Brand Makers
Dil Ka Jod Hai, Tootega Nahin
Agentic AI has become the new darling of boardrooms; no signs of slowing down in 2026: Report
As 80% of CMOs report that generative AI is either a priority or a significantly important investment for their company, a clear framework for agent design has become critical.
Agentic AI has become the new darling of boardrooms, fueling rapid agent inflation with no signs of slowing down in 2026. Yet as more companies join the agentic AI race without a defined strategy, they risk not only building inefficient solutions but also eroding consumer trust in their brand.
For many consumers, the promise of unprecedented convenience offered by agentic AI is highly appealing. According to the dentsu's Human Truths In The Algorithmic Era report, one in two respondents already state that by 2035 they would like to have an AI clone to manage shopping, administrative, and communication tasks on their behalf.
Recent developments in agentic AI—such as OpenAI’s Agent Mode and Amazon’s Buy for Me feature—are accelerating this shift toward digital delegation. In response, several organizations are developing agents of their own. However, many mistake the sheer number of agents for true value creation. While experimentation has its merits, releasing agents merely for visibility can turn early curiosity into frustration, ultimately damaging brand trust and delaying leadership in the agentic AI landscape.
Strategic Blueprint for Agentic AI
As 80% of CMOs report that generative AI is either a priority or a significantly important investment for their company, a clear framework for agent design has become critical.
1. Build agents that drive strategic value Most AI agents today lack memory and coherent design, making them ineffective at optimizing consumer journeys. True value comes from context-aware systems that can manage multi-step tasks seamlessly, adapt to evolving customer data, and maintain continuity across interactions.
2. Build in oversight to avoid technical debt Unstructured agent deployment without a centralized orchestration layer leads to operational complexity and technical debt. Brands must implement a unified control panel to oversee agent lifecycles, dependencies, and communication, enabling scalable, efficient, and resilient agent ecosystems.
3. Build in governance to mitigate risk Agent platforms and marketplaces hold promise, but without governance they pose brand and compliance risks. Companies should design auditable, testable agents with quality-assurance pipelines, human-in-the-loop review, and safeguards to prevent copyright violations, off-brand communication, and misinformation.
4. Build for modularity Framework-specific agents often lack the flexibility to adapt to the rapidly evolving AI ecosystem. Organizations should adopt modular design principles, creating agents that are decoupled from underlying LLMs and easily swappable without requiring full-stack redevelopment.
In the AI race, the brands that apply strategic rigor to agentic AI—approaching agent design with the same discipline as campaign orchestration—will emerge ahead. These organizations will deliver a new level of intelligent service that enhances trust, efficiency, and consumer delight.
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