Why AI Governance Must Live in IT, Not Just Legal
Source: Dev.to
Introduction
AI governance is no longer a policy exercise; it is an operational reality. As enterprises scale generative AI across products, workflows, and customer interactions, governance is shifting away from ethics‑only or legal‑only ownership. Recent analysis from Technology Radius shows that organizations are realizing AI risk behaves more like cybersecurity risk than regulatory paperwork, prompting a change in who owns AI governance.
Traditional Ownership
Who Managed AI Governance Historically?
- Legal teams
- Compliance officers
- Ethics committees
Primary Focus Areas
- Regulatory alignment
- Responsible use principles
- Risk disclosures
This model assumed AI systems were slow, contained, and predictable—an assumption that generative AI quickly invalidated.
Why IT Ownership Is Needed
New Realities of Generative AI
- Prompts evolve daily.
- Models update silently.
- Data flows across tools, APIs, and clouds.
Risk now emerges at runtime, not during review. Policies alone cannot keep up.
Technical Challenges Requiring IT Expertise
- Prompt injection attacks
- Data leakage through AI responses
- Unauthorized model access
- Shadow AI usage by employees
- Integration risks across SaaS tools
These issues demand visibility into systems, logs, permissions, and usage patterns—capabilities that reside within IT and security functions.
Consequences of Missing IT Ownership
Without IT involvement, governance becomes reactive, surfacing only after something breaks. AI now behaves like:
- A production system
- A data processor
- A security endpoint
Thus, it squarely falls under the domain of:
- CIOs
- CISOs
- Enterprise architects
- Platform engineering teams
Benefits of IT‑Driven Governance
When governance moves into IT, it becomes actionable—a control layer rather than just a document.
What IT Can Deliver
- Visibility into who is using which AI tools
- Insight into what data is being shared
- Monitoring of how outputs are generated
- Prompt filtering
- Access management
- Role‑based usage policies
- Always‑on logging
- Automated alerts
- Audit‑ready trails
Organizational Advantages
- Reduced friction for teams
- Clear guardrails
- Fewer last‑minute compliance blocks
- Governance as an enabler, not a bottleneck
Collaborative Roles
The shift does not sideline legal or ethics teams; instead, roles evolve:
- Legal defines policy, risk thresholds, and regulatory interpretation.
- IT enforces those policies through systems and tools.
- Security ensures controls stay effective over time.
Governance becomes collaborative, but execution lives where the systems live.
Risks of Excluding IT
Organizations that keep AI governance outside IT face real risks:
- Undetected data exposure
- Inconsistent AI behavior across teams
- Inability to prove compliance
- Delayed response to incidents
- Loss of trust—both internally and externally
Conclusion
Generative AI is no longer a side project; it is infrastructure. Infrastructure governance has always belonged in IT. Companies that recognize this will scale AI faster, safer, and with far fewer surprises.