from Michael Pertek at
diselva's experts are regularly called upon to share our know-how with decision-makers in practical formats - be it in workshops, technical committees, associations or closed meetings of boards of directors or management. The focus is not on theoretical, academic constructs, but on sound experience from real projects.
We were recently invited by an industry association to give a presentation on the use of AI in business. The audience: decision-makers who think AI is relevant, but are wondering: Where do I start? What am I missing out on? What are the tangible benefits for my business?
This is where our presentation came in:
- Real examples instead of buzzwords: we don't show what's possible, but what works. From automated reporting to smart customer communications.
- Strategic embedding: How AI projects can be successfully integrated into business strategy and what needs to be done.
- Practical experience: We report on specific projects that we have implemented together with companies from different industries.
An example ...
AI is no longer an abstract topic for the future, but a living reality. It is changing processes, products, and business models every day. For managers, the question is not whether, but how an organization will face and actively shape this change. This is not trivial, especially if there is no concrete use case or if business and IT (technology) do not work hand in hand.
In compact and easy-to-understand presentations, we show how AI is already working in practice today and how a company can achieve specific use cases. It is important to understand the basics and to recognize, create and exploit opportunities. After all, AI is not the same as traditional software development.
What leaders should know about AI
What is AI, how does it work, and how can I use it in my context? AI is more than a technology. It is a strategic tool with the potential to increase efficiency, optimize costs, and drive innovation. But the key to success is having the right application, data, architecture, and organization.
Comparison of AI, Machine Learning & Deep Learning
Our approach to AI is ...
- Understandable instead of technical
Proven instead of hypothetical
Business relevant instead of visionary & detached
Three application examples with impact
- Automated reporting: Save time in controlling with intelligent data preparation.
- Intelligent customer communication: Chatbots and agents that simplify processes and improve quality - especially in service processes.
- Document automation: Offer and contract text at the touch of a button - consistent, fast, and compliant.
Uncomfortable - but important: Legal and ethical principles for the use of AI
Managers have a responsibility - even when it comes to introducing technology. Therefore, there are a number of key frameworks to consider when using AI:
- Data protection: The Swiss Data Protection Act and the EU GDPR require transparency, consent and purpose limitation for data processing.
- Explainability: Decisions made by AI systems must be comprehensible or even explainable in certain cases ("explainable AI").
- Fairness & anti-discrimination: AI must not reinforce social or ethical distortions ("AI ethics").
- Copyright: Content created with generative AI raises new intellectual property issues.
- Responsibility & Governance: Humans remain responsible - even when the machine is involved.
diselva helps companies to use AI responsibly - technically, organizationally and legally.
How do we proceed?
The diselva AI Excellence Framework
Turning ideas into real results requires structure. With our proven framework, we support companies holistically:
- Discover - identify strategic goals, build baseline, analyze enterprise architecture
- Validat - prioritize use cases, review data situation, analyze risks and business fit
- Prototype - develop, test and evaluate PoCs - and enable learning
- Scale - implement scalable, robust solutions and integrate with systems
- Sustain - long-term governance, monitoring, ethical control, continuous optimization
What matters most - concrete results and prototypes
This approach helps to balance opportunities and risks - and to realize the benefits of AI in the long term.
We offer more than just inspiration - we offer practical solutions:
- Workshops and expert presentations for management committees
- Potential analyses and feasibility studies
- Concrete implementation projects - together with you
In short: think strategically, try and implement.
Contact us - we look forward to exchanging ideas with you!
