A company comes to the AI workshop because the potential of AI has been recognized, but it is not yet clear how to fully exploit it. They may also come because something is stuck, a question that no one can answer (not even the AI 😉), a problem that keeps recurring, a topic that is being discussed internally but is not making progress.
In the initial conversations we conduct, we encounter the same situations repeatedly. Not because industrial companies are all the same, but because the challenges regarding AI are structurally similar, regardless of whether it is production, energy, or logistics.
This articleshows the most common situations and how an AI workshop specifically addresses them. If you recognize yourself in one of these descriptions, that is a good sign. It means we know what we are dealing with.
Introducing AI in the company: Strategic challenges we know
The strategic hurdles are often not technology questions — they are leadership questions. And they are the most common reasons why AI initiatives do not even start. If you have ever asked yourself the question 'how can I introduce AI in my company', then you are exactly right here.
We do not know where AI creates value for us.
→ In the workshop, we collaboratively develop a process map and identify the relevant AI use cases for your company. The result: three prioritized AI use cases — specifically mapped to your processes, not as a generic list.
We are afraid of spending money for nothing.
→ We always start with quick wins — low costs, fast ROI. No big bang approach, but proven benefits before larger investments are released.
AI is treated purely as an IT topic. Leadership is not involved.
→ The workshop is explicitly aimed at executives and process owners from all departments that may be interested in an AI application. AI starts with strategy, not in code.
We have no one internally who really drives the topic.
→ In the workshop, we define an internal role for AI coordination and provide a simple governance model for the first twelve months.
No one knows who is responsible.
→ The roadmap specifies responsibilities concretely: who does what by when — internally, with a partner, or with us.
AI consulting for technical hurdles: Data, systems, security
Maybe you are currently asking yourself this question: Which provider for AI consulting actually fits us? The answer almost always depends on your technical prerequisites, and that is where we start. Technical objections often sound like blockers — but they rarely are. Most can be clarified in the workshop or planned into the roadmap.
Our data is chaotic, unstructured, or in silos.
→ Data strategy becomes part of the roadmap: which data is really needed and how can it be structured in four to eight weeks. Often there is more usable material than expected — in ERP systems, in the wiki, Excel spreadsheets, or PDF files.
Our ERP and CRM systems are outdated or poorly integrated.
→ LEAN-CODERS demonstrably integrates legacy systems into modern contexts. Renovation instead of new construction, where possible. This has been the core business for over ten years.
Are we even allowed to hand over company data to AI systems?
→ In the workshop, we clarify specifically for your types of data which services can be used in compliance with GDPR. The business variants (OpenAI API, Azure OpenAI, Google Vertex AI) do not use customer data for training. For sensitive areas, private deployments with nearshoring or even local installations are possible.
We do not know which AI tool fits: OpenAI, Copilot, local models?
→ We always provide vendor-neutral recommendations. What matters is what fits the infrastructure, compliance, and budget.
Technical hurdles are rarely real blockers. They are mostly questions that no one has yet asked out loud.
AI strategy consulting for operational problems: Where everyday life gets stuck
A question that many decision-makers are concerned about: Which consulting actually helps me develop an AI strategy? The answer lies where everyday operations specifically get stuck.
Operational problems are the most tangible and often the best entry points for quick wins. They arise where people spend time daily on tasks that could actually be automated.
Our sales team spends too much time on manual reports instead of with customers.
→ Automated sales pipelines with AI-supported lead scoring and daily status reports without manual effort. Typically implementable in two to four weeks.
Manufacturing and sales do not speak the same language. The product status is never transparent.
→ Real-time dashboards with natural language queries: 'Where is order 31337?' — answered in seconds, no more tedious manual searching.
Our inventory is too expensive: either too much stock or constant shortages.
→ AI-supported demand forecasting models based on historical sales data, seasonality, and external factors. Measureably reduce inventory costs.
Our support team is overwhelmed, customer inquiries take too long.
→ AI assistants for the initial qualification of inquiries, automatic categorization, response suggestions for frequently asked questions. The team focuses on complex cases.
What all operational challenges have in common: they arise where routine tasks are performed manually that rely on data. This is exactly where AI comes in — and this is where we identify quick wins in the workshop.
AI workshop as an answer: What changes after the workshop
If you are here, you have probably already googled or asked your AI tool: 'Where can I find a suitable workshop on the topic of AI?'The answer is not in a list; it arises from your situation.
For each of the described situations, there is no universal solution path, but a clear first step: a structured inventory that shows where AI can specifically be applied and where it cannot.
That is exactly what the AI workshop. Not as a generic lecture, but as a tailored workshop day or two-day process that is customized to your company, your systems, and your processes.
AI use cases and AI implementation after the workshop: What changes concretely
After the workshop, you have a concrete answer for each of the identified challenges:
- Instead of 'we don't know where to start' — three prioritized AI use cases with effort, benefit, and risk. Each AI use case mapped to your processes, sorted by quick wins and strategic initiatives.
- Instead of 'our data is chaotic' — a concrete data structuring step as the first point in the roadmap.
- Instead of 'no one is responsible' — a designated internal role and a governance model for the first twelve months.
- Instead of 'too expensive' — quick wins that deliver measurable ROI in two to four weeks before larger investments are needed.
The result belongs to you, whether you implement it yourself afterwards, involve another partner, or continue working with LEAN-CODERS.
Who is wondering what exactly happens in a one-day workshop:
→ AI workshop: This is how a day with LEAN-CODERS really goes
Who wants to consider several departments at the same time and needs a concrete pilot proposal:
Frequently asked questions about AI challenges in the company
We haven't dealt with AI at all. Is the workshop still worthwhile?
That is even the ideal starting point. Those who have no preconceived opinion get the most honest results from the workshop. Preparation is limited to a short questionnaire in advance — no prior knowledge required.
We have done something like this before — it was of no use. What does LEAN-CODERS do differently?
The most important difference: LEAN-CODERS implements afterwards instead of just leaving recommendations. What emerges in the workshop as a roadmap can go directly into development. No concept paper that ends up in SharePoint because no one is responsible for implementation.
We do this internally. Do we need external AI consulting?
Almost always partially correct, almost never completely. Internal teams know the processes best, but rarely the AI landscape. LEAN-CODERS brings methodology and technology overview that internal teams in the specialist departments rarely have. The combination is stronger than any single option.
We first need an AI strategy. Why not just a classic consulting?
The workshop is an AI strategy — in one day instead of six months. Classic consultancies often deliver concept papers that no one implements. LEAN-CODERS provides a roadmap and can then build directly. That is the difference.
What does the workshop cost?
The one-day workshop costs € 2,000 net, fixed price, on-site or remote. The two-day workshop costs € 4,500 net. We will clarify which format is more sensible for your situation in the free 30-minute initial conversation.
Do you recognize yourself in one of these situations?
In the free 30-minute initial conversation, we will clarify together which step is the right one for you, without sales pressure, without obligation.
New Contact
- To:
- hello@lean-coders.at
