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Programme snapshot
Programme · all cohorts
16
Cohorts run
64
Organisations
745
D1 sessions · all cohorts
Respondents
Programme NPS
+42
weighted aggregate
NPS
53%
Promoters
36%
Passives
11%
Detractors
D2 Confidence means /5
4.16
all cohorts
Apply / Lead
4.17
v1 + v2
Advise clients
4.11
v2 only
Design eval
Respondent function
EngineeringArchitectureBusiness LeadershipProject / Engmt
35%
24%
15%
25%
San Francisco
9 cohorts · C7, C8, C11, C12, C15, C18, C19, C20, C21
+44NPS↓ Latest -20 vs avg
n=417 D2 respondents
London
7 cohorts · C6, C9, C13, C14, C16, C22, C23
+37NPS↑ Latest ++10 vs avg
n=148 D2 respondents
Cohort detail
C6 London · v2
May 18–19, 2026
+43
NPS
Avg score 8.3/10
57% Prom · 29% Pass · 14% Det
n=21 · D2 rate 54%
C7 San Francisco · v2
May 19-20, 2026
+32
NPS
Avg score 8.3/10
53% Prom · 25% Pass · 22% Det
n=60 · D2 rate 92%
C8 San Francisco · v2
May 20-21, 2026
+43
NPS
Avg score 8.6/10
54% Prom · 35% Pass · 11% Det
n=37 · D2 rate 77%
C9 London · v2
May 20-21, 2026
+38
NPS
Avg score 8.3/10
46% Prom · 46% Pass · 8% Det
n=24 · D2 rate 44%
C11 San Francisco · v2
May 26-27, 2026
+73
NPS
Avg score 9.1/10
73% Prom · 27% Pass · 0% Det
n=41 · D2 rate 84%
C12 San Francisco · v2
May 28-29, 2026
+50
NPS
Avg score 8.5/10
58% Prom · 34% Pass · 8% Det
n=50 · D2 rate 75%
C13 London · v2
June 2-3, 2026
+40
NPS
Avg score 8.5/10
40% Prom · 60% Pass · 0% Det
n=15 · D2 rate 79%
C14 London · v2
June 4-5, 2026
+39
NPS
Avg score 8.5/10
50% Prom · 39% Pass · 11% Det
n=18 · D2 rate 106%
C15 San Francisco · v2
June 16-17
+55
NPS
Avg score 8.8/10
64% Prom · 27% Pass · 9% Det
n=33 · D2 rate 48%
C16 London · v2
June 15-16, 2026
+17
NPS
Avg score 7.8/10
39% Prom · 39% Pass · 22% Det
n=23 · D2 rate 64%
C18 San Francisco · v2
June 22–23, 2026
+35
NPS
Avg score 8.1/10
49% Prom · 38% Pass · 14% Det
n=37 · D2 rate 82%
C19 San Francisco · v2
June 24–25, 2026
+55
NPS
Avg score 8.6/10
64% Prom · 26% Pass · 10% Det
n=62 · D2 rate 92%
C20 San Francisco · v2
July 14–15, 2026
+35
NPS
Avg score 8.4/10
46% Prom · 44% Pass · 10% Det
n=48 · D2 rate 104%
C21 San Francisco · v2
July 16–17, 2026
+24
NPS
Avg score 7.9/10
39% Prom · 47% Pass · 14% Det
n=49 · D2 rate 91%
C22 London · v2
July 20–21, 2026
+41
NPS
Avg score 8.3/10
44% Prom · 53% Pass · 3% Det
n=32 · D2 rate 58%
C23 London · v2
July 22–23, 2026
+47
NPS
Avg score 8.7/10
47% Prom · 53% Pass · 0% Det
n=15 · D2 rate 107%
NPS direction
Trend over time · dot position shows direction · hover for score and CI
Dashed line = programme average · error bars show 95% confidence interval · bar height reflects cohort size — shorter = more respondents · hover for detail

Scores have remained broadly stable across 16 cohorts. The most recent cohort (C23 LDN) scored NPS +47 — +5 points above the programme average (+42).

0 +30 +50 Avg +42 C6 LDN: NPS +43 · n=2195% CI: +12 → +74 C6 LDN May 18–19, 2026 C7 S.F.: NPS +32 · n=6095% CI: +11 → +52 C7 S.F. May 19-20, 2026 C8 S.F.: NPS +43 · n=3795% CI: +21 → +65 C8 S.F. May 20-21, 2026 C9 LDN: NPS +38 · n=2495% CI: +12 → +63 C9 LDN May 20-21, 2026 C11 S.F.: NPS +73 · n=4195% CI: +60 → +87 C11 S.F. May 26-27, 2026 C12 S.F.: NPS +50 · n=5095% CI: +32 → +68 C12 S.F. May 28-29, 2026 C13 LDN: NPS +40 · n=1595% CI: +15 → +65 C13 LDN June 2-3, 2026 C14 LDN: NPS +39 · n=1895% CI: +8 → +70 C14 LDN June 4-5, 2026 C15 S.F.: NPS +55 · n=3395% CI: +32 → +77 C15 S.F. June 16-17 C16 LDN: NPS +17 · n=2395% CI: -14 → +48 C16 LDN June 15-16, 2026 C18 S.F.: NPS +35 · n=3795% CI: +12 → +58 C18 S.F. June 22–23, 2026 C19 S.F.: NPS +55 · n=6295% CI: +38 → +71 C19 S.F. June 24–25, 2026 C20 S.F.: NPS +35 · n=4895% CI: +17 → +54 C20 S.F. July 14–15, 2026 C21 S.F.: NPS +24 · n=4995% CI: +5 → +44 C21 S.F. July 16–17, 2026 C22 LDN: NPS +41 · n=3295% CI: +22 → +60 C22 LDN July 20–21, 2026 C23 LDN: NPS +47 · n=1595% CI: +22 → +72 C23 LDN July 22–23, 2026

Confidence intervals acknowledge that each cohort NPS is a measure of respondents, not all participants. The bar at each cohort shows the range within which the true NPS most likely sits — shorter bars reflect larger cohorts, where more responses produce a tighter estimate.

Function: v1 cohorts estimated from role type · marked (est.) · seniority and experience from v2 cohorts only

Function & seniority
Primary function · all cohorts + recent
Top bar = all cohorts aggregate · v1 estimated from role type
EngineeringArchitectureBusiness LeadershipProject / Engmt
All cohorts (includes est. v1)n=745
35%
24%
15%
25%
C20 San Franciscon=46
26%
30%
20%
24%
C21 San Franciscon=54
44%
22%
9%
24%
C22 Londonn=55
36%
27%
16%
20%
C23 Londonn=14
29%
21%
29%
21%
Level / seniority · v2 cohorts only
Sr PractitionerPractitionerManager / Sr ManagerDirector / Sr DirectorPartner / MD / Exec
All cohortsn=745
21%
25%
30%
18%
C20 San Franciscon=46
11%
11%
33%
30%
15%
C21 San Franciscon=54
19%
43%
13%
22%
C22 Londonn=55
15%
25%
44%
15%
C23 Londonn=14
29%
50%
21%
Experience profile · v2 cohorts only
AI tools experience prior to programme
Learning & exploringApplying in practiceDelivering independentlyOperating at the frontier
All cohortsn=745
21%
46%
20%
13%
C20 San Franciscon=46
24%
46%
20%
11%
C21 San Franciscon=54
22%
35%
24%
19%
C22 Londonn=55
20%
55%
9%
16%
C23 Londonn=14
43%
36%
21%
Prior exposure to Claude or Anthropic API
Not at allA littleRegularly
All cohortsn=745
8%
44%
47%
C20 San Franciscon=46
41%
52%
C21 San Franciscon=54
33%
61%
C22 Londonn=55
9%
49%
42%
C23 Londonn=14
29%
43%
29%
Composition over time · v2 cohorts
Proficiency and persona mix per cohort
Descriptive only — shifts reflect partner nomination decisions

% of D1 respondents per cohort · v2 cohorts only · descriptive — shifts reflect partner nomination decisions

Proficiency level over time
Frontier
20%C66%C719%C824%C98%C1119%C125%C1312%C149%C153%C162%C1819%C1911%C2018%C2116%C220%C2360%
Independent
20%C622%C723%C824%C914%C1122%C1221%C1341%C1417%C1528%C1618%C1815%C1920%C2024%C219%C2221%C2360%
Applying
41%C658%C738%C838%C951%C1133%C1253%C1335%C1456%C1544%C1651%C1848%C1946%C2035%C2154%C2236%C2360%
Learning
18%C614%C721%C814%C926%C1125%C1221%C1312%C1417%C1525%C1629%C1818%C1924%C2022%C2120%C2243%C2360%
Persona mix over time
Architect
33%C618%C721%C831%C918%C1121%C125%C1335%C1423%C1528%C1622%C1827%C1930%C2022%C2127%C2221%C2380%
Developer
36%C632%C725%C846%C920%C1146%C1274%C1335%C1433%C1528%C1620%C1839%C1926%C2044%C2136%C2229%C2380%
Transformation Lead
31%C649%C754%C824%C961%C1133%C1221%C1329%C1444%C1544%C1658%C1834%C1944%C2033%C2136%C2250%C2380%

Transformation Lead aggregates the survey's Business Leadership and Project / Engagement Management function categories.

Relevance & confidence baseline
How relevant was today's content to your role? (mean /5)
Top bar = programme average · recent cohorts below
Programme avg
4.09/5
C23 London
4.36/5
C22 London
4.16/5
C21 San Francisco
4.02/5
C20 San Francisco
4.15/5
Day 1 confidence baseline (mean /5)
Top bar = programme average · recent cohorts below
Programme avg
3.91/5
C23 London
3.67/5
C22 London
3.83/5
C21 San Francisco
3.96/5
C20 San Francisco
3.76/5
Session quality
Technical depth · all cohorts
Top row = all cohorts · recent cohorts below
Too basicAbout rightToo advanced
CohortToo basicAbout rightToo advanced
All cohorts16%76%8%
C20 San Francisco15%63%22%
C21 San Francisco28%63%9%
C22 London7%87%5%
C23 London93%7%
Pace · all cohorts
Top row = all cohorts · recent cohorts below
Too slowWell pacedToo fast
CohortToo slowWell pacedToo fast
All cohorts7%80%13%
C20 San Francisco7%85%9%
C21 San Francisco19%61%20%
C22 London5%62%33%
C23 London86%14%
NPS direction
Score trend · dot position shows direction · hover for score and CI
Dashed line = programme average · error bars show 95% confidence interval · bar height reflects cohort size — shorter = more respondents · hover for detail

Scores have remained broadly stable across 16 cohorts. The most recent cohort (C23 LDN) scored NPS +47 — +5 points above the programme average (+42).

0 +30 +50 Avg +42 C6 LDN: NPS +43 · n=2195% CI: +12 → +74 C6 LDN May 18–19, 2026 C7 S.F.: NPS +32 · n=6095% CI: +11 → +52 C7 S.F. May 19-20, 2026 C8 S.F.: NPS +43 · n=3795% CI: +21 → +65 C8 S.F. May 20-21, 2026 C9 LDN: NPS +38 · n=2495% CI: +12 → +63 C9 LDN May 20-21, 2026 C11 S.F.: NPS +73 · n=4195% CI: +60 → +87 C11 S.F. May 26-27, 2026 C12 S.F.: NPS +50 · n=5095% CI: +32 → +68 C12 S.F. May 28-29, 2026 C13 LDN: NPS +40 · n=1595% CI: +15 → +65 C13 LDN June 2-3, 2026 C14 LDN: NPS +39 · n=1895% CI: +8 → +70 C14 LDN June 4-5, 2026 C15 S.F.: NPS +55 · n=3395% CI: +32 → +77 C15 S.F. June 16-17 C16 LDN: NPS +17 · n=2395% CI: -14 → +48 C16 LDN June 15-16, 2026 C18 S.F.: NPS +35 · n=3795% CI: +12 → +58 C18 S.F. June 22–23, 2026 C19 S.F.: NPS +55 · n=6295% CI: +38 → +71 C19 S.F. June 24–25, 2026 C20 S.F.: NPS +35 · n=4895% CI: +17 → +54 C20 S.F. July 14–15, 2026 C21 S.F.: NPS +24 · n=4995% CI: +5 → +44 C21 S.F. July 16–17, 2026 C22 LDN: NPS +41 · n=3295% CI: +22 → +60 C22 LDN July 20–21, 2026 C23 LDN: NPS +47 · n=1595% CI: +22 → +72 C23 LDN July 22–23, 2026

Confidence intervals acknowledge that each cohort NPS is a measure of respondents, not all participants. The bar at each cohort shows the range within which the true NPS most likely sits — shorter bars reflect larger cohorts, where more responses produce a tighter estimate.

Segment composition · Promoter / Passive / Detractor by cohort
Shows whether passives or detractors are shifting over time
PromotersPassivesDetractors
Programme avgn=565
53%
36%
11%
C6 London NPS +43n=21
57%
29%
14%
C7 San Francisco NPS +32n=60
53%
25%
22%
C8 San Francisco NPS +43n=37
54%
35%
11%
C9 London NPS +38n=24
46%
46%
8%
C11 San Francisco NPS +73n=41
73%
27%
C12 San Francisco NPS +50n=50
58%
34%
8%
C13 London NPS +40n=15
40%
60%
C14 London NPS +39n=18
50%
39%
11%
C15 San Francisco NPS +55n=33
64%
27%
9%
C16 London NPS +17n=23
39%
39%
22%
C18 San Francisco NPS +35n=37
49%
38%
14%
C19 San Francisco NPS +55n=62
64%
26%
10%
C20 San Francisco NPS +35n=48
46%
44%
10%
C21 San Francisco NPS +24n=49
39%
47%
14%
C22 London NPS +41n=32
44%
53%
C23 London NPS +47n=15
47%
53%
NPS by persona
Developer · Architect · Transformation Lead / Business
PersonaAppearancesPooled NPSP / Pa / D distributionBy cohort (v1 uses role-group proxy)
Developer15+44
53%P 38%Pa 9%D n=164
C11 San Francisco: +78C12 San Francisco: +44C13 London: +50C14 London: +80C15 San Francisco: +67C16 London: +50C18 San Francisco: +40C19 San Francisco: +56C20 San Francisco: +70C21 San Francisco: -6C22 London: +25C6 London: +22C7 San Francisco: +24C8 San Francisco: +62C9 London: +40
Architect13+52
59%P 34%Pa 7%D n=112
C11 San Francisco: +71C12 San Francisco: +62C14 London: +0C15 San Francisco: +14C18 San Francisco: +56C19 San Francisco: +59C20 San Francisco: +43C21 San Francisco: +50C22 London: +38C6 London: +67C7 San Francisco: +38C8 San Francisco: +88C9 London: +75
Transformation Lead / Business15+37
51%P 34%Pa 14%D n=200
C11 San Francisco: +73C12 San Francisco: +40C13 London: +0C14 London: +40C15 San Francisco: +69C16 London: -12C18 San Francisco: +19C19 San Francisco: +58C20 San Francisco: +17C21 San Francisco: +39C22 London: +50C6 London: +80C7 San Francisco: +25C8 San Francisco: +17C9 London: +29
NPS score distribution · v2 cohorts
Score breakdown 0–10 (cells show count · grows with each v2 cohort)
Cohort012345678910
C6 London123384
C7 San Francisco2563121022
C8 San Francisco476416
C9 London113847
C11 San Francisco56921
C12 San Francisco11298920
C13 London4515
C14 London21645
C15 San Francisco327912
C16 London1223645
C18 San Francisco111268513
C19 San Francisco246102020
C20 San Francisco14912715
C21 San Francisco11321310811
C22 London110768
C23 London2616
NPS by organisation · recurring
Organisations in ≥2 cohorts — aggregate and per-cohort NPS
OrganisationAppearancesAvg NPSBy cohort
Deloitte9+42C11 San Francisco: +82C12 San Francisco: +83C14 London: +0C16 London: +0C18 San Francisco: -20C19 San Francisco: +83C20 San Francisco: +44C7 San Francisco: +62C8 San Francisco: +47
PwC8+30C11 San Francisco: +62C15 San Francisco: +86C18 San Francisco: +60C19 San Francisco: +54C20 San Francisco: -11C21 San Francisco: +33C7 San Francisco: -45C8 San Francisco: +0
Accenture3+72C11 San Francisco: +75C7 San Francisco: +73C9 London: +67
Cognizant3+42C18 San Francisco: +50C19 San Francisco: +89C7 San Francisco: -14
Infosys2+26C15 San Francisco: +33C7 San Francisco: +20
KPMG2+6C12 San Francisco: +12C21 San Francisco: +0
Persistent Systems2+82C15 San Francisco: +83C20 San Francisco: +80
What respondents said
NPS verbatim responses by segment · v2 cohorts
Up to 3 most recent per segment · thematic synthesis in insights.py

459 total responses · showing up to 3 most recent per segment · thematic synthesis in insights.py

Promoter · 245 responses
"Perfect balance during all training"Score 10 · C23 London
"Great content"Score 10 · C23 London
"Really immersive experience, challenging, good learning curve"Score 10 · C23 London
Passive · 159 responses
"Environment issues meant that a number of objectives could not be achieved because we ran out of time."Score 7 · C23 London
"Depends on the technical level of the person"Score 8 · C23 London
"Learn a lot"Score 8 · C23 London
Detractor · 55 responses
"The covered topics were too basic. There should have been some engineer from Anthropic to cover advanced topics."Score 6 · C22 London
"Not differentiated by level of technical skill"Score 5 · C21 San Francisco
"It’s a bit too basic for us"Score 6 · C21 San Francisco

v1 cohorts include apply and client confidence metrics · three-way split and distributions from v2 only

D2 confidence means
Apply / Design / Commercial (mean /5 · Apply shows Δ vs D1 · top row = programme avg)
Apply / Lead conversation · v1 + v2
Programme avg
4.16
C23 London
4.20 (+0.53)
C22 London
4.22 (+0.39)
C21 San Francisco
4.18 (+0.22)
C20 San Francisco
4.02 (+0.26)
Advising clients on AI · v1 + v2
Programme avg
4.17
C23 London
4.33
C22 London
4.34
C21 San Francisco
4.10
C20 San Francisco
4.15
Design an evaluation · v2 only
Programme avg
4.11
C23 London
4.07
C22 London
4.09
C21 San Francisco
4.18
C20 San Francisco
4.06
Confidence trajectory D1 → D2 · v2 cohorts
Mean delta in build confidence by matched pairs
Developer
Programme avg
+0.07n=166
C23 London
+0.00n=2
C22 London
+0.38n=8
C21 San Francisco
-0.25n=16
C20 San Francisco
+0.20n=10
C19 San Francisco
+0.36n=25
C18 San Francisco
+0.60n=5
C16 London
-0.17n=6
C15 San Francisco
-0.08n=12
C14 London
+0.20n=5
C13 London
+0.12n=8
C12 San Francisco
+0.00n=16
C11 San Francisco
+0.00n=9
C9 London
+0.00n=10
C8 San Francisco
+0.12n=8
C7 San Francisco
-0.24n=17
C6 London
+0.22n=9
Architect
Programme avg
+0.28n=117
C23 London
+1.00n=1
C22 London
+0.50n=8
C21 San Francisco
-0.08n=12
C20 San Francisco
+0.14n=14
C19 San Francisco
+0.65n=17
C18 San Francisco
+0.22n=9
C16 London
+0.67n=3
C15 San Francisco
+0.00n=7
C14 London
+0.00n=4
C13 London
+0.00n=1
C12 San Francisco
+0.25n=8
C11 San Francisco
+0.14n=7
C9 London
+0.50n=4
C8 San Francisco
+0.50n=8
C7 San Francisco
+0.12n=8
C6 London
+0.33n=6
Transformation Lead
Programme avg
+0.39n=203
C23 London
+0.67n=3
C22 London
+0.25n=8
C21 San Francisco
+0.83n=18
C20 San Francisco
+0.22n=18
C19 San Francisco
+0.42n=19
C18 San Francisco
+0.25n=16
C16 London
+0.62n=8
C15 San Francisco
+0.62n=13
C14 London
+0.40n=5
C13 London
+0.75n=4
C12 San Francisco
-0.13n=15
C11 San Francisco
+0.77n=22
C9 London
+0.00n=7
C8 San Francisco
+0.33n=18
C7 San Francisco
+0.21n=24
C6 London
+0.20n=5
D2 confidence score distributions · v2 cohorts
1–5 distribution · cells show % of respondents
Row intensity indicates response concentration at each score.
Design an evaluation for an AI solution
Cohort12345Mean
All cohorts2%20%42%36%4.12
C6 London24%48%29%4.05
C7 San Francisco18%35%47%4.28
C8 San Francisco3%11%57%30%4.14
C9 London12%38%50%4.38
C11 San Francisco2%17%46%34%4.12
C12 San Francisco4%20%32%44%4.16
C13 London20%47%33%4.13
C14 London6%17%50%28%4.00
C15 San Francisco39%33%27%3.88
C16 London4%22%52%22%3.91
C18 San Francisco11%16%38%35%3.97
C19 San Francisco21%44%35%4.15
C20 San Francisco23%48%29%4.06
C21 San Francisco2%20%35%43%4.18
C22 London19%53%28%4.09
C23 London27%40%33%4.07
Advising clients on AI when questions arise
Cohort12345Mean
All cohorts0%1%17%45%36%4.17
C6 London14%52%33%4.19
C7 San Francisco15%42%43%4.28
C8 San Francisco16%49%35%4.19
C9 London17%50%33%4.17
C11 San Francisco2%15%44%39%4.20
C12 San Francisco2%2%20%32%44%4.14
C13 London7%53%40%4.33
C14 London6%11%56%28%4.06
C15 San Francisco21%52%27%4.06
C16 London26%52%22%3.96
C18 San Francisco22%43%35%4.14
C19 San Francisco2%13%53%32%4.16
C20 San Francisco21%44%35%4.15
C21 San Francisco2%24%35%39%4.10
C22 London9%47%44%4.34
C23 London7%53%40%4.33
Lead a conversation about Anthropic and Claude
Cohort12345Mean
All cohorts0%2%16%47%36%4.16
C6 London24%29%48%4.24
C7 San Francisco3%13%47%37%4.17
C8 San Francisco14%41%46%4.32
C9 London17%50%33%4.17
C11 San Francisco15%51%34%4.20
C12 San Francisco2%2%20%42%34%4.04
C13 London7%53%40%4.27
C14 London6%11%56%28%4.06
C15 San Francisco18%58%24%4.06
C16 London9%65%26%4.17
C18 San Francisco22%46%32%4.11
C19 San Francisco13%47%40%4.27
C20 San Francisco6%15%50%29%4.02
C21 San Francisco2%20%35%43%4.18
C22 London16%47%38%4.22
C23 London13%53%33%4.20
Programme health
Flag detection matrix · hover ● for detail
Trend column compares first-half vs second-half cohorts · meaningful from 4+ cohorts
FlagC6 LondonC7 San FranciscoC8 San FranciscoC9 LondonC11 San FranciscoC12 San FranciscoC13 LondonC14 LondonC15 San FranciscoC16 LondonC18 San FranciscoC19 San FranciscoC20 San FranciscoC21 San FranciscoC22 LondonC23 LondonTotalTrend
Low satisfaction2/16↑ more
High passive rate6/16↑ more
Low D2 response rate2/16→ stable
Confidence regression1/16↓ fewer
Persona NPS split7/16↓ fewer
Org concentration5/16↓ fewer
● WARNING● INSIGHT● INFOHover dots for detail · Trend compares first half vs second half of cohorts
Field notes · analyst annotations
Cohort-level observations · written after human Tier-2 review
Add entries via: analyze.py --outlier '…' --flag '…' then re-run trends.py
No analyst annotations yet. Use analyze.py --outlier "…" --flag "…" after Tier-2 review to add entries here.
Data quality · survey compliance and completeness
Cohorts with flagged data quality issues
Issues are flagged for transparency and database migration. Assessment and remediation tracked with delivery team.

1 cohort with data quality flags · tracked for delivery team review and remediation

C23 LondonLow match rate (40.0%), More D2-only (9) than matched40.0% matched · 9/15 D2-only
Org Landscape · organisations across all cohorts
Organisation reach — appearances, people, recency
People count from D1 org distribution · Avg NPS from D2 respondents meeting minimum n · Capability profile from v2 cohorts only
64
Organisations reached
745
D1 headcount
Total respondents
16
Cohorts
44%
28 orgs in 2+ cohorts
Returning orgs
OrganisationAppearancesPeopleRecencyAvg NPS
Returning organisations
Deloitte16143current+42
PwC91071 cohort ago+30
Infosys8371 cohort ago+26
Ascendion7171 cohort ago+75
Accenture664current+72
Capgemini627current+57
Lovelytics6122 cohorts ago
valantic5141 cohort ago
Fractal Analytics5142 cohorts ago
Cognizant4274 cohorts ago+42
McKinsey4253 cohorts ago+38
NEC4132 cohorts ago+50
Forgd.AI461 cohort ago
Persistent Systems3162 cohorts ago+82
Version 13126 cohorts ago+25
DXC Technology3121 cohort ago+50
AlixPartners3114 cohorts ago+50
Zartis376 cohorts ago
EPAM363 cohorts ago
IndiciumAI341 cohort ago
Bounteous3410 cohorts ago
KPMG2322 cohorts ago+6
UST Global2144 cohorts ago+38
Reply2101 cohort ago+50
Quantium273 cohorts ago
Bain26current
Slalom241 cohort ago
BCG229 cohorts ago
First appearance
Fractional AI / Ode1182 cohorts ago-30
DXC16current
Infomotion1515 cohorts ago
SFEIR1415 cohorts ago
Sia1413 cohorts ago
Theodo1412 cohorts ago
Netlight1412 cohorts ago
b.telligent149 cohorts ago+25
NTT Data1315 cohorts ago
Praecipio1313 cohorts ago
Horváth1312 cohorts ago
Nimble Gravity137 cohorts ago

+ 3 new orgs with <3 respondents in the last 3 cohorts — included in total reach count above.

Capability Profile

Orgs with ≥3 respondents who appeared within the last 3 cohorts. v2 data only.

Deloitte143 people · 16 cohorts · current
AI Proficiency
Frontier 11Independent 27Applying 62Learning 43
Personas
Architect 24Developer 51T.Lead 68
PwC107 people · 9 cohorts · 1 cohort ago
AI Proficiency
Frontier 8Independent 11Applying 65Learning 23
Personas
Architect 10Developer 20T.Lead 77
Accenture64 people · 6 cohorts · current
AI Proficiency
Frontier 10Independent 10Applying 32Learning 12
Personas
Architect 17Developer 22T.Lead 25
Infosys37 people · 8 cohorts · 1 cohort ago
AI Proficiency
Frontier 2Independent 3Applying 18Learning 14
Personas
Architect 10Developer 7T.Lead 20
KPMG32 people · 2 cohorts · 2 cohorts ago
AI Proficiency
Frontier 8Independent 8Applying 13Learning 3
Personas
Architect 8Developer 14T.Lead 10
Capgemini27 people · 6 cohorts · current
AI Proficiency
Frontier 3Independent 6Applying 10Learning 8
Personas
Architect 14Developer 3T.Lead 10
Fractional AI / Ode18 people · 1 cohort · 2 cohorts ago
AI Proficiency
Frontier 6Independent 3Applying 8Learning 1
Personas
Developer 16T.Lead 2
Ascendion17 people · 7 cohorts · 1 cohort ago
AI Proficiency
Frontier 3Independent 5Applying 9
Personas
Architect 5Developer 9T.Lead 3
Persistent Systems16 people · 3 cohorts · 2 cohorts ago
AI Proficiency
Frontier 2Independent 2Applying 11Learning 1
Personas
Architect 6Developer 9T.Lead 1
valantic14 people · 5 cohorts · 1 cohort ago
AI Proficiency
Frontier 1Independent 6Applying 4Learning 3
Personas
Architect 7Developer 4T.Lead 3
Fractal Analytics14 people · 5 cohorts · 2 cohorts ago
AI Proficiency
Independent 3Applying 7Learning 4
Personas
Architect 5Developer 6T.Lead 3
NEC13 people · 4 cohorts · 2 cohorts ago
AI Proficiency
Frontier 3Independent 1Applying 4Learning 5
Personas
Architect 4Developer 7T.Lead 2
Lovelytics12 people · 6 cohorts · 2 cohorts ago
AI Proficiency
Frontier 1Independent 3Applying 4Learning 4
Personas
Architect 5Developer 1T.Lead 6
DXC Technology12 people · 3 cohorts · 1 cohort ago
AI Proficiency
Frontier 2Independent 2Applying 6Learning 2
Personas
Architect 2Developer 1T.Lead 9
Reply10 people · 2 cohorts · 1 cohort ago
AI Proficiency
Independent 2Applying 8
Personas
Developer 7T.Lead 3
Forgd.AI6 people · 4 cohorts · 1 cohort ago
AI Proficiency
Frontier 2Independent 3Applying 1
Personas
Architect 5T.Lead 1
Bain6 people · 2 cohorts · current
AI Proficiency
Frontier 2Independent 2Applying 2
Personas
Architect 2Developer 4
DXC6 people · 1 cohort · current
AI Proficiency
Independent 1Learning 5
Personas
Architect 1T.Lead 5
IndiciumAI4 people · 3 cohorts · 1 cohort ago
AI Proficiency
Frontier 1Independent 1Applying 2
Personas
Architect 1Developer 2T.Lead 1
Slalom4 people · 2 cohorts · 1 cohort ago
AI Proficiency
Applying 3Learning 1
Personas
Architect 1Developer 1T.Lead 2
Regional divergence · audience profile and outcomes by city
London
7 cohorts · n=148 D2
+37
NPS
4.20
D2 conf /5
San Francisco
9 cohorts · n=417 D2
+44
NPS
4.15
D2 conf /5
Primary function
London
EngineeringArchitectureBusiness LeadershipProject / Engmt
All cohorts (includes est. v1)n=235
40%
28%
15%
17%
C14 Londonn=17
35%
35%
12%
18%
C16 Londonn=36
28%
28%
19%
25%
C22 Londonn=55
36%
27%
16%
20%
C23 Londonn=14
29%
21%
29%
21%
San Francisco
EngineeringArchitectureBusiness LeadershipProject / Engmt
All cohorts (includes est. v1)n=510
33%
23%
15%
29%
C18 San Franciscon=45
20%
22%
11%
47%
C19 San Franciscon=67
39%
27%
10%
24%
C20 San Franciscon=46
26%
30%
20%
24%
C21 San Franciscon=54
44%
22%
9%
24%
AI experience · v2 cohorts
London
Learning & exploringApplying in practiceDelivering independentlyOperating at the frontier
All cohorts (includes est. v1)n=235
20%
44%
21%
14%
C14 Londonn=17
12%
35%
41%
12%
C16 Londonn=36
25%
44%
28%
C22 Londonn=55
20%
55%
9%
16%
C23 Londonn=14
43%
36%
21%
San Francisco
Learning & exploringApplying in practiceDelivering independentlyOperating at the frontier
All cohorts (includes est. v1)n=510
21%
46%
19%
13%
C18 San Franciscon=45
29%
51%
18%
C19 San Franciscon=67
18%
48%
15%
19%
C20 San Franciscon=46
24%
46%
20%
11%
C21 San Franciscon=54
22%
35%
24%
19%
Seniority · v2 cohorts
London
Sr PractitionerPractitionerManager / Sr ManagerDirector / Sr DirectorPartner / MD / Exec
All cohorts (includes est. v1)n=235
19%
28%
34%
16%
C14 Londonn=17
12%
35%
24%
24%
C16 Londonn=36
25%
19%
31%
19%
C22 Londonn=55
15%
25%
44%
15%
C23 Londonn=14
29%
50%
21%
San Francisco
Sr PractitionerPractitionerManager / Sr ManagerDirector / Sr DirectorPartner / MD / Exec
All cohorts (includes est. v1)n=510
22%
23%
29%
19%
7%
C18 San Franciscon=45
20%
22%
36%
20%
C19 San Franciscon=67
24%
24%
25%
22%
C20 San Franciscon=46
11%
11%
33%
30%
15%
C21 San Franciscon=54
19%
43%
13%
22%
Technical depth
London
Too basicAbout rightToo advanced
CohortToo basicAbout rightToo advanced
All cohorts17%79%4%
C14 London35%65%
C16 London11%86%3%
C22 London7%87%5%
C23 London93%7%
San Francisco
Too basicAbout rightToo advanced
CohortToo basicAbout rightToo advanced
All cohorts16%75%9%
C18 San Francisco27%60%13%
C19 San Francisco9%87%4%
C20 San Francisco15%63%22%
C21 San Francisco28%63%9%
Pace
London
Too slowWell pacedToo fast
CohortToo slowWell pacedToo fast
All cohorts5%80%16%
C14 London6%76%18%
C16 London3%94%3%
C22 London5%62%33%
C23 London86%14%
San Francisco
Too slowWell pacedToo fast
CohortToo slowWell pacedToo fast
All cohorts8%81%11%
C18 San Francisco11%80%9%
C19 San Francisco6%84%10%
C20 San Francisco7%85%9%
C21 San Francisco19%61%20%
D2 confidence means /5
MetricLondonSan Francisco
Apply / Lead conversation4.204.15
Advising clients on AI4.204.16
Design an evaluation4.124.11