How Interoperable AI Will Reshape Marketing and Why Marketers Must Prepare Now
As generative AI rapidly evolves, a wave of new protocols is promising to make AI systems more adaptable, personalised, and collaborative and marketers need to take notice.
Among the most significant developments are Model Context Protocols (MCPs) and agent-to-agent (A2A) protocols, which open the door to a future where AI isn't just powerful, but deeply integrated and interoperable across tools, platforms, and campaigns.
Let’s explore what this means for marketing teams and how to prepare for the shift.
Model Context Protocols: Smarter AI Through Standardised Context
Model Context Protocols (MCPs) are emerging as a way to standardise how applications deliver contextual information to large language models (LLMs). In practice, this means you don’t need to rebuild or retrain an AI model from scratch every time your context changes - instead, the model can dynamically respond to structured inputs.
For marketers, this is game-changing.
An MCP might include your brand voice, style guidelines, target audience definitions, and even live customer data. Feeding this structured context into a generative AI model allows it to produce content or actions tailored to your specific campaign or customer segment all without manually reprogramming or fine-tuning the model.
Preparing for MCP-driven AI
To stay ahead, marketing teams should begin:
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Building context libraries: Document and structure brand tone, personas, campaign rules, etc.
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Exploring tools that support MCPs or open APIs: Flexibility and interoperability will be key.
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Upskilling in context engineering: Understanding how to structure and maintain this information will be a valuable capability.
Agent-to-Agent Protocols: Towards Seamless AI Collaboration
Meanwhile, Google’s A2A (agent-to-agent) protocol aims to let AI agents from different systems communicate and collaborate safely and productively. For marketers, this could power highly automated, seamless customer experiences - think AI agents coordinating across CRM, media buying, content creation, and analytics tools.
Imagine a campaign where your content engine, ad platform, and customer insights tool all talk to each other, optimising in real time without human intervention but always aligned with your strategic goals.
One real-world example is Jellyfish, where AI agents are already automating media buying. The results?
That’s not just efficiency, it’s a complete redefinition of operational workflows.
Don’t Lose the Human Thread
As exciting as these efficiencies are, they do raise serious questions about marketing talent development. Junior roles have traditionally offered hands-on experience with the tasks AI is now taking over. So, how do we ensure the next generation of marketers still builds the skills they need?
As strategist Neil Perkin points out, while AI will handle execution, strategic oversight and creativity remain human domains. Junior marketers may no longer start with rote campaign setup, but they can be trained to work with AI crafting context, interpreting outcomes, and shaping strategy.
The Takeaway: Get Ready for Interoperable AI
For digital marketers, the message is clear: the future of AI in marketing isn’t just about smarter models, it’s about smarter systems that work together.
To stay competitive, now is the time to:
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Embrace emerging standards like MCPs and A2A protocols
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Invest in training for AI literacy and context engineering
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Reimagine how talent develops in a world of autonomous agents
AI is no longer just a tool — it's becoming a collaborator. The better we prepare our teams, tools, and strategies, the more value we’ll be able to unlock.