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Why Generative AI can’t fix complex equipment

Featured

Causal AI

Why Generative AI can’t fix complex equipment

Across the service industry, we hear service leaders learning a hard truth: AI that sounds confident isn’t necessarily correct. Conversational, generative, and agentic AI systems can handle everyday questions with impressive fluency, but when technicians rely on them to fix critical equipment, “close enough” can mean downtime, safety issues, or compliance failures.

Lars Hammer

·

February 24, 2026

why-generative-ai-cant-fix-complex-equipment

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Why Generative AI can’t fix complex equipment

Causal AI

Why Generative AI can’t fix complex equipment

Across the service industry, we hear service leaders learning a hard truth: AI that sounds confident isn’t necessarily correct. Conversational, generative, and agentic AI systems can handle everyday questions with impressive fluency, but when technicians rely on them to fix critical equipment, “close enough” can mean downtime, safety issues, or compliance failures.

Lars Hammer

·

February 24, 2026

How to optimize machine troubleshooting with IoT data

Data & IoT

How to optimize machine troubleshooting with IoT data

How to optimize machine troubleshooting with IoT data to dramatically reduce troubleshooting time, use fewer spare parts and reduce dispatches.

Lars Hammer

·

January 21, 2026

Knowledge Value Chain – Acquisition: Unlocking Knowledge’s Source

Knowledge capture

Knowledge Value Chain – Acquisition: Unlocking Knowledge’s Source

Knowledge Acquisition: Sourcing, Collecting, and Transforming explicit and tacit technical troubleshooting knowledge for advanced products.

Lars Hammer

·

January 3, 2026

The right knowledge. For the right people. At the right time.

Rollout & Adoption

The right knowledge. For the right people. At the right time.

Customers, technicians, partners and resellers all need access to your knowledge base when troubleshooting in complex products.

Lars Hammer

·

November 6, 2025

How do we capture knowledge?

Knowledge capture

How do we capture knowledge?

How do we actually capture all that knowledge embedded within the organisation? Technicians need both tacit and explicit knowledge on-site.

Lars Hammer

·

April 16, 2025

Troubleshoot High Level Symptoms in Complex Machines

Knowledge capture

Troubleshoot High Level Symptoms in Complex Machines

Getting our heads around how to troubleshoot high level symptoms that the field service engineers face all the time out there.

Lars Hammer

·

April 9, 2025

How much time should you invest in a technical troubleshooting knowledge base?

Service strategy

How much time should you invest in a technical troubleshooting knowledge base?

Choosing the right service strategy is hard. Here are my recommendations for how much time to invest in a technical troubleshooting knowledge base.

Lars Hammer

·

February 24, 2024

Streamlining Troubleshooting: How the Knowledge Value Chain Enhances Field Service Efficiency

Knowledge capture

Streamlining Troubleshooting: How the Knowledge Value Chain Enhances Field Service Efficiency

Each phase of the Dezide Knowledge Value Chain – acquisition, validation, and sharing – plays a pivotal role in transforming raw data and information into actionable insights and knowledge.

Lars Hammer

·

December 13, 2023

A 10 year AI journey in revolutionizing a service department – part one, the past

Rollout & Adoption

A 10 year AI journey in revolutionizing a service department – part one, the past

The story of taking a journey from unstructured content, hidden knowledge, and traditional documentation to modern, streamlined service.

Lars Hammer

·

April 19, 2021

How to quit your old service strategy, embrace digitalization and change the World, part 2

Service strategy

How to quit your old service strategy, embrace digitalization and change the World, part 2

Digitalization and knowledge management are the key ingredients for turning service departments into modern business units.

Lars Hammer

·

August 23, 2017

How to quit your old service strategy, embrace digitalization and change the World, part 1

Service strategy

How to quit your old service strategy, embrace digitalization and change the World, part 1

No matter how high tech a tool box the technician has, knowledge remains the key ingredient when assigning the best possible man for any given problem.

Lars Hammer

·

June 1, 2017

A static approach to serving relevant knowledge at the right time

Procedures

A static approach to serving relevant knowledge at the right time

Assembling complex machinery like wind turbines, trucks, and excavators can take 100s or even 1000s of hours on-site. The on-site field service team must assemble and commission properly, follow the instructions carefully, avoid skipping steps, and ensure the instructions are carried out in the correct order.

Lars Hammer

·

January 17, 2017

Why we need a knowledge model for troubleshooting

Knowledge capture

Why we need a knowledge model for troubleshooting

Troubleshooting systems combine human knowledge and the computational power of computers, a fusion enabled by an underlying mathematical knowledge model capable of reasoning far better than humans.

Lars Hammer

·

December 6, 2016

Transform knowledge into digital troubleshooting intelligence

Knowledge capture

Transform knowledge into digital troubleshooting intelligence

Capturing knowledge in a structured form is even more relevant and becomes even more evident when we look at troubleshooting. Using captured knowledge in a troubleshooting scenario requires that we must somehow be able to store all of our data and information in such a way that we can apply our interpretation and previous knowledge to it. We need a model-based approach to eliciting our knowledge into the computer using Causal AI.

Lars Hammer

·

September 26, 2016

Data, Information, knowledge – why is it so important?

Knowledge capture

Data, Information, knowledge – why is it so important?

According to Webster’s Dictionary, knowledge is “the fact or condition of knowing something with familiarity gained through experience or association.” In the context of business enterprises, we see that knowledge tends to be interpreted as possession of experience (tacit knowledge) as well as possession of factual information (explicit knowledge) – or where to get it.

Lars Hammer

·

January 12, 2016