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AI Consulting: What it delivers and when it is worthwhile
The topic of AI consulting has seen enormous momentum over the past two years. According to a Bitkom study from 2025, every third company in Germany now uses artificial intelligence – almost twice as many as just a year earlier. At the same time, 53 percent of the surveyed companies report lacking the technical know-how for implementation, and 51 percent see insufficient personnel resources as a barrier. This is exactly where specialized AI consulting comes in: it helps companies take a structured approach to adopting artificial intelligence and find the right solutions for their individual needs.
What is an AI Consulting Agency?
AI consulting helps companies strategically and operationally integrate artificial intelligence into their business processes. The range of services extends from analyzing existing workflows and identifying specific use cases to technical implementation and building competence within the team.
Unlike traditional IT or management consultancies, specialized AI agencies bring deep knowledge of current AI models, automation platforms, and data-driven workflows. They translate technical possibilities into concrete business outcomes and ensure that implemented solutions function sustainably. Modern AI consulting focuses not only on technology but also accompanies organizational change – through training, change management, and the establishment of data-driven decision-making processes.
The spectrum of consulting services ranges from targeted workshops for potential analysis to long-term support for complete AI transformation projects. The crucial point: good AI consulting does not sell technology for technology’s sake, but solves concrete business problems.
Who benefits from collaboration?
Basically, any company with repetitive processes, data handling, or competitive pressure can benefit from AI strategy consulting. However, the actual need should be carefully assessed. Collaboration is particularly beneficial for:
- Start-ups and scale-ups: Building scalable, AI-supported processes from the beginning – whether in sales, marketing, or customer service.
- Medium-sized companies: Companies without an internal AI department that feel competitors are moving ahead. Often, the greatest leverage lies here because sufficient data and processes exist, but internal resources are lacking.
- Corporations and large enterprises: Support for complex transformation projects, such as automating entire departmental processes or building internal AI competence.
Companies facing particular challenges, such as skilled labor shortages or increasing cost pressures, also benefit from targeted AI strategies. From my experience as a consultant, the potential is currently greatest in the B2B mid-market, because many processes are still manual and can be automated with comparatively little effort.
Why choose a specialized agency?
Working with a specialized AI consultancy offers several advantages over trying to implement AI purely internally. Naturally, if a company has the in-house expertise and capacity, much can be advanced internally. For all other companies, the following arguments favor external support:
- Expertise and speed: AI consultants work daily with the latest tools and models. What would take months internally can often be implemented in just a few weeks.
- Objective external perspective: Outsiders can identify automation potential often overlooked internally because existing processes are taken for granted.
- Access to proven tech stacks: Specialized agencies bring tested tool combinations, saving evaluation time and reducing investment mistakes.
- Competence building: Reputable consulting services do not end with implementation. They empower the internal team to independently further develop the solutions.
The competitive advantages resulting from a well-executed AI strategy are considerable: shorter lead times, better data quality, fewer manual errors, and measurable efficiency gains. According to Bitkom, AI achieved a breakthrough in the German economy in 2025 – the question for companies is no longer whether, but how quickly they integrate AI into their processes.
Services & Tasks in Detail
Strategy Development: At the beginning of every AI consulting engagement is strategy development. Together with the company, it is analyzed which processes offer the greatest leverage and where quick wins are possible. The result is typically an AI roadmap that clearly defines priorities, timelines, and expected outcomes.
Operational Implementation: Operational implementation includes the technical deployment of identified use cases: process automation with tools like Make.com or n8n, building AI-supported workflows for sales, marketing, or customer service, as well as implementing chatbots, automated reporting, or lead scoring systems. The greatest potential is often revealed in process automation – when a process that previously took hours is suddenly completed in minutes.
Controlling and Further Development: After go-live, the real work begins: monitoring, optimization, and scaling. Good consulting goes beyond mere implementation and ensures that solutions function in everyday operations and are continuously developed. This includes regular performance reviews, adapting workflows to changing requirements, and gradually building competence within the internal team so the company can operate independently in the long term.
What does AI consulting cost?
The cost of AI consulting depends heavily on scope, complexity, and the experience of the consultants. Common pricing models in the market are:
| Pricing Model | Description | Typical Price Range |
|---|---|---|
| Daily Rate | Billing per consultant day, often for workshops or strategy consulting | €800–2,500 per day |
| Fixed Price | For clearly defined projects, e.g., process analyses or tool implementation | €3,000–50,000 per project |
| Retainer | Monthly flat fee for ongoing consulting, optimization, and support | €2,000–10,000 per month |
| Performance-based | Compensation based on measurable results, e.g., saved hours or conversion increases | Individual |
Which Tools & Software are used?
The tech stack of an AI consultancy varies depending on the use case. The most commonly used platforms include:
- Make.com and n8n for visual process automation – both platforms allow building complex workflows without deep programming knowledge.
- OpenAI API and Claude for AI-supported text processing, classification, and data extraction.
- Airtable as a flexible database for CRM processes, project tracking, and reporting.
- Clay for automated lead research and data enrichment in B2B sales.
Additionally, depending on the use case, other specialized solutions may be used: Notion or ClickUp for project management, HubSpot, Attio, or Pipedrive as CRM, and various analytics tools for monitoring AI workflows. The key is not the number of tools, but a well-thought-out tech stack that integrates seamlessly.
How to choose the right agency?
Selecting the right AI consultancy is critical to project success. A structured process helps:
- Needs analysis: Clearly define the goals you want to achieve with AI consulting – e.g., process automation, AI strategy, or new tool implementation.
- Industry understanding: Does the agency understand your business model? The best technology is of little use if the professional context is missing.
- References and case studies: Ask for concrete project results. Measurable KPIs like saved hours or conversion improvements are more meaningful than general descriptions.
- Tech-stack transparency: Reputable providers openly explain which tools they use and why.
- Pilot project: A small, clearly defined initial project minimizes risk and demonstrates whether collaboration works.
- Competence building instead of dependency: A good agency empowers the internal team for the long term. If a consultancy only provides black-box solutions that won’t function without them, it is a warning sign.
Conclusion on AI Consulting
AI is no longer hype but a concrete tool for increasing efficiency and competitive advantage – the numbers clearly show this. But technology alone is not enough. What makes the difference is a well-founded AI strategy that fits the company and proper implementation that works in everyday operations.
PwC predicts that AI could increase Germany’s GDP by over eleven percent by 2030. Companies that invest in professional AI consulting now gain a head start that will be difficult to catch up in a few years. The goal is not to immediately overhaul everything – but to start with the right use cases, achieve measurable results quickly, and build from there.
My personal assessment: Not every company immediately needs comprehensive consulting. Sometimes a good workshop is enough to set the right course. The crucial point is to take action – because technology and competition won’t wait. Companies that lay the foundation for a data-driven organization today will benefit tomorrow.
About the Author
Jens Bohse, formerly Growth Lead at OMR, leads bakedwith, an AI consulting firm for mid-sized companies and startups. He advises companies on the introduction of artificial intelligence – from process analysis and tool selection to implementation. bakedwith focuses on automation and AI strategies that measurably save time and costs.