AI strategy for decision makers.

Why most AI strategy work fails before it starts

Everyone talks about AI. The hard part is deciding what to actually do with it inside your own business without getting it wrong. Invest too early on the wrong use case and you waste budget. Wait too long and a faster competitor pulls ahead.

The usual failure is a glossy deck full of generic ambitions that nobody can execute. It looks strategic. It changes nothing on Monday morning. Your team is left guessing which projects matter and which are noise.

A real AI strategy starts from your activity, not from a trend report. It looks at your processes, your data, your team and your clients before it recommends a single tool.

• Generic roadmaps copied from other industries that ignore your data reality.
• Use cases chosen for hype instead of impact and feasibility.
• No budget, no owner, no sequencing, so nothing ships.
• Governance and compliance left as an afterthought.

Our AI strategy approach, step by step

We build your AI strategy as an executable plan, written by people who can also build it. There are no intermediaries and no extra layers between the thinking and the doing.

An AI strategy at MAWT is a structured method that converts ambition into sequenced decisions. We begin by mapping every plausible AI use case across your operations, sales, finance and client experience. We then score each one on business impact and on technical feasibility against your current data and systems, so every candidate carries a defensible ranking rather than a gut feeling. The high impact, high feasibility candidates become your near-term priorities. The rest are parked with clear conditions for revisiting them. From that shortlist we write a 12 to 18 month roadmap that names budgets, the teams responsible, the dependencies between projects and the governance rules that keep you compliant with the Swiss Federal Act on Data Protection (FADP) and the EU AI Act. You leave with a plan your leadership can approve and your operators can start the same week, not a presentation that ages on a shared drive.

• Discovery: we audit your processes, data, team skills and client journeys.
• Use case mapping: we list every realistic AI opportunity, not just the obvious ones.
• Prioritisation: we rank each use case by impact and feasibility.
• Roadmap: we sequence a budgeted 12 to 18 month plan with owners.
• Governance: we define the compliance and data rules from day one.
• Enablement: we add a team acculturation plan so adoption actually happens.

What you get from an AI strategy engagement

Every output is concrete and benefit framed. You receive decisions, not slideware. The goal is that an executive can fund the plan and an operations lead can launch it without further translation.

Because the same senior humans who design the strategy also build AI solutions, the roadmap stays honest about what is buildable, at what cost and on what timeline.

• A clear map of where AI creates value in your business and where it does not.
• An impact versus feasibility prioritisation you can defend to your board.
• A budgeted 12 to 18 month roadmap with named owners and dependencies.
• A governance and compliance framework fit for Swiss SMBs.
• A team acculturation plan so people adopt the change instead of resisting it.

Who AI strategy is for

This service is built for Swiss SMBs and growing commercial companies whose leaders feel the pressure to act on AI but want a plan grounded in their real activity. It suits decision makers who would rather invest once, in the right places, than spread budget thinly across experiments that never ship.

It is equally relevant if you have already tried a few AI tools and now need to consolidate them into a coherent, governed direction.

• Swiss SMBs ready to move from talk to a fundable plan.
• growing commercial companies needing to prioritise AI investment.
• Leaders who want governance and compliance built in from the start.