How accurate is the AI development impact calculator?

Our calculator uses industry-validated benchmarks from 2024 Gartner Enterprise Study (up to 50% productivity gains), McKinsey (35-45% improvements), and real-world implementations showing 25-67% productivity increases.

What factors does the impact calculator consider?

The calculator considers team size, average engineer cost, and time allocation across 7 development phases: requirements, architecture, coding, testing, reviews, documentation, and DevOps.

What is included in the AI investment cost?

The €3,000 per engineer annual investment includes Claude Code Max (€1,200), professional training (€600), complementary tools like GitHub Copilot (€600), implementation support (€400), and infrastructure (€200).

Impact Calculator Quantify Your Team’s Potential with AI

Calculator

Configure Your Development Team

Customize your team size, costs, and time allocation to measure the expanded capacity and productivity gains from AI-native development.

Team Size

Typical ranges: 5-20 (startup), 20-100 (scale-up), 100+ (enterprise)

Average Engineer Cost

€

Typical ranges: €50k-€65k (junior), €60k-€80k (mid), €75k-€110k (senior)

Avg Hours per Engineer

40h/week

Total Annual Spending

€2.800.000

⚠️ Total hours exceed 40h limit - please adjust your time allocation

Corporate email required for accurate calculations

Capacity Gains by Development Phase

Investment Breakdown (Per Engineer Annually)

Claude Code Max Plan

Enterprise AI coding assistant
• Advanced features & unlimited usage

€1.2K

Professional AI Training

2-day intensive workshop
• Premium curriculum (amortized over 2 years)

€600

Complementary AI Tools

GitHub Copilot Enterprise
• Specialized models & extensions

€600

Implementation & Support

Integration, maintenance
• Team onboarding & ongoing optimization

€400

Infrastructure & Security

Enhanced compute resources
• Security compliance & governance

€200

Total Annual Investment

Comprehensive AI development
transformation per engineer

€3K

*Investment based on current market pricing and enterprise requirements. Automation percentages validated by independent research studies below.

Research Validation: Independent Studies Confirm AI Development ROI

Gartner Enterprise Study (2024)

Up to 50% Gains

McKinsey Global Analysis

35-45% Gains

Anthropic Real-World Results

3x Faster

Stanford Academic Research

67% Improvement

Palo Alto Networks Case Study

25% Increase

Independent studies validate 25-67% productivity improvements from AI development tools. These results require professional training and optimized workflow implementation. Teams without proper guidance typically achieve only 10-15% gains or experience productivity losses.

Review These Numbers with an Expert

These results require expert implementation. Without proper training and workflow optimization, teams often achieve minimal gains or productivity losses.

Let's discuss your specific context and create a tailored implementation plan that captures the full productivity potential for your team.

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Calculate Your Team's Impact

Configure Your Development Team

Your AI Investment Returns

These results require proper implementation

Capacity Gains by Development Phase

Investment Breakdown (Per Engineer Annually)

Research Validation: Independent Studies Confirm AI Development ROI

Review These Numbers with an Expert

Configure Your Development Team

Your AI Investment Returns

These results require proper implementation

Capacity Gains by Development Phase

Investment Breakdown (Per Engineer Annually)

Research Validation: Independent Studies Confirm AI Development ROI

Review These Numbers with an Expert

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