WhatsApp can be set up with an AI assistant so that incoming customer messages are answered automatically, frequent questions are settled immediately and appointments are booked right in the chat, without anyone on your team constantly checking a phone. For many customers, the short message has become the preferred way to reach a business: it can be typed on the side, the reply can be read at leisure, and the history stays available. Loomira is an AI phone assistant for small and mid-size businesses that, alongside calls, also answers WhatsApp messages automatically and brings both channels together in one inbox, with EU hosting and GDPR-compliant processing. This article explains why the channel works so well for customer inquiries, how automatic replies work in practice and what a GDPR-compliant setup requires.
Why do many customers prefer WhatsApp to a call or an email?
A call requires both sides to have time at the same moment; an email often feels too formal and too slow for a short question. The short message sits in between: quickly typed, answered asynchronously, permanently readable, so anyone can check at any time what was agreed.
How firmly the channel is anchored in daily life is shown by Eurostat: in 2025, 82 percent of people aged 16 to 74 in the EU used instant messaging, the same share as used email, while 76 percent made telephone or video calls over the internet. The trend is clear too: in 2024, Eurostat reported that 85 percent used the internet for telephoning, video calls or instant messaging, 14 percentage points more than in 2019 and twice the growth seen for email. Someone who writes dozens of messenger messages a day increasingly experiences it as a detour to have to call or compose an email for an appointment request or a question about opening hours. Many customers therefore now expect businesses to be reachable by messenger at all, and expect a reply that does not wait until the next working day.
What is a WhatsApp assistant?
A WhatsApp assistant is an AI system that automatically reads incoming WhatsApp messages to a business, matches them against the stored knowledge base and answers in plain language, including follow-up actions such as booking an appointment in the calendar or handing over to a person when the request cannot be resolved automatically with confidence.
The difference from simple auto-responders and menu-driven chatbots lies in understanding: the assistant answers freely worded questions ("Do you still have anything free on Saturday?") on their substance instead of reacting to keywords with canned text. And the difference from WhatsApp on a private phone lies in structure: inquiries do not land on one person's device but in a shared, traceable inbox that belongs to the business.
How does an AI assistant answer WhatsApp messages automatically?
The assistant reads the incoming message, matches the request against your knowledge base and replies clearly and in your name. For an appointment request it also checks availability in the calendar and proposes suitable times or confirms a slot directly. "I'd need an appointment next week" becomes a confirmed calendar entry with a chat confirmation, without anyone on the team typing.
If a request cannot be answered with confidence, because it is very specific, unusual or sensitive, it is passed to your team rather than the assistant guessing an unsuitable answer. This handover threshold is deliberately conservative: automation happens where the answer follows reliably from your stored content; everything else stays with people and is handed over with the full history. That produces relief on the recurring requests without complex cases getting lost in wrong automatic replies.
That businesses increasingly organize customer contact this way is measurable. According to Eurostat, 20.0 percent of EU enterprises with ten or more employees used AI in 2025, and the most common single use, at 11.8 percent of all enterprises, was analyzing written language, exactly what a messaging assistant does.
How do calls and WhatsApp come together in one inbox?
A customer who calls today and sends a WhatsApp message tomorrow should not be treated like two different people. That is why calls and chat messages run together in one shared inbox: you see at a glance what has already been discussed, regardless of channel, and do not have to switch between the call log and a chat app to keep track.
This is especially useful when a request continues across channels. A call ends with an open question that is then settled on WhatsApp, for example because the customer first has to send a photo of the faulty appliance or a document. Conversely, a chat inquiry can lead to a callback in which the full history is already on the table. For the customer it feels like one continuous conversation; for your team it is a single chronological record instead of scattered fragments.
Is this compatible with the GDPR?
Yes, provided the processing is set up accordingly. Three points are decisive. First, the AI processing of message content, the analysis, the drafting of replies and the knowledge base, should take place inside the EU. Second, you need a data processing agreement under Art. 28 of the GDPR with the provider, disclosing the services used and the chain of sub-processors. Third, customers must be able to tell that they are communicating with an automated assistant, and personal data from chat histories must not be stored longer than necessary.
There is also a peculiarity of the channel: the message transport itself runs through the WhatsApp Business Platform, and its terms apply to that transport, which belongs transparently in your privacy notice. Sensitive content, such as health information, should not be actively requested via chat as a rule. How Loomira handles these points is documented in our data protection overview; the setup of the channel is described on the WhatsApp assistant page.
How do you set up the channel?
Setup follows a manageable pattern. First a business WhatsApp number with a company profile is set up, separate from any private account, so that inquiries belong to the business and not to a person. Then you fill the knowledge base with the content the assistant should answer from: opening hours, services, prices, typical procedures. Next you define the handover rules, for which topics or uncertainties the assistant passes to your team, and, if wanted, connect the calendar for appointment booking in the chat.
Two points deserve particular care. First, who starts the conversation: customers should write to you themselves or have agreed to be contacted. WhatsApp is a dialog channel, not a mailing list, and unsolicited messages damage trust as well as deliverability. Second, the notice about automation: a short sentence at the start of the conversation that an AI assistant is replying and that a person can take over at any time creates clarity and matches the transparency principle of Art. 50 of the EU AI Act, which has applied since 2 August 2026. Both cost nothing and prevent the two most common false starts on the channel.
Which inquiries suit the channel best?
WhatsApp plays to its strengths with short, concrete requests: appointment inquiries and rescheduling, questions about opening hours and prices, status queries ("Has my order arrived?"), sending a photo before a workshop or repair visit. These are precisely the requests that make up the bulk of phone volume too, except that in chat they run asynchronously and without anyone on hold. And because the history is retained, the follow-up questions about details already given, which drag out phone calls, disappear.
The channel is less suited to long consultations and to anything requiring confidentiality beyond the usual level. The sensible division of labor: chat takes the quick standard cases, the phone takes the conversations, and both land in the same inbox. What the phone side of that division looks like is described in our overview of the AI phone assistant.
Conclusion
For a business, an automated WhatsApp channel means one thing above all: customer inquiries no longer get stuck on a private phone but are answered in a structured, traceable and reliable way, on the channel many customers prefer anyway. The prerequisites are manageable: a well-maintained knowledge base, a conservatively set handover threshold to people, and a GDPR-clean setup with EU processing and a DPA. Start there and you gain a channel that answers around the clock, and a team that only sees the cases that really need a person.