The EU Artificial Intelligence Act (AI Act) introduces the world’s first comprehensive regulatory framework for artificial intelligence. It defines clear rules for how AI systems are built, deployed, and monitored, focusing on risk management, data governance, transparency, and accountability.
While created in the EU, the Act has global implications.
Any organization offering AI-powered products or services to EU users (or processing EU data) must comply. Like the EU Data Act before it, this regulation reflects a broader trend: governance, safety, and trust are becoming non-negotiable components of modern IT operations.
For IT and Security leaders, this means AI governance is no longer an abstract compliance topic. It’s a core operational priority, requiring orchestration, auditability, and continuous oversight.
Turning AI regulation into action
The EU AI Act divides systems into risk categories, from minimal to high, each requiring specific controls around testing, documentation, and monitoring.
Tines helps organizations operationalize those obligations through intelligent workflows that automate, document, and enforce compliance across the AI lifecycle.
Consequences of non-compliance
The AI Act carries significant enforcement powers and financial penalties for organizations that fail to meet its requirements. Like the GDPR, it introduces a tiered system of fines based on the severity of violations:
Use of prohibited AI systems (such as social scoring or manipulative AI): up to €35 million or 7% of global annual turnover, whichever is higher.
Failure to meet obligations for high-risk AI systems (e.g. around transparency, data quality, or human oversight): up to €15 million or 3% of global annual turnover.
Providing false or misleading information to regulators: up to €7.5 million or 1% of global annual turnover.
Beyond monetary penalties, authorities may suspend or ban non-compliant systems, order product recalls, or restrict market access within the EU.
For organizations, the risks extend further – from reputational damage and loss of customer trust to exclusion from procurement opportunities or partnerships.
In short, compliance isn’t optional; it’s foundational to maintaining both operational integrity and market credibility.
Operationalizing AI compliance with Tines
1. Orchestrate AI governance and risk classification
Tines enables teams to translate regulatory expectations into repeatable workflows that reduce manual effort and human error.
With Tines, organizations can:
Automate AI system classification based on inputs such as data type, purpose, and model usage.
Trigger review and approval workflows before high-risk models are deployed.
Integrate with GRC or ITSM tools like Jira, ServiceNow, etc to record risk scores, compliance evidence, and audit trails.
This approach ensures every model is reviewed, logged, and traceable under the EU AI Act’s risk-based governance framework.
2. Enforce data governance and model transparency
The AI Act places strong emphasis on data integrity and transparency. Tines helps IT and security leaders embed these principles directly into their operations.
Organizations can use Tines to:
Verify data provenance, consent, and residency before it’s used in AI workflows.
Enforce data minimization and traceability rules automatically.
Generate audit-ready documentation that shows where training data comes from, how it’s stored, and who can access it.
Provide automated reporting that supports model explainability and disclosure obligations.
By embedding transparency and control at every step, Tines allows organizations to build trustworthy AI workflows by design.
3. Continuous monitoring and lifecycle auditing
Compliance isn’t a one-time event. The AI Act requires ongoing evaluation of model behavior, accuracy, and bias.
Tines supports this with:
Scheduled reviews of model performance, drift, and fairness metrics.
Real-time alerts when anomalies or non-compliant behaviors are detected.
Automated compilation of audit evidence, giving compliance teams full visibility without manual intervention.
This continuous orchestration ensures AI systems remain accountable, explainable, and aligned with regulatory expectations.
4. Centralize AI risk and compliance evidence
Using Tines as an orchestration layer, organizations can create a single source of truth for all AI compliance activity.
Aggregate risk assessments, approvals, and monitoring data in one secure workspace.
Export standardized compliance reports instantly for auditors or regulators.
Provide real-time visibility to legal, compliance, and executive stakeholders.
This centralization turns compliance from a reactive reporting exercise into a living operational process.
How Tines’ own AI model usage aligns with the EU AI Act
Tines applies the same standards internally that we enable for our customers. Our approach to AI development and deployment is rooted in security, transparency, and accountability; the same pillars outlined in the EU AI Act.
Here’s how we align in practice:
Human oversight: Every model integrated into the Tines platform (including BYOAI and copilots) undergoes formal review and approval. Human-in-the-loop control is maintained for all high-impact features.
Data governance: We use strict data governance controls to ensure no customer data is used to train models without explicit consent. All model interactions follow clear residency and retention rules.
Transparency: We document how models are used, what data they access, and how outputs are generated, ensuring customers can trace and trust every AI-assisted action.
Secure by design: Models run within controlled, auditable environments with encryption, role-based access, and continuous monitoring to detect drift or bias.
Accountability: We treat AI outputs as extensions of workflows. This means every AI decision or recommendation in Tines is logged, reviewable, and reversible.
In short, Tines uses AI responsibly, transparently, and securely, modeling the same operational discipline our platform helps customers achieve.