At Stratfield, we transform Digital Engineering through strategic AI enablement that drives tangible business outcomes. Our proven five-step methodology combines enterprise-grade security and governance with a pragmatic implementation approach. Stratfield delivers beyond technology deployment, we prioritize sustainable adoption and measurable impact, helping clients accelerate their development cycles while maintaining the highest standards of code quality and security compliance. 

Driving Innovation Through AI Integration 

AI Enablement forms the cornerstone of Stratfield's Delivery Model, accelerating digital transformation across our Digital Engineering practice. As of Q1 2025, we're seeing significant opportunities within Digital Engineering, where our AI-enhanced delivery model is improving efficiency across code reviews, test coverage, and development cycles. Within diverse prompt ecosystems, our Engineering teams are achieving meaningful results across Design, Development, and Testing phases. 

Our five-step methodology ensures successful AI integration while maintaining the highest standards of security and compliance: 

1. Security, Intellectual Property, and Governance ("SIG") 

We meet clients where they are on their AI enablement journey, beginning with a comprehensive discovery assessment of existing practices and technology infrastructure. This evaluation informs our tailored recommendations for digital engineering engagements. 

Stratfield maintains technology agnosticism across leading prompt engineering tools including GitHub Copilot, Cursor, Claude, and ChatGPT. Our approach prioritizes security, intellectual property protection, and governance alignment as non-negotiable foundations before implementation begins. We've developed robust frameworks that ensure compliant AI adoption while maximizing business value. 

2. Identify a Starter Project 

Success in AI enablement begins with choosing the right initial project. We select candidates based on specific criteria: 

• Defined implementation timeframe 

• Minimal external dependencies 

• Clear success metrics 

• Controlled risk with high visibility 

• Strong potential for business impact 

This focused approach allows for rapid demonstration of value while establishing proven patterns for broader implementation. 

3. Build a Templated Approach for AI Enablement 

Following the successful completion of the starter project, we document and systematize our delivery best practices. Our templates cover: 

• Security and compliance checkpoints 

• Prompt engineering guidelines 

• Quality assurance frameworks 

• Performance monitoring protocols 

• Knowledge sharing mechanisms 

This standardization ensures consistent quality while accelerating future implementations. 

4. Build Adoption 

Our impact-driven approach to scaling AI capabilities emphasizes sustainable growth. We recommend a strategic expansion strategy: 

• Vertical scaling within existing teams 

• Horizontal expansion to adjacent projects 

• Regular training and enablement sessions 

• Continuous feedback loops 

• Change management support   

This measured approach, supported by Stratfield's Change Management expertise, drives consistent adoption across client engagements.   

5. Measuring Results 

We believe in transparent, data-driven demonstration of value. Our results framework includes: 

• Regular stakeholder demonstrations 

• Custom metrics tracking 

• Impact analysis 

• Usage patterns and adoption rates 

• Quality indicators 

• Velocity measurements   

Looking Forward 

The integration of AI within Digital Engineering represents more than just technological advancement—it's a fundamental shift in how we approach software development and delivery. Stratfield's methodology ensures this transformation occurs systematically, securely, and successfully.   

Where to Learn More 

1. Visit our Digital Engineering hub

2. Schedule a consultation

3. Connect with Lee Turner on LinkedIn