Agentic AI is currently taking over marketing – at least according to the headlines. 91 percent of marketers use AI today, according to a Jasper survey of 1,400 marketers. But less than a third truly let it work: controlling entire processes instead of just writing individual texts. McKinsey estimates that in the future, up to two-thirds of today’s marketing work could be handled by agents – from prospecting to personalization at individual touchpoints to lead qualification.
Sounds like a huge lever. And it is. This is precisely where a conflict arises that many teams know: Marketing wants – or needs – to build. CTO and Legal say: Be careful with data. Both are right. The real question, therefore, is not whether to use agentic AI, but: Who owns the data when an AI gains access to CRM, contacts, and communication?
What “agentic” really means
It’s worth distinguishing between two stages. At the first stage, AI helps with individual content: You have an idea, you outline the content – the thought and added value remain human – and the AI handles the drafting and rephrasing for many channels. This used to be a lot of legwork. Today, AI takes over this routine task.
At the second stage, it truly becomes agentic: The AI controls an entire process, checks consistency, monitors key figures, and autonomously suggests next steps. A crucial point that many overlook is this: The thinking remains with humans. The AI handles execution, not the idea.
The biggest lever is in reporting
The recurring task that is first worth automating is not “content” – it’s reporting. Evaluating large amounts of data across many channels quickly becomes complex. This is precisely where AI can continuously monitor numbers and make suggestions. At Aivie, we’ve built a feature that analyzes emails from recent months, identifies which ones are performing poorly and why, and suggests concrete optimizations – if desired, the AI implements them directly.
The honest punchline: This report has been available for years. The problem was never the availability of data, but that it was too rarely genuinely reviewed and then acted upon. An agent closes precisely this gap between insight and action – not because it’s smarter, but because it stays on task.
Why campaigns fail due to the data question
In practice, the most exciting campaigns rarely fail due to technology. They are slowed down because sensitive data would enter a black box – a legitimate concern. Marketing wants to build, CTO and Legal urge caution. Both are right, and that’s why many things are left undone, even though they would be easily feasible.
McKinsey sees the same pattern in the numbers: Almost everyone experiments with AI, but only about a quarter scale agentic systems at all – and if so, usually only in one or two areas. The biggest obstacles are not budget or technology, but organizational, regulatory, and legal concerns. The data question is therefore not a side issue in AI implementation. It is the main issue.
Confidence means choice and control
The good news: You don’t have to choose between “cool automation” and “data control.” You just need to build access correctly. At Aivie, a simple principle applies: It’s your data. We only host and operate it for you – an attitude that has grown out of our experience with open source, and which more and more Swiss organizations are also choosing for their infrastructure.
What customers who have switched to Aivie say
We moved from HubSpot and now have lower costs, less effort and, with Aivie, a partner that doesn’t hide its services behind a paywall. We also appreciate the excellent support.
Daniel B.
IT
Both the tool and the service are excellent. I particularly appreciate the fast response and data security, as all data is stored in Switzerland. The prices are very reasonable. Would recommend this service to others!
We have been working with Aivie as a marketing automation service for years. It is the clear number one in the areas of marketing automation and marketing strategy, and also offers by far the best price-performance ratio!
Felix Caprez
CMO
This results in two freedoms. First, you granularly set which capabilities and data access the AI has: Can it see contact data, only existing emails, or only statistics? Can it only read or also write? The AI gets as much context as a task needs – and not a step more. Second, you are free to choose which AI to use: different models for different tasks or even your own – especially when the prices of many providers are rising, this freedom of choice pays off. The data is encrypted on Swiss servers, and where necessary, complete hosting on Swiss infrastructure is possible. Confidence does not mean that a specific AI is forbidden – it means that you decide, with full control over who sees what.
The blind spot: Training on your data
One point often gets lost in the AI euphoria: With many providers, data is used by default to train the model. An opt-out is often possible – but you have to actively remember it. The unpleasant consequence: Confidential communication, such as an email to a customer, can flow into a model and be stored there without you being aware of it. For a newsletter, this might not matter. For sensitive customer data, it does – especially when agentic systems delve deeper into the data than a simple chatbot.
Conclusion: First the data question, then automation
Agentic AI is a real lever. And you don’t have to choose between “building a cool campaign” and “data under control” – if you clarify the data question before you automate, not after. The two-thirds McKinsey talks about are not hype. But they only materialize if the data question is clarified beforehand.
The question that really matters remains: Does it bother you that your data might go to the USA and be used there for training? Or would you rather be sure that it stays with you?
Your data remains your data.
Let’s take a look together.
We’ll show you how to use agentic AI while maintaining full control over your data.
