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Agentic AI: the next battleground for Chinese brands

China’s companies have mastered social media marketing playbooks. Now, they must learn to win the trust of artificial intelligence (AI) agents that will increasingly shape what consumers discover, consider and ultimately buy.

These personal concierges are starting to determine the best choices for each user by balancing price, quality, reliability, sustainability and individual preferences. Tell an AI agent you want to go “somewhere”, and it can autonomously choose the destination and book transport, lodging and restaurants based on its deep, constantly updated understanding of your tastes, values and lifestyle – so-called personality pairing.

That’s a quantum leap from generative AI. Yet, AI of both the generative and agentic variety share a common dynamic: commerce is embedded into every aspect of each user’s experience. Weary of laborious click-throughs, consumers are seeking curated recommendations from AI agents. As a consequence, brands are losing influence over the answer that shapes choice, speakers argued at the recent Cannes Lions festival in France, attended by marketing executives and business leaders.

Brand identity is drifting from what companies intend to what AI agents generate and reinforce – often without marketers’ awareness. The central challenge is how to regain control. Strategies and tools for agentic AI are vastly different from those for social media engagement and search engine optimisation.

At this point, much remains unknown about when and why customers resist or embrace AI agents. And, their deployment raises unsettling issues. Security risks range from agents’ privilege and authority to vulnerabilities for would-be attackers. Agents may bypass privacy safeguards when accessing and sharing personal data to customise actions. They can cause harm unintentionally, just as humans can.
Cognitive shortfalls and cultural biases pose problems that some believe are insurmountable. Governance frameworks may lack ways to counter misinformation, address biases or prevent transactional hijacking by agents.
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