AI consulting for media companies: strategy, use cases, enablement
We bring order into your company's AI debate: from a vague “we should do something” to a prioritised roadmap with business cases – and a team that comes along.
Why AI initiatives in media companies really fail.
Rarely because of technology. Mostly because of missing prioritisation, unclear business value – and a newsroom rightly asking what this has to do with quality journalism.
The pilot stays a pilot
As early as mid-2024, Gartner expected at least 30% of GenAI projects to be abandoned after proof of concept – over data quality, cost or missing business value. An experiment is built quickly; a path into daily operations is strategy work.
Ten opinions, no decision
According to 6sense, an average B2B buying committee has around ten members. In media companies, add editors-in-chief, works councils and trainees. Without a shared target picture, good ideas block each other.
Regulation as a permanent brake
GDPR, EU AI Act, ancillary copyright, press codes: if every idea is debated legally from scratch, you never get to build. A governance framework answers the questions once – and makes you fast afterwards.
Fear of quality erosion
Newsrooms fear devaluation of their work – often rightly, when AI arrives as a cost-cutting programme. We position AI as relief from routine, with clear limits and editorial final control.
Six building blocks – combined as needed.
AI strategy & roadmap
A target picture, fields of action and a 12-month roadmap that fits your budget, team and system landscape – not an ideal world.
Use-case identification & prioritisation
We collect ideas from newsroom, product and sales, score them by value, feasibility and risk – and prioritise with a business case per use case.
Maturity assessment
An honest inventory: data quality, systems, skills, governance. So the roadmap stands on facts, not wishful thinking.
Data strategy & governance
Which content and usage data may be used for what? We clarify rights, quality and access paths – the foundation of every reliable AI system.
EU AI Act & GDPR readiness
Classification of your initiatives under the EU AI Act, transparency duties under Art. 50, GDPR checks – prepared so your boards can decide.
Enablement & change
Workshops for newsroom and leadership, prompt training, editorial guidelines and AI literacy training under Art. 4 EU AI Act (mandatory since February 2025).
Four steps to a board-ready roadmap.
Discovery (interviews, system and data review) → use-case workshops with newsroom, product and sales → scoring and business cases → roadmap decision with your leadership. Typical duration: 4–8 weeks; faster as a compact potential check. For details, see our approach.
What is actually on the table at the end.
Consulting often stays abstract – so we define deliverables up front. You take these four things from every strategy project:
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Prioritised use-case map
All candidates scored by value, effort, risk and data readiness – a decision basis for your boards.
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Business case per use case
Conservatively calculated time savings, reach or revenue effects – so your CFO can calculate instead of believe.
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12-month roadmap
Sequence, milestones, responsibilities and budget corridors – from first pilot to scaled operations.
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Governance framework
Guardrails for AI use: approval processes, labelling, quality assurance, compliance documentation.
We only recommend what we operate ourselves.
Our own portal with 500,000+ monthly users is our working lab: AI-supported research, editing and SEO workflows run there in daily production – with the same trade-offs between quality, cost and data protection your company faces. What fails there, we will not recommend to you.
Frequently asked questions about AI consulting
How long does a consulting project typically take?
A focused strategy project typically takes 4 to 8 weeks – from discovery to a board-ready roadmap. A compact AI potential check is feasible in 2 to 3 weeks. The critical factor is the availability of your experts for interviews and workshops.
What exactly is the AI potential check?
A compact entry format: we review your system landscape and data readiness, interview newsroom, product and IT, and deliver a first prioritised use-case list with a recommendation for the most sensible pilot. Ideal if you want clarity before releasing a larger budget.
Do we need a solid data foundation before starting?
No – assessing your data readiness is part of the consulting. Many effective use cases such as summarisation or editing support mainly need your content, not perfectly curated databases. Where data is missing, we plan its development into the roadmap.
How do you handle the EU AI Act?
We classify every use case within the risk logic of the EU AI Act and document transparency and labelling duties. The AI literacy obligation under Art. 4 has applied since February 2025 – our enablement formats cover it. We do not replace legal advice; we prepare it.
Are you tied to specific tools or vendors?
No. We are vendor-neutral and earn nothing from licence recommendations. Whether OpenAI, European providers such as Mistral, or open-source models in your own data centre – we recommend what fits requirements, data protection and budget, and justify it transparently.
What happens after the consulting – are we left alone with the roadmap?
Only if you want that. Our development team implements prioritised use cases directly, from prototype to operations. You can also deliver with your internal team or another partner – the roadmap is documented to work without us.
Strategy becomes software.
The biggest advantage of our consulting: it does not end at the edge of a slide. The same team that prioritises your use cases can implement them as AI software development – from a prototype in weeks to a maintained system in daily editorial use.
Start with an AI potential check.
Compact, honest, decision-ready: a first use-case map and a clear recommendation on whether and where entry pays off.