Some typical scenes from everyday AI life:
Scene 1: The hopeful start
A financial services provider is testing a custom GPT for customer communication. Works great. The team is delighted.
3 months later: Only 2 people use it.
Scene 2: The resistance
A production company wants to introduce AI for process optimization. The management is pushing. The team slows down.
Not out of unwillingness. Out of fear of losing control.
Scene 3: The overburdened entrepreneur
A GF wants to use AI to gain back time. But he doesn't have time to introduce AI.
The classic vicious circle.
Four gaps that slow down innovation:
Gap 1: The values gap
73% of employees are looking for reliability. 71% of managers want innovation. Without psychological security = no speed.
Gap 2: The pilot gap
62% cannot get out of the test phase. There is no method for moving from experiment to standard.
Gap 3: The role gap
Entrepreneurs are drowning in day-to-day business and administrative tasks. No time for strategy = no transformation.
Gap 4: The humanity gap
We optimize machines to perfection. But we still manage people like robots.
All four gaps have ONE common cause: organizations are inert and slow to change.
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Why many AI projects still fail
The good news? There are methods to gradually close the gaps - one by one.
1. closing the value gap
The problem:
Teams want security. The management wants speed. Without a bridge between the two = standstill.
The sprint: "Safe-to-Fail"
Step 1: Define ONE test workflow
Not 5 pilots at the same time. A single process with a clear rollback plan.
Example: A Swiss financial services provider tested AI-supported email triage with 3 people. Duration: 2 weeks. Every error documented, not penalized.
Step 2: Weekly 15-minute retro
Ask your team: "What went well? What do we change next week?"
This is continuous improvement in its purest form. Not quarterly reviews. Weekly adjustments.
Step 3: Transparency about learnings
Share publicly what didn't work. This builds trust faster than any success story.
Why it works:
Psychological safety does not come from talking. It comes from experiencing that mistakes lead to learning, not punishment.
Gap 2: Closing the pilot gap
The problem:
You have 3 successful pilots. But none of them becomes the standard. Why? The scaling method is missing.
The sprint: "One-Workflow-First"
Step 1: Choose the ONE workflow with the highest impact
Not the most complicated one. The one that saves the most time.
Practical example: Chief-of-Staff setup for a manager. Email triage + meeting prep + decision log.
Result: 8 hours back per week. Set up in 5 days.
Step 2: Scale step by step
Week 1: Manager uses it alone
Week 2: 3 more team leads test with
Week 3: 12 people use it productively
Not big bang. Iterative.
Step 3: Install user feedback
Every Friday: 20-minute check with users. What works? What doesn't? Adapt immediately, not in 3 months.
Why it works:
You don't get from pilot to standard through perfect planning. But through rapid iteration based on user feedback.
Gap 3: Closing the role gap
The problem:
You want to be an entrepreneur. But you've become a manager. No time for strategy = no transformation.
The sprint: "Time-Back" in 3 weeks
Step 1: Identify your top 3 time wasters
Not all at once. The three activities that cost you the most energy.
Typical candidates:
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E-mail management (often several hours/day)
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Meeting preparation and follow-up (1-2 hours/day)
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Decision documentation (1 hour/day)
Step 2: Automate ONE of them with AI
Example: Email triage with Microsoft Copilot or Gmail. Filters automatically: Urgent vs. Delegable vs. Informative.
Setup time: 2 hours. Pointing gain: 5-10 hours/week.
Step 3: Use the free time strategically
Block the recovered hours for strategy. Not for more admin.
Continuous improvement: tackle the next time waster every month.
Why it works:
You won't become an entrepreneur again with a 12-month plan. But by regaining time for strategic thinking every week.
Gap 4: Closing the humanity gap
The problem:
You optimize machines perfectly. But you manage people like robots. Rigid processes = no adaptability.
The sprint: "autonomy zones" in 2 weeks
Step 1: Define experimentation spaces
Where can teams make their own decisions without approval processes?
Example: "You may test AI tools as long as no customer data is affected."
Clear framework. Autonomy within it.
Step 2: Promote bottom-up innovation
Not just top-down targets. Let teams find their own quick wins.
A team in a production company has built its own custom GPT for shift planning. Without an IT project. In 3 days.
Step 3: Monthly extension of the autonomy zones
Based on learning successes: Where can we give more freedom?
Why it works:
Humanity in organizations is not created through values workshops. It comes from genuine autonomy in everyday working life.
Invitation to the KI-Café
Date: Wednesday, December 10, 2025
Time: 16:30-19:00
Location: St. Elisabeth Convent, Duxgass 55, 9494 Schaan
Manuel Pfiffner (CEO, sl.one) shows why using the cloud is a prerequisite for trustworthy AI:
Manuel gets to the heart of the matter:
"For many SMEs, digitalization sounds like a major project. The reality is different thanks to modern cloud platforms. We relieve our customers of the complexity of the infrastructure so that they can concentrate fully on the application. This turns IT into a practical tool that creates measurable efficiency gains in day-to-day work."
The team from mmind.ai shows three immediately usable Microsoft Copilot examples:
→ Analyze data in Excel
→ Summarize email histories
→ Create co-pilot knowledge base
Afterwards: Housewarming in our new gallery in the monastery.
