AI Training for Marketing Teams 2026: Program and Price

Marketing teams often have enough ideas and too little time for research, briefs, first drafts, channel versions, and reporting. AI can reduce the mechanical work when the team gives it current sources, a clear voice, and a review path.

This workshop is for a team that wants to build that shared method on its own material. Participants practise four linked tasks and leave with a source pack, editorial checklist, and examples that can be reused. A one-off campaign may need a delivery project instead. A missing brand standard should be resolved before the team scales output.

The four workshop tasks

1. Research and a campaign brief

The team gathers approved product information, customer context, market references, and previous campaign material. The model can organise the source pack, list open questions, and propose a brief structure. A marketer checks the sources and decides which claims belong in the brief.

The brief records audience, problem, objective, message, evidence, channel, call to action, and constraints. A claim without a source stays marked as an open item until its owner resolves it.

2. Drafting in the brand voice

Participants create a small voice guide from real examples: sentence length, level of formality, preferred terms, words to avoid, use of numbers, and the way the brand asks for action. The model then drafts from a brief and source pack.

The editor checks meaning, factual support, tone, inclusivity, links, and the intended audience. A polished sentence still needs a human decision about whether it belongs in the campaign.

3. Repurposing across channels

The team takes one approved idea and adapts it for the channels it actually uses: a landing page, email, social post, sales brief, or internal update. Each version carries the same source-backed meaning while its length and context change.

The exercise catches a common failure: the short version keeps the promise but loses its condition or qualifier. The review checklist records what can change with format and what must remain fixed.

4. Reporting on results

The model can help structure an export, summarise observations, and prepare questions for the next review. The team separates:

1. Observation: what the approved data shows.
2. Hypothesis: a possible reason that needs checking.
3. Decision: an action owned by the campaign team.

That separation keeps a fluent explanation from becoming an invented causal story. If the data cannot support a conclusion, the report says what is missing.

The source and claim register

Before drafting, create a small register:

This is especially useful for prices, customer outcomes, market numbers, product capabilities, regulatory statements, and named references. The model can point to a missing field; it should not fill the gap with a plausible sentence.

A working voice guide

"Write in our tone" is too vague for a team or a model. Convert the brand into observable decisions:

• how formal the language is;
• how the brand addresses the reader;
• sentence and paragraph length;
• preferred and prohibited terms;
• the place of technical words and explanations;
• how uncertainty and evidence are written;
• the structure of a call to action;
• two examples that pass and two that fail, with reasons.

The guide belongs beside the approved source pack. When a product description, price, or promise changes, its owner updates the source and the team records the change before reusing the draft.

A one-day workshop structure

Before the day: an engineer reviews one campaign, the current source pack, the channels, and the approval path. The team removes private data from examples or confirms the approved environment for using it.

Morning: participants build the brief, claim register, and voice examples. The group tests a short research request and checks every source.

Midday: the team drafts the main asset and two channel versions. Editors mark unsupported claims, voice drift, missing context, and broken links.

Afternoon: the group prepares a result-report template, runs an edge-case review, and writes the standard for approval, publishing, and later updates.

A second day can cover several brands, a larger source library, channel templates, or a lightweight evaluation set. It does not include automatic publishing unless a separate build has an explicit approval design.

Publication and AI transparency

Human editorial approval remains part of the workshop. The editor checks the source, claim, tone, audience, links, permissions, and owner before publication. A system that publishes without this review does not match the standard taught here.

Depending on how a system is used, the EU AI Act can create transparency and documentation duties. The team should record where AI was used and confirm the obligations for its jurisdiction and channel with its legal or compliance owner.

Data handling

Decide what can enter the selected tool:

• public references and approved product material;
• internal briefs and campaign drafts;
• customer or prospect data, only when the company permits it;
• analytics exports with identifying fields removed where possible;
• confidential launch plans, pricing, or contracts, only in an approved environment.

The team records retention, access, and deletion rules. A model provider's settings do not replace the organisation's data-processing decision.

What stays with the team

Depending on scope, the workshop produces:

• a campaign brief template;
• a source and claim register;
• a working voice guide;
• channel adaptation templates;
• a report structure that separates observation and hypothesis;
• an editorial and link checklist;
• examples of accepted and rejected drafts;
• a small set of cases for regression review.

These are operational materials. They do not replace a brand book, legal review, consent process, or the CMS workflow.

Price and format

A closed workshop starts from €1,200 net per day and usually falls in the €1,200–1,500 net range. The rate covers one day and one workshop group of up to about 15 people. The final amount depends on the number of days, groups, source preparation, and channels included.

The format is online or at the company's office and is run by Syntalith engineers. The workshop is separate from content production or a build that connects a model to a CMS. A free process scan can identify the right next step.

When training is a poor first purchase

Choose source and process work first when product descriptions conflict, no one owns the brand voice, or nobody approves claims. More drafts will increase the review queue without resolving the source problem.

Choose a delivery project when the business needs one campaign asset and no shared skill after it. Choose an implementation project when the real need is a connected research, briefing, or reporting workflow with data and permissions.

Training is a good fit when the team has a repeated marketing process, a named editor, and time to use the written standard after the workshop.

FAQ

How much does the workshop cost?

Budget from €1,200 net for a day with one marketing team of up to about 15 people. The usual range is €1,200–1,500 net. Additional channels, source preparation or separate groups expand the scope and the quote.

Can AI publish a post or landing page by itself?

The workshop keeps editorial approval with a person. The editor checks sources, claims, tone, links, permissions, and the campaign brief before publication.

Can we use our real content?

Yes, when the company permits it in the selected environment. Sensitive customer or launch data can be removed or replaced with prepared examples.

Does this include a CMS integration?

No live integration is assumed. A connected workflow needs a separate scope for authentication, source ownership, permissions, approvals, testing, and operations.

How do we start?

Bring one campaign brief, the current source pack, two voice examples, the channel list, and the approval path to a free process scan.