By Joe Nguyen, Senior Strategic Advisor, H+

For years, we've been hearing about the transformative power of AI, often framed in terms of digital assistants, chatbots, and recommendation engines. These tools, while useful, have been largely passive. They wait for our command, execute a single task, and then stop. They are a tool, a very powerful one, but still just a tool. But what if AI could go beyond being a mere assistant? What if it could become a proactive agent, capable of not just executing tasks but also orchestrating a series of them, making decisions, and even adapting its approach to achieve a larger goal?

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This is the promise of agentic AI. It represents a significant shift in how we interact with and utilize artificial intelligence. Unlike traditional and generative AI models that are designed to perform a specific function in response to a prompt (e.g.,"create a picture of a dog," "summarize this document"), an agentic AI is built to take an objective and independently figure out the steps required to accomplish it.

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Think of it like this: A traditional AI model is a talented chef who can cook any dish you ask for. You give it the recipe, and it follows the instructions to the letter. An agentic AI, on the other hand, is a world-class restaurateur. You tell it you want to open a five-star restaurant, and it will autonomously handle everything from finding a location and hiring staff to designing the menu and marketing the business—even if it has to learn new skills along the way.

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The AI Evolution: From Reactive to Proactive

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To truly understand the power of agentic AI, it's helpful to see how it fits into the broader evolution of artificial intelligence.

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1. Traditional AI/ML: The Rule-Follower

Traditional AI and Machine Learning (ML) systems are the foundation. They're built for structured problem-solving and pattern recognition. Think of a spam filter that follows a specific set of rules or a product recommendation engine that learns from your past purchases. These systems are fantastic at what they do, but they're reactive—they need a clear input to produce a single, predictable output. They operate within the bounds of their pre-programmed rules or the data they were trained on.

2. Generative AI: The Creative Assistant

Generative AI marked a major leap forward. Instead of just analyzing existing data, it creates new, original content, including text, images, and code. Tools like ChatGPT and Midjourney can generate text, images,and code from a simple prompt. While incredibly powerful and versatile, this type of AI is still largely a creative assistant. It's a single tool that you use to perform a single task at a time—it doesn't have a long-term memory or the ability to plan its own multi-step actions to accomplish a larger goal.

3. Agentic AI: The Strategic Partner

Agentic AI is the next frontier. This isn't just a model; it's a system with a high degree of autonomy. You give an agentic AI a complex objective, and it figures out the necessary steps on its own. It can orchestrate a series of tasks, use different external tools (like search engines or other APIs) to gather information or perform actions, and even self-correct if a plan goes wrong. It's a proactive, goal-oriented system that can manage an entire project from start to finish.

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How Does Agentic AI Work?

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The core of agentic AI is a multi-step process that allows it to operate with a degree of autonomy. While the specific architecture can vary, it generally includes three key components:

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1. Planning and Goal Setting: An agentic AI starts by breaking down a high-level goal into a series of smaller, manageable steps. It's like creating a project plan for itself, identifying dependencies and potential roadblocks. For example, if the goal is to "write a comprehensive report on the latest AI     trends," the agent would first plan to search for research papers, then analyze the data, and finally synthesize the findings into a structured report.
2. Execution and Tool Use: This is where the agent puts its plan into action. It doesn't just rely on its own internal knowledge; it uses a variety of external tools and APIs to accomplish its tasks. This could mean using a search engine to gather information, a code interpreter to analyze data, or even an email client to send a message. The agent's ability to seamlessly integrate and switch between different tools is a key differentiator.
3. Self-Correction and Learning: One of the most powerful features of agentic AI is its ability to learn from its mistakes. If a step in its plan fails or produces an unexpected result, the agent doesn't just stop. It analyzes what went wrong, adjusts its plan, and tries again. This iterative, self-correcting loop allows it to tackle complex problems that would be impossible for a simple, single-prompt AI to solve.

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The Agent-Driven Marketing and Advertising Funnel

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In the world of marketing, advertising, and e-commerce, agentic AI is poised to change everything. We're moving from a multi-tool era to a multi-agent era, where a group of specialized AI agents can collaborate to solve complex problems. Hakuhodo DY ONE (H+’s parent company) is pioneering this with our proprietary service, ONE-AIGENT. This service links specialized AI agents, providing comprehensive support for the entire marketing process.

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●    Planning and Research: Before a campaign even begins, an agentic AI can perform tasks like desk research and insight research. ONE-AIGENT, for example, integrates customized AI agents that have learned from the Hakuhodo DY Group’s proprietary sei-katsu-sha data infrastructure. The term sei-katsu-sha describes people as "fully rounded individuals with their own lifestyles, aspirations and dreams," not just as consumers.

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●    Creative Production: Once a plan is in place, generative AI agents can produce creative assets at an unprecedented scale, from ad copy and images to video scripts. ONE-AIGENT produces and operates creative deliverables by combining generative AI with other AI agents trained on the company’s unique operational knowledge. This allows for the mass production of creative versions that can be A/B tested to find the winning creative and maximize results.

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●    Campaign Execution & Optimization: This is where agentic AI truly shines. It can autonomously manage multi-platform campaigns, continuously monitoring performance, adjusting bids, and reallocating budgets to the highest-performing channels. ONE-AIGENT offers a full lineup of AI agents optimized for specific programmatic advertising processes, from planning to execution. The service also supports businesses in building their own AI agents and linking them with Hakuhodo DY ONE's proprietary agents. This is enabled by Zero Data Sharing, a concept designed to use a client's first-party data securely by having AI agents interact and share only necessary information or analysis results without disclosing confidential data.

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The Future is Agent-Driven

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This isn't just about automation; it's about augmentation. Agentic AI won't replace human creativity or strategic thinking. Instead, it will free us from the tedious, repetitive tasks that consume our time, allowing us to focus on what we do best: innovating, collaborating, and solving the most challenging problems - in advertising and marketing or in business intelligences or in scientific developments. The key to success may be in building a new kind of "agentic AI mesh" that allows for a seamless partnership between human expertise and autonomous systems. This collaboration will enable businesses to not only become more efficient but also to create more personalized, effective, and resilient strategies in an increasingly complex digital landscape.

The future of AI isn't about better assistants and faster tools. It's about building smarter, more capable partners. And with the rise of agentic AI, that future is closer than you think.

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