Reporting window · Aug 5 – Sep 1, 2026 · 28-day cohort

Copilot Impact Dashboard

Measured adoption, consumption and cost for the tke enterprise, with a transparent model of what the platform has to return in developer time to pay for itself.

Enterprise tke · ID 513004 Plan GHEC EMU Support Premium Unified Billing Zuora + Azure Budget cap $30,000 · hard stop

August 2026 headline

All Copilot activity sits on the tke enterprise. The second enterprise, tkelevator, has zero Copilot seats and is excluded.

Copilot Business seats
551
Copilot Enterprise: 0
Monthly active (28d)
364
66% of seats · +73% since March
Weekly active (avg)
264
48% of seats
AI units consumed
1.87M
$18,745 gross usage value
Idle seats
187
$3,553/mo · $42.6k/yr unrealised

Usage is growing, and deepening

Monthly active developers grew from 211 in March to 364 in August. More importantly, the share of users in agent-first phases (2 and 3) went from 0% to 7.9%.

Active developers vs. licensed seats

Monthly active (28d) and weekly active (7d rolling average), March – August 2026.

0 150 300 450 600 551 seats 211364 MarAprMay JunJulAug
Monthly active (28d) Weekly active (7d avg) Licensed seats

Adoption phases

453 engaged users, Aug 5 – Sep 1. Phase reflects how deeply a developer uses Copilot, from passive completions to agent-first workflows.

No cohort · passive 105 · 23.2%
Phase 1 · code-first 315 · 69.5%
Phase 2 · agent 27 · 6.0%
Phase 3 · agent-first 6 · 1.3%

Average lines of code added per developer per day, by phase

No cohort 60.3
Phase 1 112.3
Phase 2 438.5
Phase 3 169.7

Phase 2 developers ship 3.9× more code than Phase 1

438.5 lines/day versus 112.3. Only 33 of 453 engaged developers (7.3%) have reached agent-first working patterns. Moving another 10% of the Phase 1 population into Phase 2 is the single highest-leverage adoption action available.

Where the AI units go

August 2026, 1,874,466 AI units. VS Code chat dominates, but CLI and agentic surfaces now account for 12% of consumption.

By integration

Share of August AI units

vscode-chat1,406,948
copilot-developer-cli177,167
jetbrains-chat115,662
visualstudio-chat83,386
opencode58,259
copilot-developer-app20,708
claude-code10,964
copilot-pr-reviews347

By model

Top models, August AI units and usage value

ModelAI unitsValue
gpt-5.4353,554$3,536
claude-opus-4.8281,357$2,814
gpt-5.6-terra201,478$2,015
gpt-5.6-sol189,575$1,896
gpt-5.5177,985$1,780
claude-sonnet-5155,888$1,559
gpt-5.3-codex153,704$1,537
claude-sonnet-4.6144,950$1,450
gpt-5.6-luna64,254$643
claude-sonnet-4.534,230$342

Healthy model mix

No single premium model runs away with the budget. The most expensive model is 19% of spend, and mid-tier models (Sonnet, Codex, Terra) carry a large share. This is a well-balanced profile.

What it costs today

Gross usage is the total value of AI consumed. Billable is what remains after the included entitlement pools are applied. The gap between them is the promotional pool that expired on 1 September 2026.

MonthAI unitsGross usage BillableCovered by pools Avg daily usersPeak
June 20262,318,830$23,188$10,071$13,117139.9230
July 20261,824,944$18,249$2,911$15,338139.8230
August 20261,874,466$18,745$1,915$16,830132.8206

Promotional entitlement pool expired 1 September 2026

Through August, TK Elevator had a promotional pool of $16,770/month on top of the standard pool of $10,640/month. That is why August billed only $1,915 against $18,745 of gross usage. From September the promotional pool is gone and only the standard pool (551 seats × 1,900 credits = $10,469/month) applies. At August consumption levels, the metered line moves from $1,915 to roughly $8,276/month — a 4.3× increase. This is a change in what is invoiced, not a change in behaviour.

Money spent vs. money returned

A deliberately simple model. Costs are measured. Benefits are derived from a single lever, developer time saved, so the customer can argue with one number rather than ten.

Expenses · run-rate

Copilot only. GitHub Enterprise licensing is excluded.

  • Copilot Business · 551 seats × $19$10,469 / mo
  • Metered AI, August billed$1,915 / mo
  • August actual$12,384 / mo
  • Copilot Business · 551 seats$10,469 / mo
  • Metered AI, post-promo estimate$8,276 / mo
  • Forward run-rate$18,745 / mo
Annualised: $148,608 at August actuals → $224,940 at forward run-rate

Value returned · time saved

364 monthly active developers at a fully-loaded cost of $130,000/year each.

Time savedHours / moValue / moValue / yr
30 min / dev / week788$53,357$640,284
1 h / dev / week1,576$106,714$1,280,568
2 h / dev / week3,152$213,428$2,561,136
3 h / dev / week4,728$320,142$3,841,704
hours = 364 devs × h/week × 4.33 weeks
value = hours × $67.71/h  (= $130,000 ÷ 12 ÷ 160 h)
30 minutes
per developer, per month — the amount of time Copilot must save to fully pay for itself at August cost

How the break-even is calculated

August Copilot cost  $12,384 ÷ 364 active devs = $34.02 per developer per month
$34.02 ÷ $67.71 per developer-hour = 0.50 hours = 30 minutes / dev / month
As a share of a 160-hour month: 0.31% of engineering capacity

At the forward run-rate of $18,745: $51.50 per dev ÷ $67.71 = 46 minutes / dev / month  (0.48%)

Put differently: if Copilot saves each active developer half an hour a month, the platform is free. Every minute beyond that is net return. Independent field studies place realistic savings in the range of 1 to 3 hours per developer per week, which is 8 to 26 times the break-even threshold.

Net position at 1 h/dev/week

  • Value returned+$106,714 / mo
  • Copilot cost, forward run-rate−$18,745 / mo
  • Net monthly benefit$87,969 / mo
  • Net annual benefit$1,055,628 / yr
Return on spend: 5.7× at forward run-rate · 8.6× at August actuals

Cost as a share of payroll

GitHub's own ROI framing, taken from the impact API for this enterprise.

Phase 0-1 users 0.79%
Phase 2-3 users 1.62%
Break-even threshold 0.31%

Even the heaviest agent-first users cost 1.62% of their own payroll. The lightest cost 0.79%. Both sit far below any plausible productivity gain.

Assumptions, stated plainly

  • $130,000 fully-loaded annual developer cost. This is GitHub's default modelling figure, not a TK Elevator figure. Substitute the real number and every value scales linearly.
  • 160 productive hours per month, 4.33 weeks per month.
  • 364 active developers, the measured 28-day active count. The 187 idle seats are counted as cost but contribute zero benefit, so the model is conservative.
  • USD throughout. Consumption data is billed in USD; no EUR conversion is applied.
  • Time saved is not measured in this data. It is the one input the customer must supply or accept from benchmark. Everything else on this page is observed.

Three things worth doing

1  Reclaim 187 idle seats

551 seats, 364 active. The 187 seats with no activity in 28 days cost $3,553/month, or $42,636 a year.

Either reassign them to teams on the waiting list or release them at the next true-up. Idle seats also drag down every per-seat metric used to justify the platform internally.

2  Move Phase 1 into Phase 2

315 developers sit in Phase 1 at 112 LoC/day. The 27 in Phase 2 run at 438 LoC/day.

This is an enablement problem, not a licensing one. Agent mode, Copilot CLI and PR review are already available on their seats and barely used — copilot-pr-reviews is 347 AI units out of 1.87 million.

3  Brief finance before the September invoice lands

The metered line moves from $1,915 to roughly $8,276 with no change in developer behaviour, purely because the promotional pool expired. If nobody has flagged this, it will read as a 4× cost overrun. The enterprise budget is $30,000/month with PreventFurtherUsage, so there is no service risk, but there is a credibility risk.

Data gap: pull request telemetry is empty

Every PR metric returns zero — pull requests merged, median time to merge, code-shipped multiplier. Without it there is no cycle-time or throughput story, which is the evidence a CFO will ask for next. Worth confirming whether TK Elevator's repositories sit inside the tke EMU enterprise or whether this is a telemetry gap to raise internally.