Industry
In a plant, AI pays off where shop-floor data meets office decisions
The AI Business Center Foundation (AIBC) is a think tank and advisory partner that helps the boards of construction, industrial and technical-services companies adopt artificial intelligence so that it delivers measurable results and builds competitive advantage. In industry we start where production data turns into decisions.
Shop-floor automation is no longer the only issue. The office that manages it has become the issue
Industrial plants have been automating production for years. Meanwhile, the work that determines the margin increasingly happens away from the line: in quotations, orders, planning, complaints, maintenance and reporting. There, information passes through several systems and several departments, and each of them calls the same things by different names.
How cost arises
In a plant, cost arises at the interfaces: an order that passes from sales to production with an incomplete specification; a breakdown whose history is kept in three places; energy consumption that nobody has allocated to a line and a shift. AI tools can close these gaps, but only if the process has an owner and the data shares common names.
That is why in industry we work with the method of semantic transformation, that is, organising a company’s names, processes and data so that people, language models and board reports understand them the same way.
Segments
- Manufacturing plants: quotations, orders, quality, process engineers’ know-how.
- Logistics and warehousing: exceptions in the flow of goods, communication with carriers and customers.
- Energy and site utilities: allocating consumption to processes, reporting, environmental targets.
- Facility management: requests, inspections, the history of buildings and equipment.
What the Foundation does for industry
- Audit and strategy: where AI is justified in a plant, and where it is better to wait until the data is in order. AI audit and strategy
- Semantic transformation: process descriptions, a shared vocabulary for systems and departments, a report for the board. Semantic transformation
- Compliance: which AI uses in the plant require action under the rules, and from when. Compliance and ESG
- Funding: digitalisation, energy efficiency and competence projects in public programmes. Grants and funding
- Competence: programmes for the office, process engineers, maintenance and management. GenAI competence
The Foundation is vendor-neutral: we do not sell licences or implementations. We act on the board’s side — we help choose the contractor, prepare requirements and criteria, run the procurement procedure or tender, and assess bids and contractor quality. The board makes the decision.
Frequently asked questions
Does the Foundation implement predictive maintenance or machine vision systems?
No. We help assess whether such a solution is justified in a particular plant, whether the data is ready for it, how to measure the effect and what requirements to set for the vendor. The implementation is carried out by the technology vendor, an integrator or the plant's maintenance and IT departments.
Where should a plant start?
With one process in which work stalls for lack of information: the handling of requests and complaints, the preparation of quotations and estimates, the handover of an order between departments or the reporting of energy consumption. These processes have data in the company's systems and an owner, so the effect is easy to measure.
Is production data ready for AI straight away?
Rarely. The same parameter has different names in different systems, and part of the knowledge exists only in notebooks and in the heads of foremen. Gartner predicted (February 2025) that by the end of 2026 companies will abandon 60% of AI projects not supported by AI-ready data. That is why we organise names and sources first.
Let’s start with a conversation
Let us choose one process in which work in the plant stalls for lack of information. Arrange a conversation.