Rate the integrity of the tools' persistent memory against contamination by incorrect or malicious content encountered during work

The mean rating was 4.6 and the median 4.0 (n = 806 respondents). Ratings of 3 or below, the distressed range, made up 31.89% of the answers. The rating was associated with all four study measures. Higher ratings came with less cancellation (r = −0.68, 95% CI −0.76 to −0.58, p < 0.001, n = 150 engagements), higher customer satisfaction among active engagements (r = 0.64, 95% CI 0.51 to 0.75, 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 = −0.65, cluster bootstrap 95% CI −0.71 to −0.59, p < 0.001 with standard errors clustered by engagement, n = 760 respondents). After Holm correction, ratings differed by engagement status and lifecycle stage (Welch F 56.27, Holm p < 0.001, omega squared 0.453), respondent role (Welch F 5.69, Holm p = 0.030, omega squared 0.010) and vendor type (Welch F 3.40, Holm p = 0.030, omega squared 0.015).

Nine written responses addressed the indicator, all from C177, the comment field on the AI tools. Eight were negative and none positive. The negative responses described wrong content that the tool stored and reused in later work until a person noticed and cleared it.

Ratings of 3 or below, the distressed range, accounted for 257 of the 806 answers (31.89%). The engagement mean fell in the distressed range in 32 of 150 engagements.

The nine responses were primary. Each answered C177, “Add any comments on the agentic AI tools that the ratings in this section do not capture.” No response from any other question addressed the indicator.

Eight responses described wrong content kept by the tool and reused. A bad line in one custodian statement shaped the reading of the next file. A wrong routing, once learned, was repeated with confidence. Last month's exception rule was carried into a new cycle twice without anyone seeing it. A wrong refund window taken from an old merchant note stayed in use for weeks until a staff member, not the system, found it. An answer from an earlier due diligence questionnaire was reused for a different fund, and a wrong expected result was carried across three test suites.

Two responses described clearing the memory or opening a new session for every batch, and one respondent said nobody could explain what else was lost when the memory was cleared. Two described a manual check of about two extra hours added to every day. One of these respondents said the checking had contributed to a senior colleague's departure. The neutral response said contamination could not be observed directly and surfaced only when a figure came out wrong.

One response carried the strongest negative score of −10, seven carried −5 and one was neutral. With fewer than 10 responses, the distribution is reported as counts only.

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 56.27, Holm p < 0.001, omega squared 0.453). Active engagements in Transition/Cut-Over rated highest (mean 5.5, n = 242 respondents) and canceled engagements lowest (mean 3.1, n = 305 respondents). Ratings also differed by respondent role (Welch F 5.69, Holm p = 0.030, omega squared 0.010). Portfolio directors rated highest (mean 5.3, n = 30 respondents) and individual contributors lowest (mean 4.4, n = 625 respondents). Ratings also differed by vendor type (Welch F 3.40, Holm p = 0.030, omega squared 0.015). Consulting firms rated highest (mean 5.1, n = 106 respondents) and BPO specialists lowest (mean 4.2, n = 190 respondents). Outsourcing model, institution type, process family and class of work showed no difference.

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 = −0.68, 95% CI −0.76 to −0.58, Holm p < 0.001, n = 150 engagements). The association held after Holm correction in fifteen 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 = 0.64, 95% CI 0.51 to 0.75, Holm p < 0.001, n = 94 engagements). The association held after Holm correction in ten 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 = −0.65, 95% CI −0.69 to −0.61, Holm p < 0.001, n = 760 respondents). The association held after Holm correction in thirty-seven of the 37 segment levels tested.

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 customer satisfaction the weakest. The associations with customer satisfaction and intent to leave did not differ (Holm p = 0.566).

Answers clustered within engagements (ICC 0.58). Clustering reduced the 806 respondent answers to the equivalent of about 227 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.

The responses also addressed twelve other indicators, most often C157, followed by C160, C161 and C165. The most frequent theme was a failure that recurs every cycle or most days.

About a third of all ratings of the integrity of the tools' persistent memory fell in the distressed range (257 of 806 answers, 31.89%). 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 3.1, n = 305 respondents).

Written responses were voluntary. They recorded what the respondents who wrote reported, and how common it was is measured by the ratings. The few respondents who wrote described a failure that persists silently, is found by a person rather than by the system, and is remedied by discarding memory wholesale. The written evidence rests on nine responses, a base of anecdote strength.

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 1 answers, a base of anecdote strength.

Counts of written responses describe the respondents who wrote and not the study set of respondents. With nine responses, the written evidence supports counts only and no statistic.