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Digital Maturity Assessment

Lindström Präzisionstechnik GmbH

AI-Strategieberatung 2026

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Digital Maturity Assessment

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https://ai-strategy.pro/q/3d9023b5-3f8d-4532-89c1-ed3374fe16a9/maturity_assessment

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Overall score: —

0 / 7 categories scored

Category	Level 1: Initiation	Level 2: Development	Level 3: Application	Level 4: Integration	Level 5: Optimization
Business model & strategy	Initial thoughts on AI use, no clear strategy.	Development of first AI strategies, pilot projects, initial thoughts on transforming the business model.	Clear AI strategy aligned with business goals, business model adapted to AI.	AI is fully integrated into the business model, driving innovation and market opportunities.	AI strategy leads to new business models; the company uses AI to reshape markets.
Organization & processes	No organizational anchoring of AI.	First organizational structures and processes for AI projects.	AI is firmly established in selected processes.	AI is integrated across departments.	AI is a central part of the organizational culture, with continuous process optimization.
People & culture	Low awareness and low AI knowledge.	First training and awareness-building for AI.	Widespread AI competencies and acceptance in daily work.	AI competencies are part of professional development, with interdisciplinary collaboration.	AI excellence across the workforce, continuous learning and an innovation culture.
Technology & data	Basic IT infrastructure, without AI orientation.	First AI-specific technologies and data structures.	Advanced technologies support AI applications; data is used systematically.	Integrated technology platforms and a structured data strategy supporting AI.	Leading technology and data infrastructure for continuous innovation and real-time adaptation.
Processes & customers	No use of AI in processes or customer interaction.	First pilot projects for process automation and customer interaction.	AI optimizes processes and improves customer interaction.	Fully integrated, AI-supported processes and personalized customer interactions.	AI transforms processes and delivers tailored, real-time customer experiences.
Legal & ethics	Little consideration of legal and ethical questions.	First thoughts on compliance, data protection, and ethics.	Clear guidelines for legal and ethical questions, training, and implementation.	Comprehensive integration of legal and ethical standards, continuous review.	Pioneering role in developing and implementing best practices in law and ethics.
Data protection & compliance	No consideration of data protection and compliance.	First engagement with data protection requirements.	Clearly defined data protection and compliance guidelines are implemented in AI projects.	Data protection and compliance guidelines are fully integrated into all processes.	Data protection & compliance as leading standards, proactive measures, and an industry role model.

Business model & strategy

• Is there a formulated AI strategy linked to the overall business strategy?
• What role should AI play in the future business model?
• Are there any AI pilot projects already underway?

Level 1: Initiation

Initial thoughts on AI use, no clear strategy.

Level 2: Development

Development of first AI strategies, pilot projects, initial thoughts on transforming the business model.

Level 3: Application

Clear AI strategy aligned with business goals, business model adapted to AI.

Level 4: Integration

AI is fully integrated into the business model, driving innovation and market opportunities.

Level 5: Optimization

AI strategy leads to new business models; the company uses AI to reshape markets.

Organization & processes

• Are there dedicated roles or bodies responsible for AI topics?
• How are AI projects currently organized and governed?
• Are AI-related processes documented or standardized?

Level 1: Initiation

No organizational anchoring of AI.

Level 2: Development

First organizational structures and processes for AI projects.

Level 3: Application

AI is firmly established in selected processes.

Level 4: Integration

AI is integrated across departments.

Level 5: Optimization

AI is a central part of the organizational culture, with continuous process optimization.

People & culture

• How aware is the workforce of AI in general?
• What AI-related training has taken place so far?
• How open is the company culture toward change driven by AI?

Level 1: Initiation

Low awareness and low AI knowledge.

Level 2: Development

First training and awareness-building for AI.

Level 3: Application

Widespread AI competencies and acceptance in daily work.

Level 4: Integration

AI competencies are part of professional development, with interdisciplinary collaboration.

Level 5: Optimization

AI excellence across the workforce, continuous learning and an innovation culture.

Technology & data

• What does the current IT infrastructure look like?
• How accessible and well-structured is the existing data?
• Is there existing experience with AI tools or platforms?

Level 1: Initiation

Basic IT infrastructure, without AI orientation.

Level 2: Development

First AI-specific technologies and data structures.

Level 3: Application

Advanced technologies support AI applications; data is used systematically.

Level 4: Integration

Integrated technology platforms and a structured data strategy supporting AI.

Level 5: Optimization

Leading technology and data infrastructure for continuous innovation and real-time adaptation.

Processes & customers

• Is AI already used in operational processes?
• Are there any AI-supported touchpoints with customers?
• Where are the biggest potentials for process automation seen?

Level 1: Initiation

No use of AI in processes or customer interaction.

Level 2: Development

First pilot projects for process automation and customer interaction.

Level 3: Application

AI optimizes processes and improves customer interaction.

Level 4: Integration

Fully integrated, AI-supported processes and personalized customer interactions.

Level 5: Optimization

AI transforms processes and delivers tailored, real-time customer experiences.

Legal & ethics

• Are there guidelines for the ethical use of AI?
• How are legal risks of AI applications handled?
• Have employees been trained on legal and ethical aspects?

Level 1: Initiation

Little consideration of legal and ethical questions.

Level 2: Development

First thoughts on compliance, data protection, and ethics.

Level 3: Application

Clear guidelines for legal and ethical questions, training, and implementation.

Level 4: Integration

Comprehensive integration of legal and ethical standards, continuous review.

Level 5: Optimization

Pioneering role in developing and implementing best practices in law and ethics.

Data protection & compliance

• What is the current state of data protection for AI applications?
• Are there defined compliance guidelines for AI projects?
• How is compliance with data protection requirements monitored?

Level 1: Initiation

No consideration of data protection and compliance.

Level 2: Development

First engagement with data protection requirements.

Level 3: Application

Clearly defined data protection and compliance guidelines are implemented in AI projects.

Level 4: Integration

Data protection and compliance guidelines are fully integrated into all processes.

Level 5: Optimization

Data protection & compliance as leading standards, proactive measures, and an industry role model.