AI strategy · consulting in Switzerland
AI strategy for Swiss companies – from readiness check to implementation
Over 70% of AI projects stall — not because of the technology, but because use cases miss the real problems, leadership is not on board, or the data foundation is missing. We help put the right framework in place before operations begin.
AI works differently – depending on where you stand
AI is not a one-size-fits-all solution. What applies to a large enterprise works differently for an SME. What an association needs is not the same as what an agency needs.
Large enterprises & corporates: Complex system landscapes, many stakeholders, high compliance requirements. The challenge is not technology – it is governance, change management, and the question of which use cases will actually scale. AI works in large organisations when it is backed from the top and adopted from the bottom.
SMEs & boutiques with 5+ people: Small teams have one decisive advantage: they can decide quickly and implement directly. Those who start early with the right foundation – and do not wait for the big system – gain an edge over slower competitors. With CHF 30 per month per person and the right setup, a great deal can already be automated.
Associations & organisations: They face a specific task: knowledge that is spread out, members with different needs, and limited resources. AI helps structure knowledge management, scale communication, and work more efficiently internally.
Agencies & advertisers: Analysis, concept, reporting – all of this can be accelerated massively. More time for what really matters: creativity, strategy, and real client relationships.
Participants in our workshops save an average of 11.5 hours per week.
Some of our clients
How can we support your AI strategy?
How do you get AI strategy right?
Many companies skip the most important step: an honest assessment. Those who start straight with use cases or tools build on shaky ground.
Clarify the starting point
Before a strategy is defined, you need a realistic picture of the current situation: Which tools are used — officially and behind the scenes? What know-how exists? Which workflows are in place? And, crucially: What is the state of the data? Poor, unstructured or inaccessible data are the most common reason AI projects fail — even before a lack of know-how. Data readiness is not an IT issue. It is strategic.
Set strategic pillars
Based on the current situation, define the strategic pillars: Which areas have the greatest potential? Where are the risks? What must AI never do in this company? These decisions belong at executive committee level.
Develop and prioritise use cases
Concrete use cases emerge from the strategic pillars. Not as abstract ideas, but as testable hypotheses: Where is the biggest pain point? Who benefits? How do we measure success? Use cases are prioritised by business impact, feasibility and data availability – in the workshop with the teams involved.
Define goals – with business impact
Good AI goals are measurable: hours saved, error rate, processing time, NPS. If you do not define KPIs, you will never know whether AI really works. That is not a given – most companies do not measure.
Roadmap and Governance
Only when the starting point, pillars, use cases and goals are clear does a roadmap emerge. And in parallel: governance. Data protection, compliance, ethical frameworks – not as a brake, but as a prerequisite for sustainable use.
Approach
GL workshop. Audit. Pilot. Rollout.
01 / Awareness
Buy-in & Guidance
Half day
Raise leadership awareness, equip them, and bring them on board.
Set the overall strategy and objectives.
Define core guardrails.
02 / AUDIT
Use case portfolio
2 weeks
Conduct AI basics training.
Analyse the current state, identify use cases.
Prioritise use cases with the core team.
03 / Pilot
Implementation
10–30 days
Implement and measure 1–2 use cases.
Document — not a slide deck, but a system.
Present the results and define the next steps.
04 / Rollout
Scaling
Ongoing
Empower teams and integrate processes.
Roll out and scale more use cases.
Optional AI partner retainer.
Common Questions About AI Strategy
How long does developing an AI strategy take? For an initial workable framework – readiness, use case portfolio and roadmap – we allow 4–6 weeks. The executive workshop at the start takes half a day, and the full audit report follows within two weeks.
What does an AI Readiness Audit cost? Depending on company size and scope, between CHF 4,000 and CHF 14,000. For an initial conversation and assessment: free and without obligation.
What does data readiness have to do with AI strategy? A great deal. Most AI projects fail not because of the model – but because of the data. Unstructured, outdated, or inaccessible data blocks any automation approach. The AI Readiness Audit therefore always includes an assessment of the data situation.
For which companies is AI strategy relevant? We work with teams from 5 people, as well as with large companies and associations. Size is not the deciding factor – the willingness to change processes for real is.
What is the difference between AI strategy and AI implementation? The strategy defines the why, the what, and the guardrails. Implementation builds the concrete tools, workflows and automations. Both need each other – but the sequence matters.
We already use ChatGPT – do we still need a strategy? Yes. Using individual tools is not the same as working with AI strategically. And it is worth questioning the choice of tools: ChatGPT is not the best choice for every business application. → Claude & Enterprise AI
What are the most common reasons AI initiatives fail? From 230+ workshops, we repeatedly see: lack of executive buy-in, too many pilots without prioritisation, no clear guardrails, poor data quality – and no measurement. Without KPIs, nobody knows whether AI is truly making an impact.
Do we need our own AI department? No. What matters is clear ownership, a few empowered power users – and an external partner who builds and supports.
What are realistic AI goals for the first year? 2–4 automated workflows, 20–30% time savings in selected processes, an empowered team, and a documented strategy for the next 3 years.