LG U+ rolls out company-wide AI compliance system under Korea's AI Basic Act
LG U+ has put a company-wide AI management system in place to meet the Artificial Intelligence (AI) Basic Act that took effect on the 22nd. The goal is simple: protect users across services, meet legal obligations, and build trust without slowing product momentum.
What changed inside LG U+
- Full AI service review: The company audited AI across its portfolio, including the "U+one" customer center and membership app, to verify transparency obligations.
- Clear AI labeling: AI-generated outputs will be explicitly indicated so users know when content is produced by AI.
- Updated terms and notices: Terms of use and pre-use notices now make it clear when and how AI is involved.
- Company-wide education: Training for all employees to raise awareness of legal requirements tied to AI use.
- AI risk management system: A cross-functional structure spanning the CTO organization, Information Security Center, and Legal (Justice Office) to oversee compliance from planning through development and operations.
Why this matters for managers
Regulators are raising the bar on transparency and user safeguards. LG U+ is operationalizing that standard: policies, labels, training, and a risk system that spans the AI lifecycle.
This is the blueprint for reducing legal exposure and customer complaints while keeping AI initiatives moving. It's also a signal: governance is now a product requirement, not an afterthought.
Practical checklist you can run this week
- Inventory: List every touchpoint where AI influences user experience or decisions, internal and external.
- Labeling: Mark AI-generated content in-app and in reports. Keep it obvious and consistent.
- Terms and notices: Update ToS, privacy notices, and in-product disclosures to reflect AI usage and data flows.
- Governance group: Stand up a cross-functional committee (Product, CTO/Engineering, InfoSec, Legal, CX) that owns sign-off.
- Lifecycle controls: Add compliance checks at planning, model selection, data prep, testing, launch, and monitoring.
- Risk logging: Track models used, data sources, prompts/policies, known limitations, and mitigation steps.
- Incident playbook: Define how to detect, review, and correct harmful or inaccurate AI outputs.
- Vendor oversight: Require third-party AI providers to meet your labeling, security, and audit requirements.
- Training: Educate teams on legal duties, safe use, and escalation paths. Refresh quarterly.
Metrics to watch
- User complaints tied to AI features
- Time to correct or remove harmful outputs
- Disclosure coverage across products (percent of AI touchpoints labeled)
- Audit findings and remediation closure time
LG U+ says it will keep pushing for differentiated customer value and stronger experiences through AI-while staying inside clear guardrails. That's the balance leaders should aim for: practical innovation, transparent to users, defensible to regulators.
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