AI-DLC Adoption Readiness Assessment
Are you actually ready for AI-DLC — before you commit a pilot team and budget?
A structured, 25-criteria scoring model across 5 dimensions that produces a weighted Readiness Score and a recommended Adoption Path, delivered as an auto-calculating Excel workbook.
Delivered as an Excel workbook. Download immediately after purchase.
■ Instant download · ■ No macros · ■ Excel 2016+
The AI-DLC Adoption Readiness Assessment is a 25-criteria Excel diagnostic that scores an organisation's readiness to adopt an AI-driven development lifecycle across five dimensions — strategic, organisational, technical, governance, and delivery readiness — producing a weighted Readiness Score (1–5) and a recommended Adoption Path (Foundation Needed, Pilot in Bounded Greenfield, or Ready to Scale).
Most organisations approach AI-DLC adoption backwards.
They select a pilot team first and discover the governance, technical, and organisational gaps only after the pilot stalls. This assessment reverses that sequence — scoring readiness before a team or a budget line is committed.
The scoring framework.
Five dimensions. Twenty-five criteria. Weighted so Technical and Governance readiness carry more of the decision — and carry even more when the target codebase is Brownfield or Regulated-Core.
- AI-DLC Adoption Readiness Assessment
- A structured evaluation of whether an organization is positioned to adopt an AI-driven development lifecycle before committing a pilot team or budget, scored across strategic, organisational, technical, governance, and delivery dimensions.
- Adoption Path
- A three-tier recommendation — Foundation Needed, Pilot in Bounded Greenfield, or Ready to Scale — driven by Technical and Governance readiness scores combined with the overall Readiness Score.
Every tab, explained.
A 4-tab workbook, formula-based throughout — no macros, no VBA, no external data connections.
AI-DLC Readiness Assessment vs. alternatives.
Most organisations reach for one of two approaches before this. Neither produces a defensible answer to "are we ready, and for how much."
| Approach | What It Measures | Key Limitation / Difference |
|---|---|---|
| Generic AI maturity survey | Broad, org-wide AI capability | Not specific to development lifecycle adoption; no Adoption Path output |
| Ad hoc pilot (no assessment) | None — pilot selected on availability or enthusiasm | Highest failure risk; governance and technical gaps surface mid-pilot |
| Viksya AI-DLC Readiness Assessment | 25 criteria across 5 dimensions, evidence-anchored | Weighted Readiness Score + Adoption Path recommendation before budget is committed |
Built for the people who have to defend the number.
Decide whether to commit budget and a pilot team to AI-DLC adoption with a scored, defensible readiness baseline.
Scope which workstreams are AI-DLC eligible now, and which need foundational work first.
Sequence a SAFe-to-AI-DLC migration against evidence rather than executive enthusiasm.
Bring a credible, evidence-based readiness instrument into client engagements instead of a blank-page workshop.
New to the vocabulary? AI-DLC introduces its own terms — Bolts, Units of Work, Mob Elaboration, Verification Gates — that this assessment's criteria reference directly.
View AI-DLC Dictionary →Questions buyers ask before scoring their organisation.
What is an AI-DLC adoption readiness assessment?
An AI-DLC adoption readiness assessment is a structured evaluation that scores an organisation's preparedness to adopt an AI-driven development lifecycle — typically across strategic, organisational, technical, governance, and delivery dimensions — before committing a pilot team or budget.
How is AI-DLC different from Agile or SAFe?
AI-DLC replaces sprint-based execution with short, AI-executed cycles called Bolts, and replaces backlog grooming with real-time team validation rituals. The bottleneck shifts from coordinating human throughput to governing AI-generated decisions at speed, which is why standard Agile or SAFe readiness criteria do not transfer directly.
What does the Adoption Path recommendation mean?
The Adoption Path is a three-tier recommendation — Foundation Needed, Pilot in Bounded Greenfield, or Ready to Scale — based on Technical and Governance readiness scores combined with the overall Readiness Score. It tells you not just how ready you are, but what scope of adoption is defensible right now.
Do we need this before running an AI-DLC pilot?
Running a pilot without a readiness assessment is the most common cause of stalled AI-DLC adoption. Technical and governance gaps that surface mid-pilot are far more expensive to fix than gaps identified during a structured pre-adoption assessment.
What Excel versions does this work with?
The workbook is fully compatible with Excel 2016, 2019, 2021, and Microsoft 365. It uses formulas only — no macros, no VBA, no external data connections.
Is this specific to AWS's AI-DLC methodology?
The assessment criteria are informed by AWS's published AI-DLC methodology but are written to be vendor-neutral, so they apply whether your organisation adopts AWS's specific framework or a different AI-driven development approach.
AI-DLC Adoption Readiness Assessment
Score your organisation across 25 criteria before you commit a pilot team and budget to AI-DLC.