Data & AI Governance
Maxxi establishes responsibilities, criteria and controls so data and AI remain reliable, traceable and usable across decisions, processes and products, without separating governance from operations.
When scaling Data and AI requires shared responsibilities and criteria
Governance becomes a priority when adoption grows but the organization can no longer explain who decides, which criteria apply, or how problems and risks are handled.
Decision rights are unclear
Definitions, quality, access and correction move between teams because responsibility and authority are not explicit.
Quality is checked after the impact
Errors are found in reports, campaigns, processes or models after rework and loss of trust have already occurred.
Access and sharing have grown without a standard
Broad permissions, inconsistent criteria and poorly documented exceptions make security, privacy and audits more difficult.
Origins and transformations are not traceable
Teams cannot readily explain where data came from, how it changed or which decisions a problem will affect.
AI advances without a shared decision lifecycle
Models, copilots and agents emerge without an inventory, accountable owners, risk classification or consistent criteria for evaluation, approval, monitoring and change.
Lead with All intelligence in Data and AI
Maxxi connects governance to business priorities, architecture and day-to-day work:
Operating model and responsibilities
Maxxi structures domains, ownership, stewardship, forums, roles and decision rights suited to the organization.
Policies, processes and access
Maxxi defines criteria for use, access, sharing, security, privacy, exceptions and change according to context.
Quality, metadata and traceability
Maxxi connects definitions, critical data elements, glossaries, catalogs, lineage, rules and quality indicators to priorities.
AI lifecycle governance
Maxxi establishes accountable owners and controls for evaluating, approving, monitoring, changing or retiring models, copilots and agents according to use and risk.
Governance embedded in decisions and operations
Depending on priorities, maturity and risk, the structure may include:
A map of priority domains, assets, decisions or AI systems
An operating model, roles, decision rights and forums
Policies, standards, processes and exception handling
A glossary, catalog, lineage and quality criteria
An inventory, risk classification and AI lifecycle controls
Indicators, operating cadences, an implementation plan, adoption and evolution
Define who decides. Embed controls. Govern the evolution
Seven moves connect evidence, decisions and next steps. The depth of each one follows the goal of the work.
1Discover
Decisions, domains, assets, AI uses, owners, quality problems, access, risks and existing controls.
2Plan
Priorities, principles, expected outcomes, accountability model, controls and implementation waves.
3Propose
An operating model, policies, processes, indicators, governance architecture and adoption plan proportionate to the context.
4Develop
Roles, standards, flows, criteria, artifacts and configurations included in scope.
5Activate
Governance applied first to prioritized domains, decisions or systems, with owners prepared to exercise their roles.
6Operate
Forums, indicators, exceptions and responsibilities embedded in the routines of defined owners and the operational teams involved.
7Evolve
Usage, incidents, audits, regulatory change and new use cases guide adjustments to the model and controls.
What sustains the way Maxxi works
Senior expertise that improves decisions
Senior professionals understand the business context and connect executive perspective with technical depth in critical decisions.
Executive oversight that anticipates risk
Maxxi leaders take part in critical moments, bringing benchmarks, options and recommendations to keep priorities aligned and correct course in time.
Outcomes that guide execution
Expected outcomes, timelines, cost and quality guide priorities, indicators and adjustments—not only scope completion.
Knowledge that strengthens internal capability
Maxxi structures knowledge, governance and support to strengthen the client's ability to operate, evolve and scale with confidence throughout the partnership.
Governance applied to decisions, access and quality
AI risks mapped before scaling
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CX 83.6above the industry average of 76.03
ISG Provider Lens 2024See the recognitionWhen the priority calls for another front
Data & AI Assessment
When maturity, gaps, risks and priorities must be diagnosed before the program is structured.
Explore Data & AI AssessmentData Platforms
When the foundation, pipelines and technical components must be built or modernized.
Explore Data PlatformsArtificial Intelligence & Agents
When the priority is to build models, copilots and agents within defined governance criteria.
Explore Artificial Intelligence & AgentsData & AI Operations
When production pipelines, products, models and agents require continuous monitoring and management.
Explore Data & AI OperationsWhat executives need to know about Data and AI governance
What is Data & AI Governance?
It is the organizational capability to define responsibilities, criteria, processes and controls so data and AI systems are used with quality, traceability, security and accountability throughout their lifecycle.
What is the difference between Data Governance and AI Governance?
Data Governance addresses ownership, quality, metadata, access and data use. AI Governance adds responsibilities and controls for purpose, risk, evaluation, approval, monitoring, change and retirement of AI systems.
Who is responsible for governance?
Responsibility is distributed. Executive leadership and Data, AI, business, technology, security, privacy and compliance functions play distinct roles, with owners and stewards close to the domains and decisions they understand.
Does an organization need a governance platform?
Not necessarily at the start. Tools help scale cataloging, lineage, quality, access and evidence, but they do not replace well-defined priorities, roles, criteria and processes.
How can an organization start without trying to govern the entire enterprise?
The starting point may be one domain, decision, critical asset or relevant AI use case. Initial application validates responsibilities and controls before expansion into additional areas.
How is a Data & AI Assessment different from Governance implementation?
The Assessment diagnoses maturity, gaps, risks and priorities. Data & AI Governance establishes and activates responsibilities, policies, processes, criteria and controls across the organization.
Lead with All intelligence in Engineering, Data and AI.
In the conversation, Maxxi assesses domains, decisions, AI uses, responsibilities, quality problems, access, risks and current controls to define where governance needs practical application first.