01
The first use case is chosen too casually
Teams pick the most visible idea before testing whether the data, owner, process, and business case are ready.
AI Strategy & Roadmap
Build an AI roadmap that leads to real delivery.
Sphere helps teams move from scattered AI ideas to a prioritized roadmap, a readiness view, and a first pilot that is scoped for production from the start.
Use case priority mapImpact × readiness
Start hereBusiness impact
Sales follow-up automation
Support knowledge assistant
High-value but not ready
Low-priority experiment
Feasibility and data readiness
1-2 daysRoadmap workshop option
3-4 weeksFull roadmap and readiness assessment
Vendor-neutralNo forced commitment to one model or platform
Pilot-readyRoadmap ends with the first build scoped
Where AI plans usually stall
The issue is not a shortage of AI ideas.
Most organizations already have more AI ideas than they can execute. The harder part is deciding which ideas deserve investment, which ones are not ready, and what needs to happen first.
See prioritization
02
Ownership is unclear after kickoff
A pilot gets sponsorship for the first meeting, but not the decision rights, budget path, and delivery owner needed to ship.
03
Readiness is assumed instead of checked
Data, access, compliance, and integration gaps show up during the build instead of being identified before investment.
04
The roadmap stops at a presentation
The plan looks good in a meeting, but there is no scoped pilot, delivery sequence, or handoff into execution.
How Sphere prioritizes
Every candidate use case gets scored before it gets sequenced.
Sphere evaluates each opportunity against business impact, feasibility, data readiness, governance needs, and delivery complexity. The goal is to select the right first pilot, not just the loudest idea.
Start hereBusiness impact
Sales call follow-up
Knowledge assistant
High-value but data is not ready
Nice-to-have experiment
Feasibility and data readiness
Start with high-impact, high-readiness work.
These projects have enough business value, data access, ownership, and operational clarity to move quickly into a scoped pilot.
Hold high-value ideas that are not ready yet.
Some ideas are worth pursuing, but only after data, governance, integration, or change-management gaps are addressed.
Cut low-value experiments early.
The roadmap should help teams say no, not just add more ideas to a backlog.
What a useful roadmap produces
A first pilot with a clear business case.
The strongest roadmap does not end with a generic list of opportunities. It ends with a practical first move.
PetroLedger · Financial Services
Preserving institutional knowledge before it walked out the door.
Sphere prioritized a generative AI onboarding platform as the first deliverable because it had a clear business case, identifiable source knowledge, and a measurable operational outcome.
Before
Experienced staff held critical process knowledge, and new hires absorbed it slowly through shadowing and trial and error.
After
The prioritized roadmap moved directly into a production build that improved onboarding speed and preserved institutional expertise.
120%faster new-hire ramp-up after launch
$1.2Mannual savings tied to the deployed system
Why the guidance is practical
Sphere’s AI roadmap approach is built around delivery realities: data access, workflow fit, governance, ownership, and what can actually move into production.
Strategy and engineering stay connected from the first workshop.
Step 1
Identify the business outcomes leadership cares about most, not just the tools teams want to test.
Step 2
Score use cases against readiness and execution risk before money is committed to a pilot.
Step 3
Scope the first pilot with success measures, source systems, security needs, and delivery ownership defined.
How the engagement runs
Four steps from AI ambition to an executable plan.
The roadmap is built to reduce ambiguity, expose readiness gaps early, and create a clear bridge from strategy to delivery.
Discover
Map current initiatives, business goals, candidate use cases, stakeholders, and delivery constraints.
Prioritize
Score each use case against business impact, feasibility, data readiness, and governance requirements.
Validate
Confirm the data, access, integrations, owners, and compliance needs behind the top candidates.
Scope
Deliver a sequenced roadmap and a first pilot ready to move into build with clear success measures.
Choose your starting point
Start with the depth that matches where your team is now.
Some teams need a fast prioritization session. Others need a deeper readiness assessment before they commit to the first production pilot.
Focused
Roadmap workshop
A structured session to map candidate use cases, score priorities, and identify the first practical area to explore.
1-2 daysFixed scope
Book workshopMost useful
AI readiness and roadmap assessment
Prioritization plus a readiness check across top use cases, ending with a sequenced roadmap and scoped first pilot.
3-4 weeksFirst pilot scoped
Start assessmentExecution path
Roadmap into AI Foundry
Move the top-priority use case directly into delivery with the engineering, data, and governance work already framed.
Build-readyFoundry handoff
Plan deliveryQuestions before you start
Clear answers before the first workshop.
AI strategy defines the business outcomes AI should support. An AI roadmap turns that strategy into a sequenced set of use cases, readiness checks, delivery steps, and a scoped first pilot.
A focused workshop can run in 1-2 days. A deeper roadmap and readiness assessment typically runs 3-4 weeks, depending on the number of use cases and systems involved.
No. The roadmap should be vendor-neutral. Sphere prioritizes use cases, data readiness, governance, and delivery requirements before committing the plan to a specific model or platform.
The roadmap includes a scoped first pilot that can move into delivery through Sphere AI Foundry, an embedded engineering pod, or a client-led build with Sphere support.
The roadmap is built with delivery in mind. It scores use cases against data readiness, business impact, governance needs, and implementation complexity so the plan can move into build.
Turn AI ideas into a roadmap your team can execute.
Start with a workshop, a readiness assessment, or a direct path into a scoped first pilot.
Let's build your AI roadmap
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