AI strategy consulting in six clearly defined steps: together we develop your AI strategy, one that is structured, transparent and tailored to your business.
From First Meeting
to AI Strategy
An AI strategy is only as robust as the understanding of your business behind it. That is why ours starts with listening, not slides.
AI strategy consulting: what it delivers and what you hold at the end
AI strategy consulting answers one question: where does machine learning pay off in your company, and in what order should you tackle the initiatives? It does not produce a survey of technologies or a list of tools. It produces a decision your management can stand behind.
The result is an AI roadmap: prioritised use cases with effort, benefit and a first step that can start straight away. It rests on your data, your processes and your figures rather than on case studies from other industries.
The consulting process is deliberately short. Six steps, each with a tangible interim result, so that at every stage you can decide whether the next step is worth taking.
How delivery works afterwards is shown by the data science process in six phases with the deliverables of each phase.
Our Consulting Process
Six steps from the first introduction to your completed AI strategy.
Prepare the first meeting
You fill in our pre-meeting questionnaire. This allows us to tailor the first conversation precisely to your situation.
The questionnaire asks about your business model, your most important processes, the data sources you already have and the reason for seeking an AI strategy. A few minutes on your side spare you and us the preamble in the first meeting.
Initial consultation & discovery
In a structured conversation we get to know your business and identify where AI offers the greatest leverage.
The first meeting is free of charge and without obligation. We listen, ask questions and name two or three areas at the end where machine learning could have a measurable effect. If our assessment is negative, we say so in the same conversation.
Situation analysis
We analyse your data landscape, IT infrastructure, organisational maturity and regulatory requirements.
We review data sources, interfaces and the quality of the data you hold, talk to the business side and to IT, and check which requirements from the GDPR, the EU AI Act and industry rules apply. The result is a data readiness rating for each use case, without which no sound prioritisation is possible.
Opportunity mapping
Together we identify and prioritise use cases by business value and feasibility.
Each use case receives an estimate of benefit in euros, effort in person-days and delivery risk. From this a ranking emerges that the business side and management support together. Use cases without a data basis drop out or receive a preliminary step for data collection.
Strategy development
The findings are turned into an AI roadmap of your own, with milestones and resource requirements.
The AI roadmap places the prioritised use cases on a timeline, with milestones, responsibilities and the resources needed on your side. It begins with a pilot project that can start straight away and delivers a first result on real data.
Strategy presentation
We present the strategy to your decision-makers and hand over all results as structured documentation.
The presentation is aimed at management, advisory board or shareholders and answers the question of whether to start and with what. You receive the documentation with all assessments, assumptions and calculations, so the decision remains traceable without us.
What you hold at the end
The AI roadmap is a document you can work with, not a slide show. These six components are always part of it.
Prioritised use cases
A ranking by business value, feasibility and risk, with the reasoning for each position.
Data readiness rating
Which data is available, usable and reliable, and where collection or cleansing is needed before the first AI model.
Business case per use case
Benefit in euros, effort in person-days and the assumptions behind them, disclosed and adjustable.
Pilot project with a starting point
The first use case, scoped so that it can start straight away and delivers a result on real data.
Milestones and resources
Timeline, responsibilities and the effort on your side, so the roadmap fits into your annual planning.
Regulatory framework
What the GDPR and the EU AI Act mean for the planned use cases, with specific obligations for each one.
Who the AI strategy consulting is designed for
This service is aimed at managing directors, heads of department and IT managers in mid-sized companies who want to introduce AI not on principle but because of a specific problem: scrap, downtime, returns, forecast errors, manual checks. Typical clients generate their own data but have no data science team. What matters is the data situation rather than the headcount.
It is less suitable if no data is being collected yet or if you are only looking to choose a tool. In the first case we begin with data collection, in the second we point you to suitable providers. We say so in the first meeting either way.
The wider picture is on the page AI consulting for mid-sized companies and covers the services that go with the strategy.
A fixed price applies to the AI Readiness Assessment as a structured starting point.
What you can expect from the strategy consulting
Clear direction
A well-founded AI strategy that fits your business, not generic recommendations.
Prioritised use cases
Concrete use cases, assessed by business value and feasibility.
Decision basis
Structured documentation for your management and boards.
Frequently asked questions about AI strategy consulting
How long does the AI strategy consulting take?
That depends on your data situation and the number of use cases. You can book the first meeting directly with the questionnaire, and we set out the timeframe for the following steps afterwards. The roadmap is scoped so that the pilot project can begin right after the presentation.
What does the AI strategy consulting cost?
The questionnaire and the first meeting are free of charge and without obligation. The structured entry point runs through fixed-price packages such as the AI Readiness Assessment. The following steps depend on scope and data situation. You receive a quote before each step and decide whether it is worthwhile.
Do we need a data strategy first?
No. The situation analysis in step three examines your data and provides the data readiness rating a roadmap needs. If it shows that basic data is missing, data collection becomes the first building block of the roadmap. A data strategy then emerges as part of delivery rather than as a prerequisite.
How does the AI strategy consulting differ from delivery?
Consulting decides where and in what order machine learning is used. Delivery builds the AI models, prepares the data and brings the results into operation, following the data science process in six phases. At myBytes both come from one team, but you can also take on delivery with another partner.
Do we need AI expertise of our own?
No. You bring the knowledge of your business, your processes and your figures, and we bring the method and the experience with AI models. We explain technical terms where they matter for a decision. For presentations to boards we prepare the results so that they hold up without prior knowledge.
The first step towards your AI strategy
You know your business, we know the AI models. A conversation turns that into a plan.
Complete our questionnaire, so we can prepare properly for the first conversation.
Start the questionnaire