LG Ad Solutions launches Agentiv: AI agents for CTV advertising operations
LG Ad Solutions introduced Agentiv on October 30, 2025 - an AI platform built to run internal and client-facing agents that speed up campaign planning, approvals, measurement, and collaboration across Connected TV. The Mountain View team positions it as common infrastructure for deploying agents across multiple business functions, not a single feature bolted onto ad tech.
According to CTO Dave Rudnick, the company has invested heavily in the data layer needed to deploy AI responsibly across advertising workflows. Agentiv already runs 20+ agents inside the organization, supporting planning, creative, and operations teams.
What Agentiv actually does
Inside the platform, you'll find a media planning agent that turns campaign inputs into feasibility summaries and a creative review agent that helps move ad approvals faster. The point: compress time-to-decision without skipping compliance or quality checks.
- Natural language queries: Ask plain-language questions and pull campaign data without building manual reports.
- Persona-based permissions: Tiered access for advertisers, agencies, and partners to see only what's relevant.
- Clean room integration: Privacy-first data collaboration for shared insights and matched audiences.
- Optimization support: Ongoing performance analysis to inform pacing and creative changes mid-flight.
Why the architecture matters
Agentiv leans into privacy-preserving collaboration that's become standard in 2025. Measurement and audience workflows are moving into clean rooms, with platforms like Snowflake and identity providers expanding partnerships and tooling.
NIQ launched a global clean room on Snowflake for ad measurement, and LiveRamp extended capabilities that let retail media networks evaluate Meta campaigns against first-party sales. Expect Agentiv's clean room routes to sit alongside this broader movement toward secure data joins and accountable measurement.
For context, see Snowflake and the IAB for standards and ecosystem updates.
Beta program: what's included first
LG Ad Solutions plans a limited beta with select advertisers. The first feature: a data collaboration agent that lets brands combine their first-party data with LG Ad Solutions' insights in a privacy-compliant environment to guide audience identification and campaign evaluation.
This mirrors how CTV platforms typically roll out measurement products: controlled testing, defined use cases, then broader availability.
Industry context you can't ignore
Programmatic growth hit 72% in 2025. CTV's slice of media budgets is projected to double from 14% in 2023 to 28% in 2025, making workflows and measurement harder to manage without automation.
The IAB reports 86% of buyers use or plan to use generative AI for video creative. Brands are versioning assets by audience, style, and context - work that used to soak up time and budget.
CTV ad spend in the U.S. is projected to reach $46.9B by 2028, edging past traditional TV at $45.1B. With that shift comes pressure for clearer ROI and faster optimizations.
On the competitive front, Magnite acquired streamr.ai to make creative generation and CTV setup accessible for SMBs. The signal is obvious: the market wants AI that reduces setup friction and cost, not just dashboards.
What Marketing and Operations leaders should do now
- Audit first-party data: Resolve IDs, confirm consent coverage, and map how your data will be activated in a clean room. Define allowed joins and retention rules.
- Choose high-impact agent use cases: Start with feasibility checks, pacing and under-delivery alerts, creative QA, and budget approval workflows.
- Mirror your org in permissions: Translate your existing roles into persona-based access. Decide what agencies, partners, and finance see by default.
- Lock in measurement: Define incrementality tests, conversion windows, holdouts, and when to trigger creative swaps. Automate weekly normalization and anomaly flags.
- Set creative guardrails: If you use generative tools for video, codify brand rules, disclaimers, rights management, and final human review.
- Standardize taxonomy: Name campaigns, deals, audiences, and assets consistently. Agents are only as good as the labels they read.
- Governance and logs: Keep prompt and decision logs, change histories, and approvals. You'll need an audit trail for finance and legal.
- Pilot with intent: Pick one market, one objective, and 2-3 KPIs. Define "stop/go" rules before kickoff and schedule a post-mortem with next-step owners.
Sample Agentiv-style workflow
- Brief intake: Agent produces feasibility and inventory fit based on goals and audience signals.
- Creative checks: Agent reviews specs, brand safety, and compliance; flags assets for fixes.
- Data collaboration: Clean room match on first-party segments; audiences approved by legal.
- Launch and monitor: Agent watches pacing, frequency, and on-target rates; recommends shifts.
- Optimize: Swap creative variants, rebalance supply paths, and test bidding strategies.
- Report out: Agent assembles performance, incrementality reads, and learnings for the next cycle.
Questions to ask your vendor (and yourself)
- Which data sources power the agents, and how are they validated?
- How do persona-based permissions map to my teams and partners?
- What's the clean room path (match rates, latency, join types, retention)?
- What gets automated on day one vs. month three? Show me the workflow map.
- What audit logs exist, and who can access them?
- How are optimization recommendations tested before they touch live spend?
The takeaway
Agentiv pushes CTV operations toward agent-driven planning, approval, collaboration, and optimization. If you're moving more budget into streaming, your advantage won't come from another dashboard - it'll come from cleaner data, clear permissions, and agents tied to real business outcomes.
If you're upleveling your team's skills for AI-driven marketing ops, explore our practical programs for marketers: AI Certification for Marketing Specialists.
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