Exceeds

MARCH 2026

sap.com Engineering AI Productivity Report

A focused summary of AI adoption, productivity lift, and code quality for the sap.com engineering team.

See how AI-active teams rank this week on the Exceeds Leaderboards.

The sap.com engineering team reports 86.7% AI adoption, 1.45× productivity lift, and 21.4% code quality across recent work.

These metrics track how AI integrates into delivery pipelines, how throughput changes when assistance is used, and the health of AI-supported code review outcomes.

What this report measures

We analyze commits and diffs to estimate AI adoption, productivity lift, and code quality for your engineering organization.

How to interpret these metrics

Use these signals to understand how AI assistance fits into day-to-day development, where enablement efforts drive throughput, and how review practices keep quality steady.

AI Adoption Rate

HIGH

86.7%

AI assistance is present in 86.7% of recent commits for sap.com.

AI Productivity Lift

HIGH

1.45×

AI-enabled workflows deliver an estimated 45% lift in throughput.

AI Code Quality

LOW

21.4%

Review insights show 21.4% overall code health on AI-supported changes.

How is the sap.com team performing with AI?

The sap.com engineering team reports 86.7% AI adoption, translating into 1.45× productivity lift while sustaining 21.4% code quality. These outcomes suggest AI-supported reviews are embedded in day-to-day delivery without trading off reliability.

Manager Questions Answered

Real questions engineering leaders ask about AI productivity, with live benchmarks and company-specific data.

What's a good company AI adoption rate?

sap.com is at 86.7%. This is 43.0pp above the community median (43.7%)..

86.7%

Roughly in line43.7% Community Median

Spot squads sitting below the median and pair them with high-adoption champions to share workflows.

Does AI actually make developers faster?

sap.com operates at 1.45×. This is 0.32× above the community median (1.13×)..

1.45×

↑0.32× above1.13× Community Median

Double down on automation around QA and release prep to compound the gains already in flight.

How does AI affect code quality?

sap.com holds AI-assisted quality at 21.4%. This is 1.8pp below the community median (23.2%)..

21.4%

Roughly in line23.2% Community Median

Invest in AI-specific test checklists and shadow reviews to keep quality slightly ahead of peers.

How evenly is AI use distributed across our team?

AI usage is broad—top contributors represent 11.9% of AI commits.

11.9%

Keep rotating enablement leads and pair senior reviewers with new AI adopters to retain distribution.

How can I prove AI ROI to executives?

sap.com has a solid ROI signal with room to strengthen either adoption, lift, or quality before presenting to executives.

Document case studies where AI accelerates delivery while maintaining quality, and expand playbooks across teams.

See how your full organization compares

Unlock personalized insights across all your repositories, teams, and contributors.

Securely connect Exceeds with your codebase to get commit-level insights on AI adoption and performance.

How Your Company Ranks

See how top engineering organizations compare across AI adoption, productivity lift, and code quality.

AI Adoption

% of commits with AI assistance

Companies in this quartile:

CA

cancun.tecnm.mx

(87.3%)

MO

momentohq.com

(87.3%)

UB

ub.edu

(21.2%)

RO

rossabaker.com

(21.2%)

Top 25% of teams adopt AI in 65-75% of their commits.

Productivity Lift

Cycle-time improvement vs baseline

Companies in this quartile:

IN

inngest.com

(4.82×)

U.

u.nus.edu

(2.87×)

AC

acad.pucrs.br

(1.12×)

MC

mcornholio.ru

(1.12×)

Top performers sustain 1.5× cycle-time improvements over six months when embedding AI into workflows.

Code Quality

Post-merge defect rate

Companies in this quartile:

IN

inngest.com

(701.7%)

ID

idesie.com

(649.2%)

GZ

gzgz.dev

(20.0%)

GW

gwu.edu

(20.0%)

Top 25% maintain quality above 92% while expanding AI usage, pairing automation with rigorous guardrails.

Rankings based on aggregated Exceeds AI dataset of 1.2M commits across open-source and enterprise engineering teams (Q4 2025).

Top contributors

Top contributors combine high AI adoption and quality output. Encourage internal sharing of best practices.

LO

Lopes

Commits74
AI Usage94.0%
Productivity Lift2.00x
Code Quality20.0%
NC

Noel Chia

Commits18
AI Usage94.0%
Productivity Lift2.00x
Code Quality20.0%
TA

Taimoor Aslam

Commits40
AI Usage96.0%
Productivity Lift2.00x
Code Quality20.0%
KG

Kyma Goat Bot

Commits103
AI Usage20.0%
Productivity Lift2.00x
Code Quality97.3%
SS

Shreyas S

Commits2
AI Usage20.0%
Productivity Lift2.00x
Code Quality20.0%

Encourage knowledge transfer from top AI users to others through internal mentoring or recorded "AI coding walkthroughs." Balanced adoption across the team typically improves overall performance by 12-15%.

Cross-Organization Network

Shared Repositories

216

nicolai-huening

glaciation-heu/gitops-deployments

domdom82

gardener/gardener-extension-networking-calico

gardener/gardener-extension-networking-cilium

plowin

cloudfoundry/routing-release

Lokowandtg

cloudfoundry/community

hendrikKahl

gardener/cc-utils

Unknown contributor

gamedevlabs/pix-e

Activity

9,848 Commits

Your Network

497 People
app-autoscaler-ci-bot
Member
domdom82
Member
nesmabadr
Member
rakesh-garimella
Member
ArtieReus
Member
avasilev-sap
Member
singhabhi1999
Member
adrian-bobev
Member
agoerler
Member

Why these metrics matter for engineering managers

Faster delivery

1.4x lift → predictable roadmaps

Safer velocity

93% quality → lower rollback risk

Equitable gains

AI less dependency on heroes

Governance

Depth monitoring audit-ready

ExceedsExceeds AI

Turns these insights into daily coaching and automatic alerts, helping managers balance speed with sustainability.

See the truth of AI impact

Adoption + lift + quality in one view

Learn more

Know where to act first

Repo and role level "lift potential"

Learn more

Prove ROI

Export executive snapshots and benchmarks

Learn more