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AI Transformation Sprint

Turn approved AI roadmaps into production workflows.

Most enterprise AI work stalls between approved roadmap and shipped workflow. The Transformation Sprint closes that gap in three weeks, and Architech builds the workflows that follow.

Speak with an AI Engineer
Duration3 weeks
FormatSuccess-based engagement
ScopeOne to four workflows
OutcomePlan of record + measurement baseline
Ideal Fit

Who this is for

  • Operations leaders with approved AI roadmaps who need a deployable plan

  • COOs, CFOs, and all other executives who own the outcomes the workflows must deliver

  • Teams that have run AI pilots without converting them into production

  • Organizations whose AI Task Force has produced an inventory but not a plan of record

  • Leaders who want measurement infrastructure in place before transformation begins, not after

The Starting Point

Why organizations start with a Transformation Sprint

Approved AI roadmaps do not deploy themselves. The Sprint produces a deployable plan, anchored to your real numbers, with measurement built in from day one.

Convert roadmap into plan of record

Approved roadmaps name what to do. The Sprint sequences how to do it, with named owners, dependencies, and 30/60/90 milestones a delivery team can execute against.

Anchor projections in your real numbers

Generic ROI estimates collapse on contact with reality. The Sprint quantifies cost baselines and impact projections against your operational data, with confidence levels documented.

Establish baselines before deployment

The Sprint defines what gets measured and captures the baseline before transformation begins. Without that, transformation outcomes cannot be measured after.

De-risk with success-based pricing

Acceptance criteria are confirmed in Week 1. If outcomes are not accepted, no fee is charged. Capital follows confidence.

What it is

What the Transformation Sprint is

The AI Transformation Sprint is a structured three-week engagement that converts an approved AI roadmap into a deployable plan, with baselines and named owners.

It is not a strategy exercise. It is not a vendor evaluation. It is not a discovery call.

It is a focused process that produces decision-ready artifacts and the measurement infrastructure required to deploy AI workflows into production.

Duration3 weeks
FormatSuccess-based engagement
ScopeOne to four workflows
OutcomePlan of record + measurement baseline
The engagement

How the engagement works

Three weeks. One team end to end. No handoffs.

  1. Week 1. Discover

    Workflow shadowing with operational teams. Data extraction from your operational systems. Interviews with workflow owners and AI program leaders. Acceptance criteria confirmed.

  2. Week 2. Quantify

    Current-state cost modeled per sub-workflow. Baselines anchored to your numbers. Impact projections stress-tested against named risks. Change-readiness assessed.

  3. Week 3. Sequence

    Initiatives prioritized by impact, confidence, and readiness. Named-owner recommendations. 30/60/90 milestones defined. Final readout to leadership.

Sprint outputs

What you leave with

A plan you can execute. A baseline you can measure against.

Every Sprint produces the same structured output set. The result is a plan you can execute and a baseline you can measure against.

  • Sub-Workflow Deep Dive

    Process maps, cost baselines, redesign options, and impact projections with documented confidence levels for each workflow in scope.

  • Workflow Transformation Atlas

    A workflow map and structured inventory with priority scoring across workflow areas in scope. Becomes the input for any subsequent transformation work.

  • Prioritized Sequencing Plan

    Deployment order, dependency resolution, named-owner model, and 30/60/90 milestones. Adopted as your plan of record.

  • Measurement Baselines

    Defined metrics and captured baseline data for each workflow in scope. Without this, transformation outcomes cannot be measured.

  • Acceptance Criteria

    Documented criteria for each deliverable, agreed in Week 1. The basis for the success-based engagement.

  • Final Leadership Readout

    A working session with your AI program lead and ELT to align on the plan of record, named owners, and next steps.

Execution model

Where Workflow Transformation fits in the four-stage execution model

The Transformation Sprint produces the plan, the baseline, and the named owners. Architech then builds the workflows into production using the same architecture, baselines, and acceptance criteria established during the Sprint. Sprint and Build are sold separately. The Sprint stands on its own. The Build follows when the plan is approved.

01

AI Jumpstart

Identify the highest-impact workflow and define the first proof of value.

02

AI Foundations

Establish the security, governance, and data access required for production AI.

03

Workflow Transformation

Convert approved roadmaps into production workflows, measured against baseline.

04

Workflow Activation

Ensure adoption, track performance, and scale proven patterns across the organization.

The Sprint produces the plan. Architech delivers the build that follows.

Fit check

When the Transformation Sprint is the right starting point

Start with a Transformation Sprint when

  • You have an approved AI roadmap but no plan of record

  • AI work has been identified but not deployed into production

  • You need baselines and metrics defined before transformation begins

  • An AI Task Force, working group, or program lead exists to drive plan adoption

  • Capital is available for transformation work but sequencing is unclear

Start somewhere else when

  • You have not yet identified where AI applies. Start with AI Jumpstart

  • Security or data access concerns are blocking AI work. Start with AI Foundations

  • You have a defined plan and validated foundations and are ready to build. Speak with AI Engineering

AI Transformation Sprint

Convert your AI roadmap into a plan of record.

A success-based engagement that produces a deployable plan and the measurement baseline required to execute it.

Contact Information

Context

Need foundations work first?

Explore AI Foundations