AI in marketing: less routine, more time for ideas.

AI marketing as a service means we build AI solutions for four parts of the marketing team's work: content, campaigns, lead scoring and reports. We do not sell a ready-made platform and we do not replace the team. We connect AI to the systems you already use and set it up to prepare the drafts, scores and summaries that take the most time today. The marketer reviews, edits and approves before anything reaches a customer.

You do not have to start with all four areas at once. In the first week we choose one where the routine is heaviest and the effect is easiest to measure, and the others follow after the first result. If you would rather have the team work with ChatGPT, Claude or Gemini themselves, AI training for companies is the better fit. This page is about processes that run every week, not one-off questions to a chatbot.

AI writes in your brand voice because we set it up on your own material, not on generic templates. In the first week we gather a description of the tone, approved copy from recent months and the words the brand uses or avoids. From one brief the solution prepares drafts for several channels: a blog article, a newsletter, social media posts and subject line variants for the email. Every draft goes through a person on the team.

For campaigns, AI prepares a proposed segment, the copy for each channel and several variants to test, but it does not launch the campaign or spend ad budget. The marketer decides what goes out, when and to whom. Personal data about contacts goes into the solution only where agreed, and the rules for AI in marketing become part of the company AI policy we prepare in AI governance and the EU AI Act.

Lead scoring ranks new enquiries by how likely they are to become customers. AI looks at the data you already have: what the person wrote in the form, which company they are from, which pages they viewed, if your website tracks that, and how they responded to your emails. For every lead it gives a score and a short reason, so the salesperson sees not just the number but also why.

We agree the scoring rules in the first week with both marketing and sales, because the two teams need to trust the same scale. Hot leads go to a salesperson, and the rest get a series of emails until they show interest. The score is written to the CRM system you use. What happens once a salesperson takes the lead is covered on the page about offers and an up-to-date CRM.

The weekly report brings together data from the systems you use: the CRM, the email system, web analytics and ad accounts, depending on how they can be connected. Instead of someone downloading spreadsheets from several places on Monday morning, the report builds itself and reaches the team and management on the agreed day. We choose its metrics together, usually from the ones you already track. That way marketing and management look at the same numbers, not different versions of one spreadsheet.

Besides the numbers, AI writes a short note on what changed since the previous week and where it is worth taking a closer look. The note is a starting point, not a decision: the marketer checks it, adds to it and decides what comes next. If management also wants a picture of the finances on the same day, see the page on financial report automation.

The project starts with a free 30-minute call, after which you know whether AI in marketing makes sense for you and which area to start with. If it does, in the first week we review the channels, systems and data and agree the metrics we will measure success by. The pilot runs on real campaigns and leads, and the first measurable results usually come within 2–4 weeks of the start. If the solution does not deliver against the baseline, it does not reach production.

The solution can be a standalone project or part of an AI transformation with the Encorp AIM (AI Implementation Method), where it is chosen at Gate 1 and reaches production in weeks 11–12. After launch it moves to AI Ops: we monitor the quality of the drafts and scores, update the brand voice description when needed and improve the solution every month, with response within 24 hours. The code, the model instructions and the deployment remain yours.