The customer is scaling their agentic AI outsourcing engagements

Ratings of whether the financial institution was scaling its agentic AI outsourcing engagements (mean 5.5, median 5.0, n = 364 respondents) showed no association with any of the four study measures. The association with cancellation was equivalent to zero (TOST p < 0.001). Customer satisfaction on active engagements was also equivalent to zero (TOST p 0.003). The engagement indicator mean showed the same tested null (TOST p 0.001). Intent to leave was equivalent to zero as well (TOST p < 0.001). No segment family differed in these ratings after Holm control (Holm p 0.876 or higher in every family).

One written response was coded to the indicator, from 1 of 850 respondents on 1 of 150 engagements. The single scored response was positive, with a score of +5. It was a secondary response, written in answer to a question outside the indicator’s own survey section. The rating of respondents who wrote was not compared with that of respondents who did not, because one respondent wrote.

The study set mean was 5.5 on 364 answering respondents, with a median of 5.0.

The single response coded to the indicator was a secondary response. The response was written in answer to C030, a question outside the indicator’s own survey section.

The indicator has no good or bad end. Under the coding rulebook’s rule for such indicators, the written score records the effect each response states on the engagement or on the respondent. The survey question is “The customer is scaling their agentic AI outsourcing engagements.” The frequency, scope and consequence a response states set the strength of its score. A score of +10 marks a response that describes “this direction of the financial institution as helping the engagement at its best.” A score of −10 marks a response that describes “[this direction of the financial institution] as harming the engagement at its worst.”

The distribution was reported as counts only, because fewer than 10 responses carried a score. The single scored response carried a score of +5.

Figures are respondent level. Means are on the scale as recorded. A level under 30 prints no interval and a level under 10 prints counts only.

Engagement families were tested on engagement means, and respondent role and vendor type were tested on respondents. A distressed p marked exact is a Fisher exact test for a two by two table, and one marked simulated is a Monte Carlo test run until its p is stable to the third decimal, both used where an expected count is under 5. No difference held after Holm control for outsourcing model, institution type, process family, class of work, engagement status and lifecycle stage, respondent role and vendor type.

The share of engagements canceled on the study date, measured at engagement level (base 150 engagements, 56 canceled). The association is a descriptive contrast, inflated because canceled engagements were rated after cancellation, and is not predictive.

The study set r was −0.04 (95% CI −0.20 to 0.12, Holm p 1.000, n = 150 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 20 tested segment levels, 0 held after Holm control.

The satisfaction score recorded against each engagement on a 100-point scale. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

The study set r was 0.02 (95% CI −0.18 to 0.22, Holm p 1.000, n = 94 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 16 tested segment levels, 0 held after Holm control.

The mean of an engagement’s 100 indicator ratings, measured at engagement level (base 150 engagements). Where this indicator is one of the 100, the mean is recomputed without it.

The study set r was 0.06 (95% CI −0.10 to 0.22, Holm p 1.000, n = 150 engagements). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 24 tested segment levels, 0 held after Holm control.

The respondent’s stated likelihood of leaving the current job within 12 months, rated 1 to 10 (C019). Measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

The study set r was 0.00 (95% CI −0.10 to 0.11, Holm p 1.000, n = 352 respondents). The association did not hold after Holm control. Equivalence Tests of Null Results found it equivalent to zero inside the bound. Of the 37 tested segment levels, 0 held after Holm control.

Pairs were compared on the engagement level form of every measure, each turned so that a higher value was the better outcome, on the 150 engagements where the indicator and all four measures existed. Of the 6 pairs, 0 differed after Holm control.

Clustering within engagements did not reduce the 364 respondent answers, so the effective n equaled the nominal n.

Tested null, equivalent to zero: cancellation rate, customer satisfaction, engagement indicator mean and intent to leave. No result was inconclusive. The detection floor column is the study floor at 150 engagements. Intent to leave was tested on its effective n.

Each change was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

Every check held. A check holds when its test lands on the same side of 0.05 as the primary test and, where the primary test is below 0.05, its r keeps the primary sign. Thin-base rule: engagements in any level under 30 engagements of outsourcing model or process family removed. Institution type is not used, because every one of its levels is under 30.

Each of the four measures was computed from data this indicator does not contain, so each result is a finding rather than an arithmetic consequence.

Each deviation was computed before rounding, so it can differ by 0.01 from the difference of the two printed values.

The comparison ran on 150 engagements. The indicator departed from the study’s typical pattern on cancellation rate, customer satisfaction, engagement indicator mean and intent to leave.

The response coded to the indicator was also coded to “How happy are you with your current job?” (C018, 1 response) and “My manager cares about the larger team” (C084, 1 response).

Every robustness check run on this item held (22 of 22 checks). How far the financial institution was scaling showed no association with cancellation, customer satisfaction, the engagement indicator mean, or intent to leave.

The written responses were not set against the rating, because fewer than 10 responses carried a score. Written responses were voluntary. They recorded what the respondents who wrote reported, and how common it was is measured by the ratings. The analysis of the written responses rested on 1 response, a base of anecdote strength.

The evidence is reported experience: what the delivery team said about its own engagement, gathered in one cross-section. The figures showed associations, not causes. Indicators about the financial institution were reported at second hand by vendor staff. Cancellation is a descriptive contrast, because canceled engagements were rated after they ended.

Tests across respondent role and vendor type were run at respondent level and treated respondents as independent. The section Clustering and Effective Sample Size states whether, and by how much, clustering within engagements reduced the information in respondent level figures.

Customer Management Executive answers were at anecdote strength (n = 2).

Fewer than 10 responses carried a score, so written sentiment was reported as counts, with no statistic. Coding was performed by AI coders under a fixed rulebook. No response coded to the indicator fell in the sample second-coded under rulebook 0.5, so agreement on whether a response was coded to the indicator could not be assessed. No response coded to the indicator was second-scored under rulebook 0.6, so agreement on the score could not be assessed.