Strategy and value
“Every team is at a different stage with AI, and there's no roadmap.”
Some teams are experimenting, some are all in, some are waiting for permission. Nobody can say where the organization stands as a whole.
The question leaders ask
Where do we actually stand with AI, and what comes next?
01 / The challenge
You will recognize this if…
- AI use varies widely between teams, programs and vendors.
- The strategy says "AI-first", but nothing says what changes next quarter.
- You cannot compare yourselves with peers, or with where you were last year.
- Investment decisions are made tool by tool, not as a plan.
02 / Why it happens
The root cause.
AI adoption in software delivery happened bottom-up, one tool and one team at a time. Without a shared picture of maturity across strategy, process, people, engineering and governance, every decision is local and progress cannot be steered.
Maturity is not the number of tools you have licensed. It is how consistently AI improves outcomes across strategy, delivery, people, engineering and governance. Most organizations are uneven: one team is far ahead, another has barely started, and vendors sit somewhere else again.
We believe a roadmap should be built from evidence, not ambition. Assess honestly, choose the next level for each dimension, and move a few things decisively rather than everything a little. A roadmap you can fund and track beats a vision deck every time.
04 / How we solve it
What we do about it, with you.
We assess where you stand, agree the next level for each dimension, and stay alongside you as an advisor while the roadmap is delivered.
- 01
Assess where you stand
An AI adoption assessment across teams and vendors: tools, practices, engineering quality, skills, governance and outcomes.
- 02
Place it on a maturity framework
Our AI-SDLC maturity framework shows where each team is, from exploring to AI-native, and what the next level looks like.
- 03
Build the roadmap
A sequenced plan: what to change, in what order, with what investment and what return.
- 04
Track the climb
Re-assess at intervals, so leadership sees maturity and outcomes moving, not just license counts.
One clear picture of where you stand
A roadmap leadership can fund and track
Progress measured in maturity and outcomes
The framework
Know where you stand. See the next step.
The assessment places each team, and the organization as a whole, on five levels of AI-SDLC maturity. The roadmap is the route from where you are to where you need to be.
The YuktiMedha AI-SDLC maturity framework
Five levels. Six dimensions. One roadmap.
Each dimension is placed on a level, so the roadmap shows exactly what to move next.
- Level 1ExploringIndividuals try AI tools on their own. No shared rules, no measures.
- Level 2AdoptingApproved tools and basic guidelines. Usage is tracked, outcomes are not.
- Level 3IntegratedAI is built into the SDLC, with quality gates, guardrails and delivery measures.
- Level 4OptimizedDelivery is measured, predicted and steered. Ownership is end to end and feedback arrives in days.
- Level 5AI-nativeRoles, estimation, pricing and governance are redesigned around AI.
Assessed across
- Strategy and value
- Process and delivery
- People and roles
- Engineering quality
- Governance and risk
- Measures and economics
Does this sound like your team?
Tell us what you are seeing, and we will tell you honestly whether and how we can help.