Maria Sergeeva
AI & Data Governance Advisory
AI without governance is a management risk.
AI initiatives are moving faster than governance structures — without clear ownership or accountability.
Independent. Executive. Uncompromising.
I bring clarity, control, and accountability to AI and data — at management and board level. Before regulators, risks, or complexity take over.
At management and board level, this creates immediate risks:
– Decisions based on AI outputs that are not fully understood or challenged
– Unclear accountability for data quality, AI models, and decision ownership
– Regulatory requirements not translated into operating models
The result: financial exposure, regulatory risk, and reputational damage.
Most organizations recognize these gaps only when critical decisions have already been made.
What I do
I provide independent, high-impact assessments and advisory at the intersection of AI, data, and governance.
My work focuses on:
– AI governance readiness (EU AI Act)
– Data accountability and ownership models
– Risk and control structures for AI and data
– Independent audit assessments for management and boards
Who I work with
I primarily work with:
– Mid-sized and large organizations navigating AI, data, and regulatory complexity
– Management, board, risk, and internal audit functions
– Organizations where AI governance, accountability, and operating structures are becoming business-critical
My focus is on organizations that require independent evaluation, executive-level clarity, and governance structures that hold under regulatory and operational pressure.
Why me
19+ years across data, governance, and audit in complex organizational environments.
My background in physics shapes how I approach systems, risk, and decision-making — analytical, structured, and focused on root causes rather than surface symptoms.
I have worked across data, IT, audit, and business functions — leading data management initiatives, governance structures, and risk-based assessments.
Independent.
Governance often fails because organizations assess themselves through the same structures responsible for delivery. Independent evaluation creates transparency where internal interests, operational pressure, or organizational politics can distort decision-making.
Executive.
AI governance failures do not remain technical issues.
They become management, accountability, regulatory, and reputational risks.
Uncompromising.
Effective governance requires clear accountability, critical challenge, and the willingness to address uncomfortable structural weaknesses before they escalate.
I don’t implement systems.
I provide clarity, structure, and critical challenge at the level where decisions matter.
Selected experience:
Leadership responsibility for global data management and governance structures within large international corporate environments
Work in organizations with complex cross-functional structures, global operations, and large-scale data landscapes
Experience across data governance, audit, finance, reporting, and operational decision environments
Responsibility for data quality, governance operating models, and management-relevant reporting structures
Involvement in audit and control environments requiring risk-based assessment, accountability, and regulatory alignment
Close collaboration with management, audit, and business stakeholders in organizations operating at international scale