Data and AI Governance

Your data is a strategic asset. So are the AI systems it feeds. Make sure both are trusted, governed, and performing to their full potential.

Trusted by

I highly appreciate the quality of work provided by Adastra consultants and would recommend them to executives and companies willing to increase their data governance maturity.

Martin Novak

Head of BI, Sazka

Avast highly appreciates the results of cooperation with ABC and recommends utilizing ABC’s expertise in data governance for the development and implementation of data strategies.

Miroslav Umlauf

C.D.O., Avast

ABC team’s effort has helped us formalize the concept of data use in Eurowag (for both technical and non-technical users) and increase the overall data governance maturity and data literacy level in the company.

Vaclav Dorazil

VP of Data & Digitalization, Eurowag

Make Data and AI Trustworthy for Decisions, Reporting, and Automation

Organizations that treat data and AI as strategic assets outperform those that don’t. But without clear ownership, consistent definitions, and embedded controls, both data and AI systems introduce risk rather than reducing it.

Adastra establishes clear accountability across data and AI, aligns definitions across management, regulatory, and operational needs, and builds governance into how your organization works. Not as a separate layer but as a natural part of how data is managed and AI systems are developed, deployed, and monitored. This includes compliance with data and AI regulations such as GDPR, NIS2, EU AI Act, and EU Data Act.

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Up to 35%

gain in operational efficiency through data and AI governance implementation

25%

Increase in staff productivity with proper data governance in place

By 2027

AI governance will be required by all sovereign AI laws and regulations worldwide (Gartner, 2025)

Why Adastra as Your Business Consulting Partner

We don’t just advise, we deliver. Combining business insight, data expertise, and AI-driven technology in one team, we design, build, and run solutions that create real impact from day one. With 1,000+ engagements across the globe, deep local knowledge, and a wide network of technology and business partners, we deliver flexible, integrated solutions tailored to your business.

20+

years delivering business & IT consulting projects

2200+

experts with business, data & AI experience globally

40+

countries where we delivered projects

Ready to Strengthen Your Data & AI Governance?

Connect with Adastra experts to evaluate your current governance maturity, identify critical gaps, and define clear, practical steps to improve data ownership, AI oversight, regulatory compliance, and operational control.

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How Adastra Establishes Effective Data and AI Governance

For over 25 years, Adastra has helped organizations design and operationalize governance frameworks that ensure data is reliable and AI is controlled, transparent, and accountable.

Our methodology combines the Adastra 4P Framework, DAMA-DMBOK standards, the AIGA AI Governance Framework, and the TASMAS methodology to deliver governance that is holistic, practical, and built to last.

Data and AI Governance Assessment and Strategy

Assess maturity using Adastra’s 4P Framework and DAMA/AIGA benchmarks. Define a prioritized governance roadmap aligned with business strategy and data monetization goals.

Data Management and Quality

Define domains, owners, and decision rights. Implement data quality, master data, metadata, and reference data management with embedded policies, processes, privacy, and security controls.

AI Governance and Lifecycle Management

Govern AI from use case definition to production monitoring, including GenAI/LLM, agentic AI, and third-party AI tools. Ensure risk classification, validation, version control, bias prevention, and clear ownership.

Governance Operating Model and Accountability

Design the target operating model with defined roles, RACI structures, escalation paths, KPIs, and governance reporting. Set standards for responsible AI use, transparency, explainability, fairness, and human oversight.

Governance Platform Selection and Implementation

Select and implement governance and AI lifecycle platforms. From data catalogues and metadata tools to AI model registries, quality monitoring, and reporting systems.

Data and AI Literacy, Training, and Managed Support

Deliver literacy programs, role-specific training, and change management. Data-Office-as-a-Service for organizations needing continuous governance operations.

Adastra’s Path to Well-Governed Data and AI

Adastra follows a proven approach that moves from assessment to enterprise-wide rollout. The pace and scope are tailored to each organization’s maturity and priorities.

Phase I

Data and AI Governance Assessment

Maturity assessment report
Gap analysis and recommendations
Maturity benchmarks
Technical landscape and architecture assessment

Phase II

Use Cases and Business Requirements

Business requirements
AI use cases list and prioritization

Phase III

TO-BE Design and Platform Selection

Data & AI strategy and target operating model
Governance framework
AI use cases design with business cases
Policies and processes catalogue
Governance artifacts library
Tooling specifications
Enterprise data & AI architecture design

Phase IV

Implementation Roadmap

Implementation roadmap
Change management and adoption program
Policies and processes design
Platform and infrastructure design
Tooling selection and implementation
AI governance artifacts
Data & AI literacy and organizational upskilling

Phase V

Proof of Concept and Validation

Governance validation on pilot use cases
MVP on data domain
Proof of concept execution and validation
AI use cases prototyping

Phase VI

Company-Wide Rollout

AI platform deployment
AI use cases scaling and rollout
Data domains rollout

Grounded in Proven Frameworks, Built for Operational Results

We don’t deliver reports that sit on shelves. Adastra’s governance methodology focuses on introducing real-world practices. Grounded in Adastra’s 4P Framework, internally recognized DAMA-DMBOK, and AIGA. All applied through hands-on analysis of your data, your systems, and your organization, both on-site and off-site.

Adastra 4P Framework: People, Policies, Processes, Platform

Ensures governance is holistic and practical. Addressing all four pillars together is the only way to move beyond theory and design governance that is truly operational, sustainable, and embedded in day-to-day business.

DAMA Wheel and Adastra's Data Governance framework.

DAMA-DMBOK: Data Management Framework

A globally recognized framework that defines the core principles, best practices, and essential functions of data management, independent of technology. It guides Adastra’s approach from planning through implementation to operational processes.

AIGA: AI Governance and Auditing Framework

The AIGA Framework defines how AI is designed, developed, deployed, and monitored responsibly and at scale. It sets policies, processes, assigns accountability, and aligns data, compliance, cybersecurity, DevOps, and risk functions to ensure AI investments deliver value while minimizing operational, legal, and ethical risks.

Success Story

NLB Scales AI Agents with Enterprise Agentic AI Platform

NLB partnered with Adastra to deploy an enterprise agent platform with standardized design, approval workflows, and controls, enabling safe, scalable AI across departments with predictable costs and full traceability.

months to AI platform and first use case productization

80%

lower time and cost to implement AI use cases

100%

data security, auditability and traceability

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Success Story

Adastra Helped a Leading Bank Optimize Operations and Implement New Data Management Concept

Our client wanted to enhance data-driven decision-making, optimize resource utilization, and ensure the data across all systems is trusted, accessible and understood.

Adastra implemented a tailored data governance program that enhanced data management operations.

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Data and AI Governance FAQ

Where do data and AI governance engagements usually start?

Most engagements start with a concrete issue: disputed management reports, regulatory findings, shadow IT appearing, audit questions, or inconsistent KPIs across systems. We begin by identifying what data and AI systems matter most and why trust has broken down.

Why must governance cover both data and AI?

Data governance is the foundation for AI governance. AI is only as reliable as the data it uses, while ungoverned AI introduces risks related to bias, transparency, accountability, compliance, and security.

Without governed data and AI-specific controls, organizations face quality issues, model risks, integration challenges, cybersecurity exposure, and difficulty proving ROI.

Adastra treats data and AI governance as one continuum, extending existing governance foundations into the AI era through shared policies, roles, and standards, while helping organizations align with evolving regulations such as the EU AI Act, GDPR, NIS2, and sector-specific requirements.

How is this different from traditional data and AI governance programs?

Traditional programs focus on policies and tooling. Adastra focuses on ownership and execution; clarifying who is accountable, aligning definitions across reporting and systems, and embedding controls into how data and AI systems are produced and used.