technologies
AI is transforming the way brands converse, sell, and build loyalty.
Mariangeles Leiva LuqueNovember 5, 2025 | 9 min
A few years ago, I attended Marketing Shake for the first time and everything revolved around omnichannel marketing. Today, I returned to the same event—rebranded as Marketing Shake Up: AIhora? Between the Possible and Impossible in Data Marketing—and noticed how it's no longer just about adopting AI tools, but learning to think critically amid the noise.
One of the talks raised a key question:
“How do we awaken critical thinking in an era where AI promises to do everything for us?”
The answer: “Learn to think with good judgment.”
This is perhaps the most important new professional skill: the ability to distinguish between automating for efficiency or by inertia, and using AI to do more—or to do better.
Key tools that work with AI in Google Ads
Summary of key trends in digital marketing and automation according to Marketing Shake Up:
- 1. SEO isn’t dead: it just changed its name SEO is no longer just about attracting human traffic. Now it means thinking for LLMs (large language models like ChatGPT or Gemini). Sessions and CTR aren't enough; now, brands measure how much of their content feeds AI. Content must be useful and structured for both people and machines, and new KPIs are needed based on real usage by AI systems.
- 2. The evolution of automation: from static flows to continuous learning Marketing automation shifted from fixed logic to living systems powered by AI. Now, messages adapt in real time to each user’s behavior, raising open rates above 70%. AI decides channel, content, and timing, leaving pure technical automation behind.
- 3. Conversation to convert: rise of conversational channels Channels like WhatsApp and Messenger are key for service and conversion. For users, feeling well attended is more important than who responds. The challenge is designing conversational agents that communicate brand culture, clarity, and empathy—not just generic answers.
- 4. From landing to chat: new conversion points The classic journey (click→landing→form) is being replaced by click-to-message experiences. AI guides the user inside the chat to conversion, and QR codes open chats in stores, events, or packaging. However, tracking conversions is now more challenging and requires advanced traceability like Conversions API.
- 5. More data, more traceability, less micromanagement AI processes thousands of variables and the team’s role is to understand what’s measured and how to use that data to make decisions. The current challenge is to design self-tuning systems and free up time for strategic tasks.
- 6. Implications for brands: experience first Conversational channels not only sell: they build loyalty, collect payments, and retain customers. Bots improve experience and results in support and collections. The real challenge is cultural: focusing on customer experience over technology.
Practical implications for AI and automation marketing
Adapting to these trends enables relevance, conversion, and better experiences in the new digital environment:
- Create useful content for humans and machines: Structure information so it is understandable for people and also for AI models. Include KPIs about how the content is used by AI.
- Automate with learning and personalization in mind: Implement intelligent systems that adapt messages and channels to each user in real time, increasing communication effectiveness.
- Prioritize the conversational experience: Turn contact points into relevant conversations (chats, messaging). Ensure empathetic and brand-aligned answers.
- Measure what matters and free up time for strategy: Let AI handle micromanagement and focus on designing and interpreting metrics that guide learning and the business.
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If you want to use AI to scale your campaigns without losing control, you need a clear structure, good measurement, and a solid strategy. At We Make It Lab, we help you integrate all of this to achieve real, sustainable results.
Mariangeles Leiva Luque
It's not just about using AI, but using it well. The real difference is in how you combine automation with business judgment. That’s where the true impact lies.
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