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The 2026 State of CX Outsourcing
The Gist
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Integrated AI orchestration. Treasure Data introduces a multi-agent AI marketing system for unified strategy and execution.
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Enterprise-focused design. Platform-agnostic solution aligns with martech stacks and future data needs.
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CMO workflow impact. CMOs and marketing teams gain streamlined campaign planning and execution within a governed enterprise workspace.
Treasure Data is betting that enterprise marketers want AI agents that work together, not another disconnected point solution. And they are betting so big on agentic AI and marketing they changed their flagship conference name from CDP World to Agentic World.
On Jan. 12, the company launched Marketing Super Agent, a multi-agent AI system built into its AI Marketing Cloud. According to company officials, the product handles identity-informed audience intelligence, strategy, creative, activation and real-time optimization within a governed enterprise workspace.
The system is powered by a Super Agent Orchestrator that dynamically assembles specialist task agents for functions including deep research, sentiment analysis, persona creation, competitor intelligence and channel-specific ad generation. Treasure Data asserts that every AI agent collaborates through a live in-session memory layer, enabling context awareness and explainable reasoning chains.
Designed to be platform-agnostic, Marketing Super Agent aims to support any martech stack. Qualified companies can request access to the product.
Table of Contents
- Why Treasure Data Built Marketing Super Agent
- Treasure Data's Super Agent World
- Market Context: Enter the Marketing Agent
- Marketing Agents That Act Like Marketers
- From Campaign Planning to Execution
- Treasure Data Background
Why Treasure Data Built Marketing Super Agent
In an interview with CMSWire, Treasure Data leaders said Marketing Super Agent was built in response to a fragmented enterprise marketing environment where AI capabilities exist, but workflows remain scattered across tools, teams and internal silos.
Rohan Ranjan, head of product marketing at Treasure Data, pointed to market saturation and tool sprawl as core challenges facing enterprise marketing teams.
“If you think about the current state of marketing, there's a lot of legacy tech vendors, there's a lot of advancement,” Ranjan said. “If you look at especially in the CDP space right now, everyone's trying to add agentic capabilities to do better audience exploration. Better emails and better campaigns. But essentially, it's been largely static. There's been a lot of entrants to the market. I'd say even in the CDP industry, there are over 200 competitors now, and it's getting really hard to kind of differentiate yourself. And there's a lot of fragmentation; companies have so many tools in their tech stack, especially in the marketing side.”
Ranjan said the company saw an opportunity to move beyond isolated AI features and instead apply agentic AI to coordinate real-world marketing processes that already exist inside enterprises.
“How can we use agentic AI to move beyond just the agents being able to automate a lot of tasks and start to actually reason and execute what already exists?” he said.
The result, he explained, is a system designed to act as a control layer across marketing strategy, planning and execution — without requiring enterprises to rip and replace their existing martech investments.
Related Article: Treasure Data Unveils AI Marketing Cloud and 'Super Agent' Vision at CDP World 2025
Treasure Data's Super Agent World
In April 2025, Treasure Data appointed Rafael Flores as chief product officer to lead its next phase of AI-driven CDP innovation. At CDP World in October 2025, the company unveiled its AI Marketing Cloud and previewed its "Super Agent" concept. In December at AWS re:Invent, Treasure Data made its full product portfolio available through AWS Marketplace.
Founded in 2011 and headquartered in Mountain View, Calif., Treasure Data operates globally with offices in Japan, South Korea, the United Kingdom and France, serving enterprise customers including Anheuser-Busch InBev, Subaru, Nestlé, Stellantis and Yum! Brands. In August, Forrester named Treasure Data a Strong Performer in its B2B CDP Wave.
Market Context: Enter the Marketing Agent
Multi-agent AI orchestration has hit an inflection point as enterprises consolidate vendors to unify data and eliminate disconnected tools.
Human-in-the-Loop, Not Autonomous Marketing
In the interview with CMSWire, Treasure Data leaders stressed that Marketing Super Agent is designed to augment marketers — not operate independently without oversight.
Ranjan described the platform as intentionally collaborative, with humans approving, adjusting and guiding AI-driven workflows at every stage.
“We’re not saying, 'Hey, this is going to go automatically do everything,'” he said. “I think humans still need to approve of every step. So essentially, what it will do is it will create a plan of what agents it's going to use for one particular task, based off of your prompt, get approval, ask for suggestions, and then the person plus the AI will work together to actually modify the steps.”
The system generates a structured execution plan based on marketer intent, then asks for confirmation, clarification or deeper analysis before proceeding. Marketers can decide whether to move quickly or conduct more extensive research before campaigns are activated.
Ranjan said the goal is controlled acceleration — reducing cycle times without removing human judgment from enterprise marketing decisions.
Key Adoption Drivers for AI in Marketing
Organizations are embedding AI-powered analytics and automation into marketing operations at scale. Sixty percent of marketers now use AI daily, with nearly one in five departments allocating 40% or more of their budgets to AI initiatives.
Technical Prerequisites for AI in Marketing
Enterprise deployment follows three distinct tiers:
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AI infrastructure for scaled training and inference
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AI models for content creation and application development
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Packaged agents for customer service, cybersecurity and industry-specific applications
Nearly 70% of companies investing in conversational AI are simultaneously updating customer data strategies. Deep integrations with customer data platforms, CRM and digital experience platforms have become table stakes.
Reported Outcomes for AI in Marketing
Organizations deploying AI-powered analytics reported up to 25% increases in customer satisfaction alongside significant cost reductions. Companies excelling in personalization deliver 15% higher total shareholder return, according to BCG research.
Marketing Agents That Act Like Marketers
CMOs have been promised 'AI transformation' but offered point tools and copilots that don't understand their business. Marketing Super Agent is the first AI system that behaves like a real marketing organization: strategic, smart, and built natively inside the data foundation that CMOs trust.
- Kazuki Ohta, CEO and co-founder
Treasure Data
Marketing Super Agent Feature Breakdown
Marketing Super Agent includes day-one capabilities across three functional areas, according to Treasure Data.
| Capability | Description |
|---|---|
| Strategy | Identity-informed research, competitive intelligence, persona modeling, and brief development grounded in unified customer profiles |
| Creative | Data-informed campaign concepting, personalized ad copy creation, and platform-specific creative aligned to audience intent and lifecycle stage |
| Execution | CDP-native email and journey creation, audience activation across channels, and real-time orchestration powered by governed customer data |
From Campaign Planning to Execution
Treasure Data executives told CMSWire Marketing Super Agent is designed to move beyond planning and ideation into direct campaign execution — all within the same governed environment.
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Ranjan said the system is built to generate and activate assets across channels without forcing marketers to switch platforms.
“We are going to orchestrate end to end. It will generate the Instagram ads. It will generate your hero banners for your website,” he said.
Treasure Data interim CMO Karen Wood said this orchestration layer is intended to deliver measurable business outcomes by compressing time-to-market and improving campaign performance.
“The intention is all the benefits that Rohan mentioned — improve speed to market, and improve the speed of campaigns, and improve campaign results, ROI, revenue,” Wood said.
Both executives emphasized that the current launch represents the first phase of a longer roadmap, with deeper integration into customer data, journey orchestration and execution tools planned throughout the year.
Treasure Data Background
Treasure Data targets marketing, analytics and customer experience leaders at large B2C enterprises, particularly those with complex, multi-brand operations.
The platform is positioned as an enterprise-grade, AI-powered Customer Data Platform (CDP) that centralizes first-, second- and third-party data into a unified customer record. It offers real-time data streaming, AI-driven personalization and broad integration with marketing, sales, service and operations systems.
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