Rate your employer's readiness to take accountability when an agent it operates makes a costly error

The mean rating was 3.7 and the median 4.0 (n = 794 respondents). Ratings of 3 or below, the distressed range, made up 46.98% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.59, 95% CI −0.68 to −0.47, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.67, 95% CI 0.54 to 0.77, p < 0.001, n = 94 engagements), a higher engagement indicator mean computed without the indicator (r = 0.87, 95% CI 0.82 to 0.90, p < 0.001, n = 150 engagements) and lower intent to leave (r = −0.62, cluster bootstrap 95% CI −0.69 to −0.54, p < 0.001 with standard errors clustered by engagement, n = 744 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 29.99, Holm p < 0.001, omega squared 0.336) and respondent role (Welch F 8.76, Holm p = 0.002, omega squared 0.019).

Of the 38 written responses, nearly all from C135, 29 were negative and 8 positive. The negative responses described agent errors that no one above the delivery team would own, so that they landed on the analyst on shift. The positive responses described a lead or the vendor's side taking the error without passing it down. A more negative written score came with higher intent to leave.

Ratings of 3 or below, the distressed range, accounted for 373 of the 794 answers (46.98%). The engagement mean fell in the distressed range in 63 of 150 engagements.

The primary responses numbered 35, all written in answer to C135, “Add any comments on your employer that the ratings in this section do not capture.” The remaining 3 responses, 7.89% of the total, were secondary and came from 2 other questions. That secondary share ranked 48th from the highest among the 71 Part 2 indicators with 30 or more written responses, against a median of 18.92%. Respondents who wrote both a primary and a secondary response numbered 0. Negative responses made up 77.14% of primary responses (27 of 35) and 2 of the 3 secondary responses.

Fourteen responses said that no one above the respondent owned an agent's error, that the question of who pays went unanswered, or that ownership took weeks to settle. Respondents asked who would carry the cost of a bad deployment and were offered a workshop. When an assistant gave a wrong leave-accrual answer to dozens of new hires, no one could say who signed off the correction. After a summary missed an indemnity cap, leadership was silent for nearly two weeks, and the respondent judged that the silence did more damage than the error.

Eleven responses said the error landed on the individual: the analyst's name on the ticket or the case file, the ticket returned to the analyst's queue, the analyst on shift at two in the morning. One respondent said that when the agent closed a real intrusion alert as noise, no one above put a name to it, and the weight fell on whoever was on shift. Another team kept a private checklist before releasing files because no one had said who answers for a misrated one.

The eight positive responses described a lead, leadership or the vendor's side taking the error without passing it down: a lead who took the hit when a batch was routed wrong, a team that owned a duplicate payment with the financial institution without argument. Most of these placed accountability with the immediate lead.

Of the 38 responses, 29 (76.32%, 95% CI 61.76% to 89.19%) were negative and 19 (50.00%) carried the strongest negative score of −10. Positive responses numbered 8 (21.05%), and 1 was neutral. The mean written score was −5.0 (95% CI −7.0 to −2.8, n = 38 responses), and the median was −7.5.

Of the 38 responses, 38 came from respondents who also rated the indicator. Among them, the written score rose with the rating (Spearman rho 0.55, 95% CI 0.24 to 0.77, p < 0.001, n = 38 responses). The written responses corroborated the rating. Of the 29 negative responses with a rating, 20 (68.97%) came from respondents whose rating was in the distressed range.

Respondents who wrote about the indicator and gave a rating numbered 38, with a mean rating of 3.2. The 756 respondents who rated the indicator without writing about it had a mean of 3.7. The difference, −0.5 (95% CI −1.2 to 0.3), included zero. Ratings in the distressed range made up 55.26% of the ratings from respondents who wrote (21 of 38) and 46.56% of the ratings from respondents who did not (352 of 756).

Every figure in the segment tables is at respondent level. Segments with fewer than 30 respondents carry no interval. Segments with fewer than 10 report counts only.

Segment families recorded at engagement level were tested on engagement means. Respondent role and vendor type were tested on respondents. Where an expected count fell below 5, the test of the distressed share used Fisher's exact test for a two-by-two table, marked exact, or a Monte Carlo test, marked simulated. After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 29.99, Holm p < 0.001, omega squared 0.336). Active engagements in Production rated highest (mean 4.6, n = 95 respondents) and canceled engagements lowest (mean 2.4, n = 307 respondents). Ratings also differed by respondent role (Welch F 8.76, Holm p = 0.002, omega squared 0.019). Portfolio directors rated highest (mean 4.7, n = 31 respondents) and individual contributors lowest (mean 3.5, n = 611 respondents). Outsourcing model, institution type, process family, class of work and vendor type showed no difference.

Written sentiment did not differ by engagement status and lifecycle stage across the 32 engagements with a written response (Kruskal-Wallis H 2.76, df 3, p = 0.431). Fewer than two groups held 10 or more responses, so the groups are reported as counts only: active engagements in Build-Out (6), active engagements in Transition/Cut-Over (18), active engagements in Production (5) and canceled engagements (9).

No test across respondent roles was run, because fewer than two roles had 30 or more written responses. Individual contributors wrote 26, engagement managers wrote 11 and portfolio directors wrote 1 responses, reported as counts only.

Cancellation rate is the share of engagements canceled by the study date, measured at engagement level (150 engagements, 56 canceled). Canceled engagements were rated after cancellation. The association is therefore a descriptive contrast and not a forecast of cancellation.

Across the study set, higher ratings came with less cancellation (r = −0.59, 95% CI −0.68 to −0.47, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in eleven of the 20 segment levels tested.

Customer satisfaction is the percentage recorded against each engagement. The primary estimate uses the 94 active engagements. A descriptive contrast uses all 150 engagements.

Across the active engagements, higher ratings came with higher customer satisfaction (r = 0.67, 95% CI 0.54 to 0.77, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in fourteen of the 16 segment levels tested.

The engagement indicator mean is the mean of an engagement's ratings across the rated indicators, measured at engagement level (150 engagements). The indicator is one of the rated indicators. Each comparison therefore uses the mean recomputed without it.

Higher ratings came with a higher engagement indicator mean (r = 0.87, 95% CI 0.82 to 0.90, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in twenty-four of the 24 segment levels tested.

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. It is measured at respondent level on up to 798 respondents, with the engagement-level form reported alongside.

Respondents who gave higher ratings reported lower intent to leave (r = −0.62, 95% CI −0.66 to −0.57, Holm p < 0.001, n = 744 respondents). The association held after Holm correction in thirty-six of the 37 segment levels tested.

Two comparisons set the engagements with at least one negative response against all other engagements. Of the 126 other engagements, 118 had no written response addressing the indicator. These two comparisons therefore do not isolate written sentiment. Of the 24 engagements with a negative response, 7 (29.17%) were canceled, against 49 of the 126 other engagements (38.89%). The difference did not reach significance (Fisher exact p = 0.491). Customer satisfaction among active engagements did not differ between the two groups (mean 62.12% on 17 engagements against 64.53% on 77, Welch t −0.87, p = 0.390).

Two correlations test written sentiment directly. Across the 32 engagements with a written response, the engagement mean written score was not associated with cancellation (point-biserial r −0.23, p = 0.210). Across 37 respondents, a more negative respondent mean written score came with higher intent to leave (Spearman rho −0.35, p = 0.032). Of the four comparisons, one reached significance at 0.05.

The four associations were compared in pairs on their engagement-level forms, each oriented so that a higher value is the better outcome, across the 150 engagements with all four measures. After Holm correction, five of the six pairs differed. The association with the engagement indicator mean was the strongest and the association with cancellation the weakest. The associations with customer satisfaction and intent to leave did not differ (Holm p = 0.514).

Answers clustered within engagements (ICC 0.63). Clustering reduced the 794 respondent answers to the equivalent of about 215 independent answers. Respondent-level intervals therefore used the cluster bootstrap. Respondent-level tests of intent to leave used standard errors that allow for clustering by engagement.

No association was equivalent to zero. Each of the four differed from zero. The detection floor shown is the study floor at 150 engagements. Intent to leave was tested on its effective sample size.

Each change was computed before rounding and may differ by 0.01 from the difference between the two printed values.

All 22 checks held. A check holds when its test falls on the same side of 0.05 as the primary test. Where the primary test falls below 0.05, the check must also keep the sign of the primary correlation. The thin-base check removes the engagements in any level of outsourcing model or process family with fewer than 30 engagements. Institution type is not used for that check, because every one of its levels has fewer than 30 engagements.

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. The indicator is one of the rated indicators, and the engagement indicator mean was recomputed without it. The correction changed r by 0.00, from 0.87 to 0.87.

Each deviation was computed before rounding and may differ by 0.01 from the difference between the two printed values.

The comparison covered 150 engagements. The indicator followed the study's typical pattern on all four measures, and no deviation held after Holm correction.

Among the 71 Part 2 indicators with 30 or more written responses, the indicator's share of negative responses, 76.32%, ranked 47th from the highest, against a median of 80.82%. Its mean written score, −5.0, ranked 30th from the most negative, against a median of −4.7.

The indicator most often present in the same responses was C157, “Rate the factual reliability of the AI tools' outputs on this engagement before any human review.”, in 20 of the 38 responses (52.63%). C123, “Rate the adequacy of your employer's investment in training its workforce.” (9 responses), C122, “Rate your employer's current supply of qualified agentic AI talent against what its engagements need.” (7 responses), C125, “Rate how well your employer's training programs build financial industry knowledge.” (5 responses) and C115, “Rate the overall effectiveness of your employer's top leadership team.” (4 responses) followed.

The most frequent theme was “Liability or regulatory accountability unclear”, in 7 responses (18.42%). The second was “Raised it, nothing came back”, in 6 responses.

Nearly half of all ratings of the employer's readiness to take accountability when an agent makes a costly error fell in the distressed range (373 of 794 answers, 46.98%). The rating was associated with all four study measures, and every association held under each of the 22 robustness checks. Canceled engagements rated far below the three active stages (mean 2.4, n = 307 respondents).

The written evidence places accountability for agent errors at the lowest level of the delivery team. Where a lead accepted the error, respondents rated the employer well. Where no one above did, the analyst on shift carried it. Written sentiment was associated with intent to leave.

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.

Tests by respondent role and by vendor type treated respondents as independent. The section on clustering reports how far clustering within engagements reduced the information in respondent-level figures.

Customer management executives gave 2 answers, a base of anecdote strength.

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 (38 responses on 32 engagements). Intervals for written sentiment therefore used a bootstrap by engagement.