Utomo AI Readiness Platform

Make AI readiness
a decision you
can explain.

Connect evidence, professional judgment and implementation priorities in one assessment workspace. Understand what your organization can support, where the gaps are and what it should do next.

Request a demonstration Explore the platform ↓

7: connected dimensions
49: assessment subdimensions
9: engagement stages
6: core deliverables

Actual AI Readiness Platform assessment screen showing reviewed subdimensions and evidence adequacy in a demo project.

Actual platform interface · Demonstration data, not customer results

From assessment to action

A score needs a story behind it.

The useful question is not simply how ready you are. It is what supports that judgment, which conditions are holding you back and what would make an investment worth pursuing.

The platform supports a consultant-led engagement from evidence collection to leadership discussion. It connects assessment findings with use cases, risks, roadmaps and reviewed outputs, giving teams a traceable basis for recommendations.

01
Establish context
Define the objectives, scope and decisions the assessment should inform.
02
Build the evidence
Review documents and interviews, record findings and assess readiness.
03
Shape priorities
Compare use cases and risks, then sequence the work required to move forward.
04
Review the decision
Prepare versioned outputs for quality review, approval and an executive conversation.

Inside the platform

Follow the evidence through to the next step.

Explore six actual screens from the demonstration engagement.

Give the engagement a shared direction.

Keep the assessment objective, scope, sponsor, team and methodology stages in view. A common project record connects the work to the decision the organization needs to make.

AI Readiness demo project overview showing assessment scope, team and methodology stages. — Project overview · Demo engagementView full-size screenshot ↗

The organization, accounts, figures and records shown belong to the training scenario described in the assessment guide. They illustrate the workflow and are not evidence of customer outcomes or completed quality approval.

The readiness framework

Seven dimensions. No isolated answers.

Each dimension contains seven subdimensions. Together, they connect organizational intent with the conditions required to deliver responsible value.

D1Business Strategy & Objectives: Connect AI ambitions with business objectives, sponsorship and a clear reason to invest.
D2Process & Use Case Opportunity: Understand the work, the problem and the opportunities where AI could make a meaningful difference.
D3Data Readiness: Examine whether the necessary data is available, usable and supported by appropriate access and rights.
D4Technology Readiness: Consider the architecture, infrastructure, integration and operating capabilities needed for delivery.
D5People & Organization: Assess skills, ownership, ways of working and the organization's capacity to adopt change.
D6Governance, Risk & Compliance: Bring accountability, risk, controls and relevant obligations into adoption decisions.
D7Value, Feasibility & Roadmap: Bring the findings together to prioritize opportunities, test feasibility and plan measurable next steps.

The engagement

A clear path from first question to final discussion.

Stages 01–02

Align the engagement

Confirm the business question, sponsor, scope and working arrangements.

Pre-engagement
Kick-off

Stages 03–06

Understand the organization

Build and test the evidence, identify opportunities and review the readiness judgments.

Document review
Stakeholder interviews
Opportunity workshop
Readiness scoring

Stages 07–09

Prepare the next decision

Compare the options, sequence the work and bring reviewed recommendations to leadership.

Use-case prioritization
Roadmap development
Final report & presentation

What the work produces

Six connected outputs for a practical next step.

The engagement brings findings into formats that support working teams and decision-makers. Outputs move through versioning, quality review and approval.

AI Starter Assessment Report

An integrated account of the context, evidence, findings and recommendations.

AI Readiness Scorecard

A structured view of readiness, supported by reviewed judgments and evidence adequacy.

Use Case Matrix

A comparison of opportunities, their enabling conditions and recommended priorities.

AI Risk Register

A record of identified risks, controls and the matters that need further attention.

Implementation Roadmap

Sequenced actions across workstreams, with owners, dependencies and decision points.

Executive Presentation Deck

A concise decision narrative for sponsors and leadership discussions.

Human judgment, clear responsibilities

Review is part of the work.

Defined responsibilities

Project managers coordinate the engagement; dimension consultants develop assessments; lead consultants review judgments. Quality review and final approval have distinct responsibilities.

A living evidence trail

Evidence versions, findings and output snapshots keep recommendations connected to their sources. When sources change, affected deliverables need attention before approval.

AI assistance by choice

The optional AI Copilot requires project opt-in and written client consent. Assessment ownership, review and final decisions remain with the responsible people.

A useful first conversation

Start with the decision you need to make.

Which AI opportunities deserve investment? What needs to improve first? What should a pilot prove before you scale?

Bring your objectives, candidate use cases and assessment context. We can demonstrate how evidence, readiness judgments and priorities connect, then discuss the engagement scope and deployment requirements.

Discuss your assessment