AI Strategy for Business
An AI strategy that ends in decisions not in slides
Assessment, use-case portfolio, governance and a roadmap your team can actually execute.
The pressure is real: the board asks about AI, competitors automate, and your workforce already uses the tools, with or without permission. What is missing is rarely motivation but a realistic frame: Where does AI create measurable value for us? What do we deliberately skip? And in what order do we proceed?
digitario builds this frame together with leadership and key people, compact, prioritised and with clear ownership. Not an 80-slide strategy, but a working document: a use-case portfolio with benefit/effort scoring, governance guardrails and a roadmap with a first pilot.
The difference to classic strategy consulting: the recommendations come from daily hands-on AI practice and 24 years of product and delivery experience. What ends up on the roadmap has been built in some form before.
01 · What this is about
Four questions a useful AI strategy answers.
Where does value emerge? What are the risks? Who owns what? And where do we start?
An AI strategy is not a technology document, it is a decision document. It connects business goals with concrete fields of application, sets guardrails for data and accountability, and makes the entry small enough to succeed safely and measurable enough to build trust.
Just as important as the commitments are the refusals: a good strategy also names what will deliberately not be done, protecting the organisation from tool actionism and parallel experiments without ownership.
Typical flow of the strategy work
Business goals, data readiness, running initiatives, risks
MENSCHCollect use cases and score them by benefit and effort
KIDefine data, roles, approvals and tool guardrails
MENSCHSequence, owners and success metrics
MENSCHFirst use case at limited scale, measurable
KITypical starting points
Leadership needs to take a position on AI but lacks a solid picture of the options. Or scattered experiments are already running without shared direction or governance. Or a finished strategy exists, but nobody knows how to translate it into execution.
What digitario takes on
Compact strategy work with the people who will own it afterwards, not over their heads.
- Baseline assessment: goals, data readiness, current activities, regulatory frame
- Use-case portfolio with honest benefit/effort scoring
- Governance guardrails: data, roles, approvals, tool selection
- Prioritised roadmap with owners and success metrics
- Guidance through the first pilot, up to production on request
- Enabling key people instead of consultant dependency
02 · Building blocks
Three building blocks that work together.
Use-case portfolio
All candidates on one page, scored by benefit, effort, data readiness and risk. The basis of any serious prioritisation.
Governance & data frame
Clear rules for data access, tool usage, approvals and accountability, so AI adoption does not become an uncontrolled side show.
Roadmap & first pilot
A sequence that builds trust: start small, measure, scale. With owners and metrics instead of declarations of intent.
03 · The difference
Strategy from someone who knows execution.
digitario comes from 24 years of operational product and delivery accountability, and uses AI daily in its own work. Both flow into every recommendation.
That protects against the two most common strategy failures: roadmaps that do not hold up technically, and governance so strict that nobody can work. A strategy is only useful when both sides fit together.
Background
- AI agents, LLM workflows and local models in own operation
- Product and delivery leadership in enterprises and SMEs
- Regulated industries: insurance, media, telecom
- In the Swiss market since 2008
04 · FAQ
Frequently asked questions about AI strategy
It is deliberately compact: depending on company size and maturity, usually some weeks from baseline to roadmap. A strategy that drags on for many quarters is often outdated by the time it is delivered.
No. Data readiness is captured in the assessment and feeds the prioritisation. Many high-impact use cases need less infrastructure than assumed.
The result is a working document with owners and metrics instead of a slide deck, and the recommendations come from daily hands-on AI practice plus operational delivery experience.
Yes, especially there. SMEs do not need an enterprise strategy but two or three well-chosen use cases with clear value and an entry that does not endanger daily business.
On request, yes, from the first pilot to the productive system. Strategy and execution from one partner is the core of the digitario model. There is no obligation to do so.
05 · Next step
Know where you stand in 30 minutes.
In an intro call we sort out your starting position: what is realistic, what comes first, and whether you even need a strategy yet, or rather a pilot.