>> Data & AI strategy //
AI potential. Structured. Effective.
AI is used, but not strategically controlled
Many companies are already working with AI. The first pilots are underway, individual use cases have been launched and management interest is high. Nevertheless, there is often no common understanding of where AI will really have an impact and how a scalable approach can be developed.
There is usually no clear prioritization, no uniform architecture and no defined next step. This is precisely where the Data & AI Strategy comes in.
In practice, a similar pattern emerges: AI is available, but not strategically managed. Pilots remain isolated, scaling is rarely successful. At the same time, there is a lack of a clear entry point and a common direction between management, specialist departments and IT. The EU AI Act also increases the pressure to act.
Three forces are driving this development: processes and production need AI to make better decisions. AI potential must be identified and prioritized in a structured manner. Regulation and competition ensure that AI can no longer just be used experimentally.
Four steps
to a data & AI strategy
A Data & AI Strategy brings structure to precisely this initial situation and leads step by step to implementation.
Clarify focus
Where does the greatest AI benefit arise in the company?
Structuring potential
Which use cases really have an impact?
Develop target image
What does structured AI use look like?
Derive a roadmap
Which steps you will actually implement.
Packages & services
From the initial overview to concrete implementation, we accompany you on the path to the Digital Product Twin. Choose the package that suits your current needs and maturity level.
Package xs
Orientation workshop (2-4 hours)
free of charge
Contents:
- Short workshop on AI positioning
- Initial classification of relevant data and AI potentials
- Overview of possible use case fields
- Management summary
Benefit:
Quick clarity about the current level of AI maturity in the company and initial orientation as to where AI can really have an impact.
Package s
Recommended
Inspiration
Understanding and classifying AI potential
Contents:
- AI positioning
- Analysis of existing use cases
- First areas of potential
- Target image
Benefit:
Clarity about the current AI maturity level and first prioritized fields of action in the company.
Paket m
Innovation
KI strategisch strukturieren und nutzbar machen.
Inhalte:
- Alles aus S
- Priorisierte Use Cases
- Architektur Anforderungen
- Geschäftsmodell Betrachtung
Nutzen:
Ein strukturiertes Zielbild für KI im Unternehmen sowie klare Prioritäten für skalierbare Anwendungen.
Paket L
Integration
Von KI Strategie in die Umsetzung
Inhalte:
- Alles aus M
- Umsetzungsplanung
- PoC Begleitung
- Skalierungsplanung
Nutzen:
Eine konkrete Roadmap zur Umsetzung von KI Use Cases sowie Unterstützung bei Einführung und Skalierung.
Aus der Praxis
SEQYL Cases
Lassen Sie uns sprechen!
