Enablement & Adoption

Track AI adoption across teams, identify champions and laggards, share best practices, and drive increased usage with targeted interventions.

Overall Adoption Rate

81%

689 of 850 engineers

333 users increasing usage

Champions

3.8% of total engineers

Active Users

689

Avg 6.9h/week per user

Needs Attention

161

Inactive - immediate action needed

Growing Usage

333

48% showing growth

Adoption Segments

Distribution of users by adoption level

Champions

32(20.5h/wk)

Active Users

217(12.3h/wk)

Moderate Users

226(5.2h/wk)

Low Adoption

214(1.5h/wk)

Inactive

161(0.0h/wk)

Team Adoption Breakdown

Compare AI adoption across 8 engineering teams

Team	Size	Adoption Rate	Avg Hours/Week	Champions	Laggards	Top Tools
Mobile Engineering	65	86%	6.4h	5	27	Notion AICursor
Backend	130	84%	5.8h	5	56	GrammarlyNotion AI
Product Engineering	220	82%	5.6h	8	95	CursorGrammarly
Data Engineering	95	82%	6.0h	5	41	CursorGrammarly
Platform Engineering	85	80%	5.2h	3	39	Notion AIChatGPT Plus
Security	48	79%	4.8h	0	25	ChatGPT PlusClaude Pro
Infrastructure	72	78%	5.2h	2	32	ChatGPT Plusv0
Frontend	135	76%	5.3h	4	60	GrammarlyCursor

Highest Adoption

Mobile Engineering

86%

Most Champions

Product Engineering

8 champions

Needs Most Support

Frontend

76% adoption

Top AI Champions

Power users leading AI adoption

Rank	Engineer	Team	Hours/Week	Primary Tools
#1	Mason Garcia Engineer	Frontend	24.0h	GitHub CopilotNotion AIChatGPT Plus
#2	James Smith Engineer	Backend	24.0h	Notion AIChatGPT PlusGrammarly
#3	Charlotte Gonzalez Junior Engineer	Data Engineering	23.4h	GrammarlyGitHub CopilotCursor
#4	Lucas Jones Junior Engineer	Frontend	23.1h	v0Cursor
#5	Benjamin Garcia Junior Engineer	Mobile Engineering	23.0h	Notion AIGitHub CopilotGrammarly
#6	Sophia Johnson Junior Engineer	Data Engineering	22.7h	v0GrammarlyChatGPT Plus
#7	Sophia Moore Junior Engineer	Product Engineering	22.6h	Claude ProGitHub Copilot
#8	Emma Rodriguez Senior Engineer	Backend	22.4h	GitHub Copilotv0Grammarly
#9	Lucas Davis Junior Engineer	Infrastructure	22.2h	GitHub CopilotClaude ProNotion AI
#10	Amelia Anderson Senior Engineer	Mobile Engineering	22.0h	Notion AIGitHub CopilotCursor

Recognition Opportunity

Consider publicly recognizing these champions and leveraging them as mentors for peer learning programs. Their expertise can accelerate team-wide adoption.

Users Needing Attention

Engineers with low or no AI tool usage

Engineer	Team	Hours/Week	Status	Action
Henry Anderson Engineer	Backend	0.0h	Inactive	Onboarding needed
Amelia Hernandez Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Emma Jackson Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Lucas Taylor Senior Engineer	Backend	0.0h	Inactive	Onboarding needed
William Miller Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Harper Lopez Engineer	Backend	0.0h	Inactive	Onboarding needed
Evelyn Garcia Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Liam Hernandez Engineer	Backend	0.0h	Inactive	Onboarding needed
Henry Gonzalez Engineer	Backend	0.0h	Inactive	Onboarding needed
Amelia Brown Engineer	Backend	0.0h	Inactive	Onboarding needed
Harper Davis Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Mia Jackson Engineer	Backend	0.0h	Inactive	Onboarding needed
Ethan Gonzalez Senior Engineer	Backend	0.0h	Inactive	Onboarding needed
Amelia Moore Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Isabella Garcia Engineer	Backend	0.0h	Inactive	Onboarding needed
William Taylor Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Liam Jones Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Ava Davis Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
William Garcia Junior Engineer	Backend	0.0h	Inactive	Onboarding needed
Benjamin Jones Junior Engineer	Backend	0.0h	Inactive	Onboarding needed

Action Required

These 20 users represent missed productivity opportunities. Consider: 1-on-1 onboarding sessions, assigning an AI buddy, or targeted training workshops.

Best Practices

Proven practices from top users and industry leaders

Daily AI Assistant Usage

high impact

Use AI coding assistants for every coding session, not just complex tasks

Adoption:

68%

productivity

CursorGitHub

Source: Top 10% users

AI-Powered Code Reviews

high impact

Use AI to pre-review code before submitting PRs, catching issues early

Adoption:

45%

quality

ClaudeChatGPT

Source: Industry benchmark

Context-Rich Prompts

medium impact

Provide detailed context and examples in prompts for better AI responses

Adoption:

52%

productivity

ClaudeChatGPT

Source: Top 10% users

Actionable Recommendations

Data-driven actions to improve adoption

Organize AI Tools Training Workshop

highmedium effort

Target: Security Team

Security team has only 62% adoption rate, well below company average. Schedule hands-on training.

+15-20% adoption within 4 weeks

Add 15 Cursor Licenses

highlow effort

Target: Frontend Team

Frontend team at 95% license utilization with high ROI. Clear demand for expansion.

10-12 additional hours saved per week

Add AI Tools to Onboarding

highlow effort

Target: All New Hires

New engineers take 7.5 days to first commit. With AI: 3.2 days. Include in day-1 onboarding.

57% faster onboarding for new hires

Quick Wins

Focus on 2 high-priority, low-effort recommendations first for immediate impact.