SDLC AI Capability Scorecard

AI Tools Alone Won't Transform Your SDLC

Many teams believe they're already using AI effectively across the software development lifecycle (SDLC). But tool adoption isn't capability, and the gap between the two is where investment quietly leaks. This scorecard gives you a snapshot of where your team stands across all seven SDLC phases, scored on a five-level maturity scale.

What is the Five-Level Maturity Scale?

The Five Level Maturity Scale measures how systematically and safely AI is embedded across each phase of the SDLC.

Level 1

Exploring

Ad-hoc individual use; no shared standards or visibility.
Level 2

Experimenting

Some developers trialling AI; inconsistent, ungoverned.
Level 3

Operationalising

AI in daily workflows with policies and quality gates.
Level 4

Scaling

Standardised, reusable patterns and playbooks across teams.
Level 5

Transforming

AI-native delivery; agents and MCP integral to the SDLC.

How the Scorecard Works

Step 1: Answer the Questions

Select the answer that best describes your team's current state, for each SDLC phase. The scorecard will calculate each phase's current score from your answer.

Step 2: Set a Target

Choose a target for each phase, typically one to two levels up from where you are now.

Step 3: Re-measure at Handover

Your step one scores will become the baseline. When the engagement wraps and capability hands back to your team, you score again - the gap between the two is your proof of improvement.

Your maturity level is scored based on your lowest-scoring phase

Even if your team moves fast in, say, code generation, if they're still relying on a developer to manually run regression testing, that doesn't add up to a high maturity score.

Go to scorecard

What are the target outcomes?

Measurable change in how your team ships to production, not just a higher score.

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Developer Productivity

Meaningful improvement in output per developer.

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Cycle Time

Reduced feature delivery time.

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Code Quality

Improved test coverage, fewer defects in production.

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Developer Satisfaction

Reduced toil, more time on high-value work.

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Governed Usage

Clear policies, quality gates and compliance controls in place.

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Self-Sustaining Capability

Internal champions, prompt libraries and a community of practice.

Next step

Walk Through Your Results With Us

Share a few details below and we'll set up a time to go through your SDLC results together, what they mean, and what a phased engagement would actually involve for your team.

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