AI consulting: How to get started with AI
The easy way to smart use cases, clear priorities, and real results.
AI consulting with a clear roadmap
AI has great potential, but where should companies start? A wide range of technologies, unclear objectives, and vague benefits make it difficult to get started. So how do you begin? Which AI use cases are really worthwhile? And how can you implement an AI project that doesn’t get stuck in the pilot phase but delivers measurable results? This is exactly where our AI consulting for companies comes in.
Why our AI consulting makes the difference
Our AI consulting provides clarity for companies: we help them discover potential, make use cases tangible, and create structures that transform AI from an experiment into a success factor. By meaningfully combining human expertise and technology, we ensure reliable results. Our goal: to empower your company to successfully launch AI projects—with a clear roadmap, based on reliable data, and with concrete added value.
OUR SERVICES
AI consulting for businesses – your path to a productive solution
Good artificial intelligence consulting does not begin with selecting the right technology, but with an overall picture of goals, requirements, and needs, as well as data and processes. This ensures that AI in the company is built on a solid foundation – supported by a smart combination of reliable technology, human expertise, and a clever strategy.
We usually start our AI projects with a workshop in which we examine your processes, data, and business goals. This allows us to identify meaningful and feasible use cases together. In other words, it’s not just about whether AI is “feasible” , but whether and how it can work in your company – economically, technically, and operationally.
Our AI experts check the quality, relevance, and completeness of your data and advise you on selecting the right model: whether predictive analytics, prescriptive AI, or generative AI—we show you which technology offers the greatest leverage for your goals. And we choose an approach in which humans and machines interact perfectly to achieve valid results.
Issues such as data protection, transparency, and the EU AI Act must be considered at an early stage. The goal is to securely integrate AI solutions into the existing IT landscape and comply with the requirements of GDPR, ISO, EU AI Act, and other governance standards.
Once the strategy, data, and governance are in place, it’s time to start implementing your AI project: setting up the AI models, training them with the right data, step-by-step implementation into your systems, and training your colleagues.
YOUR REQUEST:
We are happy to assist you.
Let’s get talking – we look forward to hearing your initial or more concrete ideas.
OUR ADDED VALUE: Why EBF?
At EBF, we combine technological depth with an understanding of your business reality – from analysis and development to operation. This enables us to avoid typical mistakes that slow down many AI projects. Because our AI experts know what matters!
Your advantages at a glance:
Experienced IT specialist with a focus on practical consulting on artificial intelligence
Many years of expertise and interface know-how
Structured introduction to the world of artificial intelligence
Proven methods for data, model, and process evaluation
Confident handling of data protection
Focus on time and cost efficiency
Sustainable results with fast, measurable ROI
E-BOOK: “From 0 to AI”
Looking for more guidance? In our e-book “From 0 to AI,” you’ll find a detailed self-assessment and tips for a successful start.
practical examples:
How AI makes a difference
Artificial intelligence is unleashing its potential across all industries: it makes processes smarter, data more valuable, and applications more powerful—whether in start-ups, medium-sized companies, or large corporations. Four examples illustrate what AI can already do today—and at the same time, they are just the beginning of what we can make possible.
Medical MRI machine in a modern operating room. Clean, sterile environment with advanced technology and equipment. Potential for uses in healthcare publications, educational materials, and presentations.
FAQs about AI consulting
AI projects can align with GDPR and EU AI Act expectations by embedding governance from day one: lawful basis checks, data minimization, audit trails, risk classification, and human oversight where required. Teams should document model purpose, data lineage, and control points across the lifecycle. EBF’s AI Consulting approach uses this governance-by-design approach so delivery, security, and compliance are managed together rather than retrofitted later. This is critical for enterprise adoption in Europe.
When selecting an AI consulting partner, enterprises should evaluate production delivery evidence, not just strategy capability. Key criteria include data engineering depth, governance maturity, in Germany compliance readiness for GDPR and EU AI Act, and the ability to move from pilot to production at scale. EBF’s AI Consulting approach provides this end-to-end model, combining use-case design, implementation, and operational governance.
Prioritize AI use cases by scoring business value, data readiness, delivery complexity, and time-to-impact, then selecting quick wins with clear financial metrics. Use a portfolio view that balances low-risk operational improvements with higher-value strategic cases.
Moving from AI experimentation to production deployment requires structured transition planning: validated data pipelines, defined compliance checkpoints, integration design, and operational monitoring. Most organizations stall at this stage because pilots lack production-readiness criteria. EBF’s AI Consulting approach applies a stage-gate model that connects pilot outcomes to production requirements, covering technical architecture, security, GDPR alignment, and go-live governance. This closes the gap between proof-of-concept and scalable enterprise AI operations.
Before starting AI projects, organizations need defined data ownership, sufficient quality, stable access pipelines, and governance for security and retention. Data readiness should also include label quality, metadata consistency, and monitoring for drift or bias risks. EBF’s AI Consulting approach runs data-readiness assessments to identify gaps early and define remediation before model development. This reduces rework and improves the chance of production-grade outcomes.
Build custom AI when the use case is core to competitive advantage, requires proprietary data logic, or needs deep integration that packaged tools cannot provide. Buy when speed and standard functionality are the priority. Many enterprises use a hybrid approach: buy commodity capabilities and build differentiating components. EBF’s AI Consulting approach helps organizations make this decision with architecture, TCO, and risk criteria before committing budget.
A well-structured 90-day enterprise AI pilot should include use-case selection, data-readiness assessment, solution design, working prototype, compliance checkpoints, KPI definition, and a clear go/no-go recommendation for production. Integration planning and security validation should start in the pilot, not after it ends. EBF’s AI Consulting approach structures pilots around these production-readiness criteria so organizations can make an evidence-based scale-up decision within the pilot window. This reduces wasted investment when a use case is not yet ready for production.
Your Request
Sounds good?
Let’s talk.
We know this is a big topic, which is why we are happy to provide simple informational discussions. Even if you are already further along, we would be happy to advise you.
