Know how to introduce AI in your company
Our blog: articles and practical knowledge from our projects, our research and our trainings.
Quick answers
To make AI work in daily operations, companies proceed in five steps: They choose use cases with a clear benefit and decide between buying and building. They choose the model and how to connect their data. They automate workflows with AI agents whose results experts approve. They train their team. And they check the EU AI Act, data protection and security from the start.
Where does AI pay off, and should we build or buy?
Many midsize companies use AI without defining where it pays off: according to a survey of 517 companies by the FZI Research Center for Information Technology, 40 percent use AI but only 21 percent have an AI strategy (October 2025). AKARA Solutions' Discovery compares your current workflow with two target states, with and without AI agents, before you invest. Source: FZI Research Center for Information Technology, October 6, 2025
Learn more: Guide (in German): AI strategy for small businessesGlossary (in German): Artificial intelligenceSeminar (in German): AI for advanced users: from idea to applicationService: Consulting
Which AI model fits, and how does your data get in?
The model determines the cost and quality of an AI application, which is why AKARA Solutions chooses it for each use case. Companies usually connect their own documents via retrieval-augmented generation (RAG): according to AWS, new documents get into the system within minutes this way, while retraining the model takes hours to days. Source: AWS Prescriptive Guidance
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Multimodal AI
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Learn more: Guide (in German): From prototype to appGlossary (in German): RAG (retrieval-augmented generation)Seminar (in German): AI for advanced users: from idea to applicationService: Operations and infrastructure
What can AI agents do, and where are their limits?
An AI agent works through a task in several steps on its own and uses your systems along the way. Gartner expects up to 40 percent of enterprise applications to include such agents by the end of 2026 (August 2025). At the same time, Gartner expects more than 40 percent of agentic AI projects to be canceled by the end of 2027 (June 2025). That is why AKARA Solutions builds agents so that your experts sign off where their judgment matters. Source: Gartner, press releases of August 26, 2025 and June 25, 2025
Learn more: Guide (in German): Automation with n8n and MakeGlossary (in German): AI agentSeminar (in German): Agentic AI: automating tasks with AIService: Implementation and integration
In the initial call, we work out which step should come first for you.
Book a callHow does your team learn to work well with AI?
Whether AI makes a difference in daily work depends on how confidently the team uses it. In a survey of 243 users, 75.7 percent said AI tools help them complete tasks faster (Anam 2025). The AKARA Academy trains teams live in two-day seminars (in German), from the basics to AI agents. Source: Anam 2025, arXiv
Learn more: Guide (in German): Prompt engineering basicsGlossary (in German): Prompt engineeringSeminar (in German): Prompting for beginnersService: Training
What do the EU AI Act, data protection and security require?
The EU AI Act applies in stages. Since February 2025, Article 4 has required companies to take measures to support the development of their staff's AI literacy; under the Digital Omnibus, the obligations for high-risk systems apply from December 2, 2027 (Annex III) and August 2, 2028 (Annex I). AKARA Solutions classifies every application under the EU AI Act and clarifies data flows and access rights with your IT. Source: Regulation (EU) 2026/1744 and the timeline of the European Commission's AI Act Service Desk
Learn more: Guide (in German): Data protection and AIGlossary (in German): EU AI ActSeminar (in German): AI compliance and security (EU AI Act)Service: Compliance and security
AI in your industry
Use cases, figures and contacts for each industry.
Frequently asked questions
How does a company get started with AI?
With a workflow that comes up often and takes a lot of time today. For that workflow, you check data, systems and benefits, build a prototype on real data and measure what it saves. At AKARA Solutions, this first step is called the Discovery: we map your workflow and compare it with two target states, with and without AI agents.
What does an AI project with AKARA Solutions cost?
That depends on the workflow, so every project starts with a Discovery at a fixed price, which we name in the initial call. If you go ahead, the Discovery is credited. You then receive a fixed price for the entire project with a price guarantee: it holds even if the implementation takes longer than planned.
Build or buy AI: which is better?
Usually a combination. Purchased software covers standard tasks; workflows that give you a competitive edge are worth a solution of your own. What matters is whether strategy, team and processes fit the chosen combination; many AI initiatives fail because of people and processes, less often because of the technology. Our Discovery shows before you decide what each path saves in time and cost.
Do we need our own data specialists for AI?
Not to get started. For most applications, connecting existing documents and systems is enough, and AKARA Solutions takes care of that. Above all, your team needs practice working with AI. The AKARA Academy trains your team in two-day live seminars (in German), and during the project we transfer the knowledge to your team step by step.
What obligations does the EU AI Act bring?
That depends on how your company uses AI. Since February 2025, Article 4 has required measures to support the development of your staff's AI literacy; the law does not prescribe mandatory training or a certificate. Additional obligations apply to high-risk systems from December 2, 2027 or August 2, 2028.
Which AI model does AKARA Solutions work with?
With Claude by Anthropic. AKARA Solutions is a partner in the Claude Partner Network. We choose which Claude model runs in your application based on the task. We manage model costs for each application.
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Let's talk about your first use case.
In the initial call, we work out which workflow pays off first and what it needs.