent learned from a lead, a colleague or a senior, and two described a note file the team kept and passed to new joiners in place of the official material. Seven described learning alone, from outside videos at night, search, vendor documents or old test cases and broken runs. Eleven said no one senior, or no one above the respondent, knew the agents or had done the work before, so that questions went unanswered for days or came back to the respondent.

Figure 1. Written responses addressing the indicator, by question answered and written score (n = 37 responses)ExhibitNote: Each bar is one survey question. Every question lies outside the indicator's survey section, so every response is secondary. Segments wide enough to hold a label carry their count. C135 asked: “Add any comments on your employer that the ratings in this section do not capture.” C030 asked: “What are the top 3 things that you love most about your job?”Table 4. Written responses by originTable

| Origin | Responses | Respondents | Engagements | Negative | Strongest negative (−10) | Positive | Mean written score |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Primary | 0 | 0 | 0 | 0 | 0 | 0 | None |
| Secondary | 37 | 37 | 33 | 19 of 37 (51.35%) | 1 of 37 (2.70%) | 14 of 37 (37.84%) | −0.8 |
| All responses | 37 | 37 | 33 | 19 of 37 (51.35%) | 1 of 37 (2.70%) | 14 of 37 (37.84%) | −0.8 |

## Distribution of Written Sentiment

Figure 2. Distribution of written sentiment (n = 37 responses)ExhibitNote: Column height is the share of the 37 responses. Labels give the count and the share.Table 5. Summary statistics of written sentimentTable

| Statistic | Value | Basis |
| --- | --- | --- |
| Mean written score | −0.8 | 95% CI −2.4 to 0.8, cluster bootstrap by engagement, 10,000 draws, n = 37 responses |
| Median written score | −5.0 | n = 37 responses |
| Negative responses | 19 of 37 (51.35%) | 95% CI 34.29% to 68.29% of 37 responses, cluster bootstrap by engagement |
| Strongest negative responses (−10) | 1 of 37 (2.70%) | Statements of totality, constancy or serious harm |
| Positive responses | 14 of 37 (37.84%) | +5 or +10 |
| Net balance | −13.51 percentage points | Share positive minus share negative, base 37 responses |
| Respondent-level mean | −0.8 | Mean of each respondent's own mean written score, n = 37 respondents |

Of the 37 responses, 19 (51.35%, 95% CI 34.29% to 68.29%) were negative and 1 carried the strongest negative score of −10. Positive responses numbered 14 (37.84%), and 4 were neutral. The responses had a mean written score of −0.8 (95% CI −2.4 to 0.8, n = 37 responses on 33 engagements) and a median of −5.0.

Every response to C030 was positive. The responses to C135 were mostly negative (19 of 28), Of their five positive responses, four paired thin training with a lead, a colleague or the team's own notes that made up for it, and the other found the agentic courses practical and placed the gap in banking knowledge.

## Descriptive Statistics by Segment

Table 6. Descriptive statistics by segmentTable

| Segment | Base | Answered | Answer rate | Engagements | Vendor and partner training, share | On the job, share | Online courses, share |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 850 | 800 | 94.12% of 850 | 150 | 17.50% | 17.00% | 17.00% |
| Outsourcing model | | | | | | | |
| CXM | 232 | 221 | 95.26% of 232 | 42 | 17.19% | 17.65% | 13.57% |
| ITO | 244 | 230 | 94.26% of 244 | 40 | 15.65% | 18.26% | 16.09% |
| BPO | 209 | 195 | 93.30% of 209 | 37 | 15.90% | 17.44% | 21.54% |
| KPO | 165 | 154 | 93.33% of 165 | 31 | 22.73% | 13.64% | 17.53% |
| Institution type | | | | | | | |
| Asset management | 132 | 122 | 92.42% of 132 | 24 | 17.21% | 15.57% | 17.21% |
| Wealth management and private banking | 140 | 135 | 96.43% of 140 | 23 | 11.85% | 15.56% | 20.00% |
| Investment banking (advisory and capital-markets origination) | 105 | 96 | 91.43% of 105 | 19 | 16.67% | 17.71% | 18.75% |
| Insurance (life, property and casualty, health) | 78 | 74 | 94.87% of 78 | 14 | 20.27% | 18.92% | 10.81% |
| Commercial and business banking | 82 | 76 | 92.68% of 82 | 13 | 19.74% | 15.79% | 13.16% |
| Payments and merchant acquiring (networks, acquiring, processing) | 71 | 68 | 95.77% of 71 | 13 | 16.18% | 14.71% | 17.65% |
| Credit card and payments issuing | 73 | 69 | 94.52% of 73 | 12 | 23.19% | 23.19% | 17.39% |
| Retail and consumer banking | 73 | 68 | 93.15% of 73 | 12 | 22.06% | 11.76% | 16.18% |
| Markets and trading (sales and trading, global markets) | 57 | 56 | 98.25% of 57 | 11 | 17.86% | 14.29% | 19.64% |
| Private equity and private capital | 39 | 36 | 92.31% of 39 | 9 | 13.89% | 30.56% | 16.67% |
| Process family | | | | | | | |
| Corporate and back-office functions | 248 | 230 | 92.74% of 248 | 47 | 21.74% | 15.22% | 15.22% |
| Technology engineering and operations | 204 | 192 | 94.12% of 204 | 35 | 14.06% | 20.83% | 17.19% |
| Client servicing and communications | 94 | 92 | 97.87% of 94 | 16 | 14.13% | 16.30% | 13.04% |
| Trade, settlement and reconciliation | 80 | 77 | 96.25% of 80 | 15 | 14.29% | 22.08% | 22.08% |
| Payments, cards and disputes | 73 | 70 | 95.89% of 73 | 12 | 18.57% | 20.00% | 15.71% |
| Credit, underwriting and suitability | 57 | 54 | 94.74% of 57 | 9 | 20.37% | 12.96% | 11.11% |
| Regulatory, audit, tax and legal | 51 | 45 | 88.24% of 51 | 9 | 11.11% | 11.11% | 24.44% |
| Financial crime and client onboarding | 43 | 40 | 93.02% of 43 | 7 | 25.00% | 7.50% | 27.50% |
| Class of work | | | | | | | |
| LOB Operational | 451 | 429 | 95.12% of 451 | 76 | 17.25% | 16.55% | 17.02% |
| Corporate Functional | 399 | 371 | 92.98% of 399 | 74 | 17.79% | 17.52% | 16.98% |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 175 | 162 | 92.57% of 175 | 31 | 19.14% | 16.67% | 17.28% |
| Active, Transition/Cut-Over | 250 | 235 | 94.00% of 250 | 43 | 17.87% | 14.89% | 17.02% |
| Active, Production | 103 | 95 | 92.23% of 103 | 20 | 14.74% | 18.95% | 20.00% |
| Canceled | 322 | 308 | 95.65% of 322 | 56 | 17.21% | 18.18% | 15.91% |
| Respondent role | | | | | | | |
| Individual Contributor | 667 | 619 | 92.80% of 667 | 150 | 17.77% | 17.93% | 15.83% |
| Engagement Manager | 150 | 150 | 100.00% of 150 | 150 | 16.67% | 12.67% | 24.00% |
| Portfolio Director | 31 | 29 | 93.55% of 31 | 29 | 17.24% | 20.69% | 6.90% |
| Customer Management Executive | 2 | 2 | 2 of 2 | 2 | 0 | 0 | 0 |
| Vendor type | | | | | | | |
| IT services major | 316 | 292 | 92.41% of 316 | 59 | 15.41% | 15.07% | 15.41% |
| BPO specialist | 198 | 188 | 94.95% of 198 | 37 | 18.09% | 15.96% | 21.28% |
| Consulting firm | 117 | 113 | 96.58% of 117 | 23 | 21.24% | 19.47% | 16.81% |
| Boutique or specialist provider | 87 | 79 | 90.80% of 87 | 17 | 11.39% | 24.05% | 16.46% |
| Pure-play agentic AI firm | 75 | 72 | 96.00% of 75 | 14 | 20.83% | 19.44% | 16.67% |
| Not reported, recovered by engagement | 57 | 56 | 98.25% of 57 | 47 | 23.21% | 12.50% | 12.50% |

Table 7. Descriptive statistics by segment, remaining answer levelsTable

| Segment | Base | Answered | Answer rate | Engagements | University coursework, share | Self-taught, share | Employer training program, share |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 850 | 800 | 94.12% of 850 | 150 | 16.50% | 16.38% | 15.63% |
| Outsourcing model | | | | | | | |
| CXM | 232 | 221 | 95.26% of 232 | 42 | 16.74% | 20.36% | 14.48% |
| ITO | 244 | 230 | 94.26% of 244 | 40 | 18.70% | 15.22% | 16.09% |
| BPO | 209 | 195 | 93.30% of 209 | 37 | 17.95% | 12.82% | 14.36% |
| KPO | 165 | 154 | 93.33% of 165 | 31 | 11.04% | 16.88% | 18.18% |
| Institution type | | | | | | | |
| Asset management | 132 | 122 | 92.42% of 132 | 24 | 19.67% | 16.39% | 13.93% |
| Wealth management and private banking | 140 | 135 | 96.43% of 140 | 23 | 17.04% | 17.04% | 18.52% |
| Investment banking (advisory and capital-markets origination) | 105 | 96 | 91.43% of 105 | 19 | 14.58% | 18.75% | 13.54% |
| Insurance (life, property and casualty, health) | 78 | 74 | 94.87% of 78 | 14 | 25.68% | 9.46% | 14.86% |
| Commercial and business banking | 82 | 76 | 92.68% of 82 | 13 | 15.79% | 25.00% | 10.53% |
| Payments and merchant acquiring (networks, acquiring, processing) | 71 | 68 | 95.77% of 71 | 13 | 7.35% | 22.06% | 22.06% |
| Credit card and payments issuing | 73 | 69 | 94.52% of 73 | 12 | 11.59% | 8.70% | 15.94% |
| Retail and consumer banking | 73 | 68 | 93.15% of 73 | 12 | 19.12% | 16.18% | 14.71% |
| Markets and trading (sales and trading, global markets) | 57 | 56 | 98.25% of 57 | 11 | 14.29% | 16.07% | 17.86% |
| Private equity and private capital | 39 | 36 | 92.31% of 39 | 9 | 16.67% | 8.33% | 13.89% |
| Process family | | | | | | | |
| Corporate and back-office functions | 248 | 230 | 92.74% of 248 | 47 | 12.17% | 19.57% | 16.09% |
| Technology engineering and operations | 204 | 192 | 94.12% of 204 | 35 | 15.10% | 15.10% | 17.71% |
| Client servicing and communications | 94 | 92 | 97.87% of 94 | 16 | 22.83% | 19.57% | 14.13% |
| Trade, settlement and reconciliation | 80 | 77 | 96.25% of 80 | 15 | 19.48% | 9.09% | 12.99% |
| Payments, cards and disputes | 73 | 70 | 95.89% of 73 | 12 | 18.57% | 12.86% | 14.29% |
| Credit, underwriting and suitability | 57 | 54 | 94.74% of 57 | 9 | 20.37% | 14.81% | 20.37% |
| Regulatory, audit, tax and legal | 51 | 45 | 88.24% of 51 | 9 | 20.00% | 24.44% | 8.89% |
| Financial crime and client onboarding | 43 | 40 | 93.02% of 43 | 7 | 15.00% | 10.00% | 15.00% |
| Class of work | | | | | | | |
| LOB Operational | 451 | 429 | 95.12% of 451 | 76 | 18.41% | 16.08% | 14.69% |
| Corporate Functional | 399 | 371 | 92.98% of 399 | 74 | 14.29% | 16.71% | 16.71% |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 175 | 162 | 92.57% of 175 | 31 | 15.43% | 11.73% | 19.75% |
| Active, Transition/Cut-Over | 250 | 235 | 94.00% of 250 | 43 | 17.87% | 18.30% | 14.04% |
| Active, Production | 103 | 95 | 92.23% of 103 | 20 | 17.89% | 13.68% | 14.74% |
| Canceled | 322 | 308 | 95.65% of 322 | 56 | 15.58% | 18.18% | 14.94% |
| Respondent role | | | | | | | |
| Individual Contributor | 667 | 619 | 92.80% of 667 | 150 | 16.64% | 15.83% | 15.99% |
| Engagement Manager | 150 | 150 | 100.00% of 150 | 150 | 16.00% | 18.00% | 12.67% |
| Portfolio Director | 31 | 29 | 93.55% of 31 | 29 | 13.79% | 20.69% | 20.69% |
| Customer Management Executive | 2 | 2 | 2 of 2 | 2 | 1 | 0 | 1 |
| Vendor type | | | | | | | |
| IT services major | 316 | 292 | 92.41% of 316 | 59 | 18.15% | 18.15% | 17.81% |
| BPO specialist | 198 | 188 | 94.95% of 198 | 37 | 16.49% | 16.49% | 11.70% |
| Consulting firm | 117 | 113 | 96.58% of 117 | 23 | 11.50% | 8.85% | 22.12% |
| Boutique or specialist provider | 87 | 79 | 90.80% of 87 | 17 | 16.46% | 20.25% | 11.39% |
| Pure-play agentic AI firm | 75 | 72 | 96.00% of 75 | 14 | 16.67% | 13.89% | 12.50% |
| Not reported, recovered by engagement | 57 | 56 | 98.25% of 57 | 47 | 17.86% | 19.64% | 14.29% |

Each share is computed on the respondents who answered in that row. Rows with fewer than 10 respondents report counts only.

## Tests of Difference Between Segments

Table 8. Tests of difference between segmentsTable

| Segment family | Unit | Chi-square | df | p | Holm p | Cramer's V | Test for p | Levels excluded |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Outsourcing model | Engagement | 17.66 | 15 | 0.288 | 1.000 | 0.25 | Monte Carlo, simulated | None |
| Institution type | Engagement | 4.88 | 10 | 0.924 | 1.000 | 0.24 | Monte Carlo, simulated | a |
| Process family | Engagement | 2.31 | 5 | 0.810 | 1.000 | 0.21 | Monte Carlo, simulated | b |
| Class of work | Engagement | 2.78 | 5 | 0.734 | 1.000 | 0.17 | chi-square | None |
| Engagement status and lifecycle stage | Engagement | 13.57 | 15 | 0.579 | 1.000 | 0.22 | Monte Carlo, simulated | None |
| Respondent role | Respondent | 11.04 | 10 | 0.354 | 1.000 | 0.08 | Monte Carlo, simulated | Customer Management Executive, n = 2 |
| Vendor type | Respondent | 27.70 | 25 | 0.322 | 1.000 | 0.08 | chi-square | None |

Note: a Levels excluded: Insurance (life, property and casualty, health), n = 9, Commercial and business banking, n = 8, Payments and merchant acquiring (networks, acquiring, processing), n = 7, Credit card and payments issuing, n = 6, Retail and consumer banking, n = 9, Markets and trading (sales and trading, global markets), n = 8, Private equity and private capital, n = 5. b Levels excluded: Client servicing and communications, n = 8, Trade, settlement and reconciliation, n = 7, Payments, cards and disputes, n = 9, Credit, underwriting and suitability, n = 5, Regulatory, audit, tax and legal, n = 7, Financial crime and client onboarding, n = 5.

Segment families recorded at engagement level were tested on engagements, and respondent role and vendor type on respondents. After Holm correction, the source differed in no family.

## Written Sentiment by Segment

Figure 3. Written sentiment by engagement status and lifecycle stage, share of each group's responsesExhibitNote: Each bar is the whole of its group's responses, divided by written score from −10 at the left to +10 at the right. Segments large enough to hold a label carry their share, or their count in groups of fewer than 10 responses.Table 9. Written sentiment by segmentTable

| Segment | Responses | Respondents | Engagements | Mean written score | Negative | Strongest negative (−10) |
| --- | --- | --- | --- | --- | --- | --- |
| Engagement status and lifecycle stage | | | | | | |
| Active, Build-Out | 11 | 11 | 10 | −0.5 | 6 of 11 (54.55%) | 0 of 11 (0.00%) |
| Active, Transition/Cut-Over | 11 | 11 | 9 | 0.0 | 5 of 11 (45.45%) | 0 of 11 (0.00%) |
| Active, Production | 4 | 4 | 4 | ‡ | 2 of 4 | 1 of 4 |
| Canceled | 11 | 11 | 10 | −1.4 | 6 of 11 (54.55%) | 0 of 11 (0.00%) |
| Respondent role | | | | | | |
| Individual Contributor | 37 | 37 | 33 | −0.8 | 19 of 37 (51.35%) | 1 of 37 (2.70%) |
| Engagement Manager | 0 | 0 | 0 | No responses | | |
| Portfolio Director | 0 | 0 | 0 | No responses | | |
| Customer Management Executive | 0 | 0 | 0 | No responses | | |

Note: ‡ Base under 10. No statistic is reported.

Written sentiment did not differ by engagement status and lifecycle stage (Kruskal-Wallis H 0.66, df 3, p = 0.883, n = 33 engagements). All 37 responses came from individual contributors, so no test across roles was run.

## Association with Cancellation Rate

Cancellation rate is the share of engagements canceled by the study date, measured at engagement level (150 engagements, 56 canceled).

Table 10. Association with cancellation rate by answer levelTable

| Answer level | Engagements | Canceled | Cancellation rate |
| --- | --- | --- | --- |
| Vendor and partner training | 17 | 5 | 29.41% |
| On the job | 16 | 8 | 50.00% |
| Online courses | 12 | 5 | 41.67% |
| University coursework | 15 | 7 | 46.67% |
| Self-taught | 20 | 10 | 50.00% |
| Employer training program | 14 | 5 | 35.71% |

Table 11. Association with cancellation rate, tests across answer levels by segmentTable

| Segment | Engagements | Chi-square | df | p | Holm p | Cramer's V | Test for p |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 94 | 2.39 | 5 | 0.792 | 0.792 | 0.16 | chi-square |
| Outsourcing model | | | | | | | |
| CXM | 26 | a | | | | | |
| ITO | 25 | a | | | | | |
| BPO | 21 | a | | | | | |
| KPO | 22 | a | | | | | |
| Institution type | | | | | | | |
| Asset management | 17 | a | | | | | |
| Wealth management and private banking | 12 | a | | | | | |
| Investment banking (advisory and capital-markets origination) | 13 | a | | | | | |
| Insurance (life, property and casualty, health) | 9 | ‡ | | | | | |
| Commercial and business banking | 8 | ‡ | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 7 | ‡ | | | | | |
| Credit card and payments issuing | 6 | ‡ | | | | | |
| Retail and consumer banking | 9 | ‡ | | | | | |
| Markets and trading (sales and trading, global markets) | 8 | ‡ | | | | | |
| Private equity and private capital | 5 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 32 | a | | | | | |
| Technology engineering and operations | 21 | a | | | | | |
| Client servicing and communications | 8 | ‡ | | | | | |
| Trade, settlement and reconciliation | 7 | ‡ | | | | | |
| Payments, cards and disputes | 9 | ‡ | | | | | |
| Credit, underwriting and suitability | 5 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 5 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 22 | 0.73 | 1 | 0.392 | 0.784 | 0.18 | chi-square |
| Corporate Functional | 42 | a | | | | | |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | | b | | | | | |
| Active, Transition/Cut-Over | | b | | | | | |
| Active, Production | | b | | | | | |
| Canceled | | b | | | | | |

Note: ‡ Base under 10. No statistic is reported. a Not tested: fewer than two levels of 10 or more engagements. b Not tested: no variation in cancellation.

Across the 94 engagements with an assigned source, cancellation did not differ by source (chi-square 2.39, df = 5, p = 0.792, Cramer's V 0.16).

## Association with Customer Satisfaction

Customer satisfaction is the percentage recorded against each engagement. The engagement-level estimate uses the active engagements in the sources with 10 or more active engagements.

Table 12. Association with customer satisfaction by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Vendor and partner training | 12 | 60.0 | 13.9 |
| On the job | 8 | ‡ | |
| Online courses | 7 | ‡ | |
| University coursework | 8 | ‡ | |
| Self-taught | 10 | 63.9 | 14.0 |
| Employer training program | 9 | ‡ | |

Note: ‡ Base under 10. No statistic is reported.Table 13. Association with customer satisfaction, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 22 | 0.43 | 1, 19.2 | 0.521 | 0.521 | −0.027 | † |
| Outsourcing model | | | | | | | |
| CXM | 15 | a | | | | | |
| ITO | 14 | a | | | | | |
| BPO | 12 | a | | | | | |
| KPO | 13 | a | | | | | |
| Institution type | | | | | | | |
| Asset management | 9 | ‡ | | | | | |
| Wealth management and private banking | 8 | ‡ | | | | | |
| Investment banking (advisory and capital-markets origination) | 5 | ‡ | | | | | |
| Insurance (life, property and casualty, health) | 6 | ‡ | | | | | |
| Commercial and business banking | 5 | ‡ | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 4 | ‡ | | | | | |
| Credit card and payments issuing | 3 | ‡ | | | | | |
| Retail and consumer banking | 5 | ‡ | | | | | |
| Markets and trading (sales and trading, global markets) | 5 | ‡ | | | | | |
| Private equity and private capital | 4 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 17 | a | | | | | |
| Technology engineering and operations | 14 | a | | | | | |
| Client servicing and communications | 3 | ‡ | | | | | |
| Trade, settlement and reconciliation | 3 | ‡ | | | | | |
| Payments, cards and disputes | 7 | ‡ | | | | | |
| Credit, underwriting and suitability | 4 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 3 | ‡ | | | | | |
| Financial crime and client onboarding | 3 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 31 | a | | | | | |
| Corporate Functional | 23 | a | | | | | |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 13 | a | | | | | |
| Active, Transition/Cut-Over | 30 | a | | | | | |
| Active, Production | 11 | a | | | | | |
| Canceled | | b | | | | | |

Note: † Base under 30. No interval is reported. ‡ Base under 10. No statistic is reported. a Not tested: fewer than two levels of 10 or more engagements. b Not tested: canceled engagements fall outside the active population.

Customer satisfaction did not differ by source (Welch F 0.43, p = 0.521, n = 22 engagements), on a base of 22 active engagements in the sources with 10 or more active engagements.

## Association with the Engagement Indicator Mean

The engagement indicator mean is the mean of an engagement's ratings across the rated indicators, measured at engagement level (150 engagements). The source is not a rated indicator and does not enter the mean.

Table 14. Association with the engagement indicator mean by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Vendor and partner training | 17 | 3.8 | 1.6 |
| On the job | 16 | 3.9 | 1.6 |
| Online courses | 12 | 3.9 | 1.6 |
| University coursework | 15 | 4.0 | 1.2 |
| Self-taught | 20 | 3.7 | 1.5 |
| Employer training program | 14 | 4.3 | 1.6 |

Table 15. Association with the engagement indicator mean, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 94 | 0.24 | 5, 39.3 | 0.940 | 1.000 | −0.040 | 0.000 to 0.010 |
| Outsourcing model | | | | | | | |
| CXM | 26 | a | | | | | |
| ITO | 25 | a | | | | | |
| BPO | 21 | a | | | | | |
| KPO | 22 | a | | | | | |
| Institution type | | | | | | | |
| Asset management | 17 | a | | | | | |
| Wealth management and private banking | 12 | a | | | | | |
| Investment banking (advisory and capital-markets origination) | 13 | a | | | | | |
| Insurance (life, property and casualty, health) | 9 | ‡ | | | | | |
| Commercial and business banking | 8 | ‡ | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 7 | ‡ | | | | | |
| Credit card and payments issuing | 6 | ‡ | | | | | |
| Retail and consumer banking | 9 | ‡ | | | | | |
| Markets and trading (sales and trading, global markets) | 8 | ‡ | | | | | |
| Private equity and private capital | 5 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 32 | a | | | | | |
| Technology engineering and operations | 21 | a | | | | | |
| Client servicing and communications | 8 | ‡ | | | | | |
| Trade, settlement and reconciliation | 7 | ‡ | | | | | |
| Payments, cards and disputes | 9 | ‡ | | | | | |
| Credit, underwriting and suitability | 5 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 5 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 22 | 0.03 | 1, 19.5 | 0.865 | 1.000 | −0.046 | † |
| Corporate Functional | 42 | a | | | | | |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 13 | a | | | | | |
| Active, Transition/Cut-Over | 30 | a | | | | | |
| Active, Production | 11 | a | | | | | |
| Canceled | 40 | a | | | | | |

Note: ‡ Base under 10. No statistic is reported. † Base under 30. No interval is reported. a Not tested: fewer than two levels of 10 or more engagements.

The engagement indicator mean did not differ by source (Welch F 0.24, p = 0.940, n = 94 engagements).

## Association with Intent to Leave

Intent to leave is the answer to C019, “How likely are you to leave your current job in the next 12 months?”, rated 1 to 10 by up to 798 respondents. For the indicator, the engagement-level comparison uses the mean intent to leave of each engagement.

Table 16. Association with intent to leave by answer levelTable

| Answer level | Engagements | Mean of the measure | SD |
| --- | --- | --- | --- |
| Vendor and partner training | 17 | 6.8 | 2.3 |
| On the job | 16 | 7.4 | 2.5 |
| Online courses | 12 | 7.0 | 2.2 |
| University coursework | 15 | 7.2 | 2.2 |
| Self-taught | 20 | 7.3 | 2.6 |
| Employer training program | 14 | 6.3 | 2.4 |

Table 17. Association with intent to leave, tests across answer levels by segmentTable

| Segment | Engagements | Welch F | df | p | Holm p | Omega squared | 90% CI |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Study set | 94 | 0.36 | 5, 39.7 | 0.871 | 1.000 | −0.033 | 0.000 to 0.031 |
| Outsourcing model | | | | | | | |
| CXM | 26 | a | | | | | |
| ITO | 25 | a | | | | | |
| BPO | 21 | a | | | | | |
| KPO | 22 | a | | | | | |
| Institution type | | | | | | | |
| Asset management | 17 | a | | | | | |
| Wealth management and private banking | 12 | a | | | | | |
| Investment banking (advisory and capital-markets origination) | 13 | a | | | | | |
| Insurance (life, property and casualty, health) | 9 | ‡ | | | | | |
| Commercial and business banking | 8 | ‡ | | | | | |
| Payments and merchant acquiring (networks, acquiring, processing) | 7 | ‡ | | | | | |
| Credit card and payments issuing | 6 | ‡ | | | | | |
| Retail and consumer banking | 9 | ‡ | | | | | |
| Markets and trading (sales and trading, global markets) | 8 | ‡ | | | | | |
| Private equity and private capital | 5 | ‡ | | | | | |
| Process family | | | | | | | |
| Corporate and back-office functions | 32 | a | | | | | |
| Technology engineering and operations | 21 | a | | | | | |
| Client servicing and communications | 8 | ‡ | | | | | |
| Trade, settlement and reconciliation | 7 | ‡ | | | | | |
| Payments, cards and disputes | 9 | ‡ | | | | | |
| Credit, underwriting and suitability | 5 | ‡ | | | | | |
| Regulatory, audit, tax and legal | 7 | ‡ | | | | | |
| Financial crime and client onboarding | 5 | ‡ | | | | | |
| Class of work | | | | | | | |
| LOB Operational | 22 | 0.10 | 1, 19.6 | 0.760 | 1.000 | −0.043 | † |
| Corporate Functional | 42 | a | | | | | |
| Engagement status and lifecycle stage | | | | | | | |
| Active, Build-Out | 13 | a | | | | | |
| Active, Transition/Cut-Over | 30 | a | | | | | |
| Active, Production | 11 | a | | | | | |
| Canceled | 40 | a | | | | | |

Note: ‡ Base under 10. No statistic is reported. † Base under 30. No interval is reported. a Not tested: fewer than two levels of 10 or more engagements.

Intent to leave did not differ by source (Welch F 0.36, p = 0.871, n = 94 engagements).

## Association of Written Sentiment with the Study Measures

Table 18. Written sentiment and the study measuresTable

| Comparison | With a negative response | Without a negative response | Test | Statistic | n | p |
| --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate, engagements | 5 of 17 (29.41%) | 51 of 133 (38.35%) | Fisher exact | | 150 | 0.598 |
| Customer satisfaction, active engagements | 63.33%, n = 12 | 64.21%, n = 82 | Welch t | −0.26 | 94 | 0.797 |
| Engagement mean written score and cancellation, engagements | | | Point-biserial r | −0.03 | 33 | 0.854 |
| Respondent mean written score and intent to leave, respondents | | | Spearman rho | −0.13 | 32 | 0.464 |

The comparisons set engagements with a negative written response against all other engagements, most of which had no written response addressing the indicator. Cancellation affected 5 of the 17 engagements with a negative response (29.41%), against 51 of the 133 other engagements (38.35%), a difference that did not reach significance at 0.05 (Fisher exact p = 0.598). Customer satisfaction was 63.33% on the 12 active engagements with a negative response, against 64.21% on the 82 other active engagements (Welch t −0.26, p = 0.797), a difference that did not reach significance at 0.05. The engagement mean written score against cancellation (r = −0.03, p = 0.854, n = 33 engagements) did not reach significance at 0.05, and the respondent mean written score against intent to leave (rho = −0.13, p = 0.464, n = 32 respondents) did not reach significance at 0.05. No written outcome test reached significance.

## Comparison of Associations Across the Four Measures

Table 19. Associations across the four measuresTable

| Measure | Effect size | n | Value | p | Equivalent to zero | Rank among the four |
| --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate | Omega squared, 0 or 1 flag | 94 | −0.030 | 0.792 | Yes | 2 |
| Customer satisfaction | Omega squared | 22 | −0.027 | 0.521 | No | 1 |
| Engagement indicator mean | Omega squared | 94 | −0.040 | 0.940 | Yes | 4 |
| Intent to leave | Omega squared | 94 | −0.033 | 0.871 | Yes | 3 |

Steiger's z compares two correlations, and a categorical indicator yields an effect size across its levels and not a correlation. The pairs of measures were therefore not compared. No association reached significance.

## Clustering and Effective Sample Size

Table 20. Clustering and effective sample sizeTable

| Statistic | Value | Reading |
| --- | --- | --- |
| Clusters (engagements) | 150 | Engagements with one or more answers. |
| Mean respondents per engagement | 5.3 | Answers per engagement, among engagements with one or more answers. |
| ICC(1) | 0.00 | Share of the variance that lies between engagements. |
| Design effect | 1.00 | One plus the product of the ICC and the mean cluster size less one. |
| Nominal respondent n | 800 | Every answer, with “I do not know” and “I prefer to not answer” counted as levels, as in the plurality rule. |
| Effective n | 800 | Nominal n divided by the design effect. |
| Cluster bootstrap applied | No | Applied to every respondent-level interval where the ICC is 0.05 or above. |

Answers did not cluster within engagements (ICC 0.00): respondents on the same engagement named different sources. The design effect was 1.00, and the effective n equaled the 800 answers. The respondent-level tests used standard errors clustered by engagement.

## Equivalence Tests of Null Results

Table 21. Equivalence tests of null resultsTable

| Measure | n | Omega squared | Equivalence bound | Equivalence p | Equivalent to zero | Achieved power | MDE at power 0.80 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Cancellation rate | 94 | −0.030 | Omega squared < 0.090 | 0.007 | Yes | 0.61 | 0.127 |
| Customer satisfaction | 22 | −0.027 | Omega squared < 0.090 | 0.187 | No | 0.29 | 0.283 |
| Engagement indicator mean | 94 | −0.040 | Omega squared < 0.090 | 0.002 | Yes | 0.61 | 0.127 |
| Intent to leave | 94 | −0.033 | Omega squared < 0.090 | 0.005 | Yes | 0.61 | 0.127 |

The engagement indicator mean (equivalence p = 0.002) and intent to leave (equivalence p = 0.005) were equivalent to zero, each on 94 engagements. Customer satisfaction was not (equivalence p = 0.187, n = 22 engagements), and its result is inconclusive rather than evidence of no association. The cancellation contrast carries no equivalence test.

## Robustness Checks

Table 22. Robustness checksTable

| Check | Measure | Primary p | Check p | Check statistic | Conclusion holds |
| --- | --- | --- | --- | --- | --- |
| Kruskal-Wallis in place of Welch F | Customer satisfaction | 0.521 | 0.644 | 0.21 | Yes |
| Kruskal-Wallis in place of Welch F | Engagement indicator mean | 0.940 | 0.897 | 1.63 | Yes |
| Kruskal-Wallis in place of Welch F | Intent to leave | 0.871 | 0.764 | 2.58 | Yes |
| Active engagements only | Engagement indicator mean | 0.940 | 0.595 | 0.29 | Yes |
| Active engagements only | Intent to leave | 0.871 | 0.622 | 0.25 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Cancellation rate | 0.792 | 0.784 | 0.49 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Customer satisfaction | 0.521 | 0.809 | 0.46 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Engagement indicator mean | 0.940 | 0.741 | 0.55 | Yes |
| Respondent level, cluster-robust Wald F by engagement | Intent to leave | 0.871 | 0.647 | 0.67 | Yes |

All nine checks held. A check holds when its test falls on the same side of 0.05 as the primary test. The respondent-level test, with standard errors clustered by engagement, found no difference for any of the four measures (p from 0.647 to 0.809).

## Measure Independence and Part-Whole Correction

Each of the four measures was computed from data the indicator does not contain. Each result is therefore a finding and not an arithmetic consequence.

## Comparison with the Study Norm

A categorical indicator has no signed correlation with the study measures and therefore no profile against the study norm.

## Comparison of Written Sentiment with Other Part 4 Indicators

Figure 4. Share of negative written responses, indicators of Part 4 with 30 or more written responses (n = 11 indicators)ExhibitNote: Each column is one indicator, ordered from the highest share of negative responses. The indicator is the amber column. The dashed line marks the median share, 33.33%.

Among the 11 indicators of Part 4 with 30 or more written responses, the indicator's share of negative responses, 51.35%, ranked 5 of 11 from the highest, against a median of 33.33%. Its mean written score (−0.8, n = 37 responses) ranked 5 of 11 from the most negative, against a median of 0.8 across the 11 indicators.

## Co-Occurring Indicators and Themes

Figure 5. Other indicators and themes in the same written responses (n = 37 responses)ExhibitNote: Themes carry no score. Labels give the count and the share of the 37 responses. The figure shows each indicator and each theme among the five most frequent of its kind, with every tie at the cut. The questions of the indicators shown are quoted in the text where they lead. Emotional states in the same responses, as counts: angry 1, calm or fine 1, tired 1.

The indicator most often present in the same responses was C123, on the adequacy of the employer's investment in training its workforce, in 21 of the 37 responses (56.76%), followed by C124, on how well the employer's training programs build practical agentic AI skills, in 10. The most frequent theme was “Skills learned” (9 responses), every one a response to C030.

## Interpretation of the Data

Respondents named six sources of their AI knowledge in almost equal numbers, and the source did not separate engagements on cancellation, customer satisfaction, the engagement indicator mean or intent to leave. Two of these results were equivalent to zero, and every robustness check held.

The written responses describe a different picture from the answer itself. Individual contributors who wrote said they learned the agents on live work, from colleagues and from outside material, after training of slides and videos, and that often no one above them knew the agents. The answers record where knowledge was said to come from, and the written responses record how thin the formal route was for those who wrote.

## Limitations

The evidence is the reported experience of the vendor's delivery teams, collected in a single cross-section. The associations reported here are not causal.

The respondent gave one source. Most people learn from several, so the answer records the source the respondent judged most important.

Customer satisfaction was tested on 22 active engagements, a small base.

Shares of written sentiment are shares of responses and not of the study set of respondents. The written score takes five fixed values, so its mean and median are coarse. Responses clustered within engagements (37 responses on 33 engagements), and intervals for written sentiment therefore used a bootstrap by engagement. In the sample read by a second reader, the two readers agreed on the presence of the indicator in 5 of the 5 responses either reader marked, and on the score in 2 of the 3 responses both readers scored.

## Definitions

Table 23. DefinitionsTable

| Term | Definition |
| --- | --- |
| Response scale | The answer is one of the listed sources of AI knowledge shown in the indicator specification. The indicator is not a rating. No distressed range applies. |
| Answering base | Respondents who gave one of the listed answers. |
| Non-answers | “I do not know” and “I prefer to not answer” are counted separately. They are excluded from the answering base and from the shares. |
| Indicator class | Respondent level: a property of the respondent rather than of the engagement. |
| Failure category | The five failure categories of the Study Taxonomy apply only to the rated indicators. The indicator carries none. |
| Assigned answer | The answer given by the largest number of an engagement's respondents. A tied engagement carries no assigned answer. |
| Written response | A written answer about the respondent's own engagement that addresses the indicator. Non-answers and answers about another engagement are excluded. |
| Primary and secondary | A primary response answered the written-answer question of the indicator's survey section. A secondary response answered a question in another section and addressed the indicator in its content. |
| Written sentiment score | a |
| Clustered test | A test whose standard error allows for the answers of respondents on the same engagement to be alike. |
| Cluster bootstrap | An interval computed by resampling engagements rather than responses, so that the responses from one engagement stay together. |

Note: a Each written response carries one of five scores: −10, −5, neutral, +5 or +10. The sign records whether the response described an effect on the engagement or on the respondent as harmful or helpful. The magnitude records its strength, and −10 marks a statement of totality, constancy or serious harm. A source of knowledge has no favorable or unfavorable value. Its score therefore records the effect the respondent associated with the way the respondent learned.

## Sources and Provenance

Table 24. Sources and provenanceTable

| Source | Value |
| --- | --- |
| Study data | Study Data.xlsx, Data sheet, column C017, sha256 219eba0457274d04 |
| Statistics engine | compute_statistics.py, sha256 738319eef764602b |
| Statistics record | Computed Statistics.json, record C017, sha256 1ae50a3637fc9370 |
| Computed | October 13, 2026, 04:57 UTC |
| Template | Indicator Template v2, version 2.0 of 10 October 2026 |
| Figures placed by script | 1,312 |
| Written responses | Quotes Master.jsonl, sha256 27da38085e2b13fd |
| Written sentiment scores | Quote Coding Rulebook, version 0.6, with section 21 |
| Written-response computation | qa_stats.py, sha256 74a61f3a96169da9. wfacts.py, sha256 b85fae20adf812a1. build_indicator.py, sha256 c7b10c57927ea734 |
| Written-response records | C017.qa.json, sha256 d53aa9cdead03ab3. C017.wfacts.json, sha256 e7086be208210ba8. Hand-written text handcraft/C017.json, sha256 0fd7726fda3b5a32 |


## Links to related study evidence

- [Part 4](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/part-4-delivery-workforce/)
- [Customer satisfaction](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-1-measure-customer-satisfaction/)
- [Engagement indicator mean](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-1-measure-engagement-indicator-mean/)
- [Intent to leave](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-4-c019/)
- [C019](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-4-c019/)
- [C123](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-2-c123/)
- [C124](https://akholi.com/outsourcing-2026-agentic-ai-tier-1-banks/study-data/part-2-c124/)