AI Adoption and Maturity Trends

2026-03 → 2026-07 · 5 snapshots

Synthesis Software Technologies · Technology Office · Long-term view · latest: 2026-07-01 · latest snapshot →

74%
License adoption
+5.0pp vs prior month
62
Employees with no tools
-10.0 vs prior month
42%
Projects using AI
-4.7pp vs prior month
107
Assessment responses
no change vs prior

Adoption over time

License adoption by tool

Adoption by department

Heatmap of department adoption % across snapshots. Departments are sorted by latest headcount; cells are blank when a department wasn’t present that month.

Latest snapshot (2026-07) — license coverage by department

Department Headcount With license Adoption %
Code 52 38 73.1%
Cloud 32 18 56.2%
Regtech 23 18 78.3%
Halo 22 12 54.5%
Managed Operations 20 14 70.0%
Intelligent Data 17 14 82.3%
Sales 12 12 100.0%
Payment Centre of Excellence 11 8 72.7%
PMO 9 7 77.8%
Business Enablement & Operations 8 7 87.5%
Professional Services 7 7 100.0%
Finance 5 5 100.0%
Technology 4 4 100.0%
Cryptography 4 3 75.0%
Araxi 3 2 66.7%
Product Incubation 2 2 100.0%
Human Resources 2 1 50.0%
Marketing 1 0 0.0%
Product Development Services 1 1 100.0%
Executive 1 1 100.0%

Project AI maturity by tier

Each project is assigned to its highest qualifying tier each month. L3 is CI/CD-embedded or full-feature AI; L2 is AI for development; L1 is research-only; L0 is no AI; TBD are projects pending classification.

Project performance by AI tier

Mean overall_rating per AI tier, over time. Climbing lines on L2/L3 vs flat L0 lines support the “AI is helping delivery” story; divergence the other way is worth investigating.

People bridge quality

Match quality for projects_people.csv, grouped by project role and match method.

Month Role Match Method Rows Share of Role
2026-05 account_manager name 42 100.0%
2026-05 project_manager name 20 100.0%
2026-05 tech_lead name 41 100.0%
2026-06 account_manager name 45 100.0%
2026-06 project_manager name 21 100.0%
2026-06 tech_lead alias 1 2.5%
2026-06 tech_lead name 39 97.5%
2026-07 account_manager name 51 100.0%
2026-07 project_manager name 24 96.0%
2026-07 project_manager unmatched 1 4.0%
2026-07 tech_lead alias 1 2.22%
2026-07 tech_lead name 44 97.78%

Project AI tag mix (detail)

Tag-level breakdown beneath the tier rollup. A project can carry multiple tags; counts here are tags, not projects.

License movement

New seats added this month vs seats lost (shown below zero) and seats retained from the prior month. A retained-heavy bar means stable adoption; a new-heavy bar means active rollout.

Self-assessed maturity

Distribution of self-reported AI maturity levels (L0–L4) across respondents each month, as % of total responses.

Latest snapshot (2026-07) — by department

Department Responses Avg level Developers L0 L1 L2 L3 L4
Code 24 2.08 0/24 1 0 19 4 0
Cloud 16 2.25 0/16 0 1 11 3 1
Regtech 14 2.43 0/14 0 0 9 4 1
Intelligent Data 8 2.25 0/8 0 0 6 2 0
Payment Centre of Excellence 8 2.5 0/8 0 0 5 2 1
Managed Operations 6 2.17 0/6 0 1 4 0 1
PMO 6 2.17 0/6 0 0 5 1 0
Business Enablement & Operations 5 2.4 0/5 0 0 3 2 0
Professional Services 5 2.6 0/5 0 0 2 3 0
Sales 5 1.8 0/5 0 1 4 0 0
Halo 3 2.0 0/3 0 0 3 0 0
Technology 2 4.0 0/2 0 0 0 0 2
(no department) 2 1.5 0/2 0 1 1 0 0
Product Incubation 2 3.0 0/2 0 0 0 2 0
Cryptography 1 3.0 0/1 0 0 0 1 0

Alignment matrix over time

Counts of respondents in each tools-vs-self-assessment bucket. Aligned = L2+ with tools; Add methodology = L2 with tools (move-the-middle cohort); Critical gap = L3+ self-assessed with no tools provisioned.