March 11, 2026 – 09:00 – 15:30 CET
AUDIENCE
Team Managers, Department Managers, AI Managers
FORMAT
On-site at BlueCallom in Zürich
LANGUAGE
The discussion will be conducted in English
DATE
March 11th, 2026 – 09:00 – 15:30 (CET)
Day after the BlueCallom ight
LOCATION
Zürich Seefeld
REQUIREMENT
Managerial position
PRICE
Future fee CHF 3,500 per person
Introductory fee: CHF 800 per person for this first, March 11th program.
Your questions and suggestions up front
If you have SPECIFIC QUESTIONS or want us to address a SPECIFIC TOPIC,
Let us know up front by mentioning it in your registration.
Artificial Intelligence will be your most Mission Critical System.
Managing Enterprise AI is a mindset
You no longer only compete with other managers – you also compete with their AI.
Our Background
- Our founders built two multi-billion-dollar companies.
- We started in late 2022 on Enterprise AI and have been working for a solid 3 years.
- We have roughly 100 companies on our platform and have learned more than we could ever imagine.
Agenda
09:00 Networking
Coffee and gipfeli
09:30 AI leadership is a management discipline, not a technical one.
As a manager, you already make complex decisions every day:
• You understand financial control and forecasting
• You know how operational systems work
• You interpret dashboards, KPIs, and balance sheets
• You already use tools like spreadsheets and ChatGPT
In this program, we focus on the practical management questions every manager must be able to respond:
• What exactly is Enterprise AI — and how do I explain it to my teams and executives?
• Is “data cleansing” necessary? — and what is required to get started?
• What are the biggest differences between ChatGPT, Copilots, and Agents, and Enterprise AI Solutions?
• How can AI be applied directly to Sales, R&D, Innovation, Compliance, and Operations?
• What does AI mean for jobs, productivity, and team structures — short term and midterm?
• How do I measure productivity, impact, usage, and ROI of AI in everyday business operations?
Key management insight:
Every machine is eventually measured by its utilization.
AI is no different — but its impact is far greater.
10:00 – Enterprise AI Is About Leadership, Not Technology
Management perspective:
Imagine adding 10 intelligent digital workers for every employee over the next two years.
How do you organize, lead, measure, and scale that — responsibly and profitably?
Your IT organization will:
• Implement systems
• Ensure security and compliance
• Operate platforms and infrastructure
You drive and delegate how AI changes the way your team delivers additional value.
In this session, we focus on managerial ownership:
• What decisions stay with management?
• What can (and should) be delegated to IT?
• How do you define the new operational vision?
We address real management concerns:
• What data security means in daily operations
• What skills managers and teams actually need
• How employees typically react — and how to lead through it
AI is already mission-critical today and you will lead the transformation.
Coffee Break
11:00 – Enterprise AI Use Cases That Change Daily Work
We demonstrate working, real-world Enterprise AI systems and how they are used in everyday management.
Sales
• AI-driven sales processes where teams spend up to 80% of their time with customers
• Forecasts, reports, and pipeline management are handled autonomously
• Managers focus on decisions, not administration
Innovation
• Autonomous AI innovation pipelines from idea to blueprint and go-to-market in hours
• Management shifts from steering meetings to approving outcomes
Competition & Market Intelligence
• AI systems that monitor competitors, markets, and technologies in real time
• Daily executive briefings with recommendations before the workday starts
Compliance
• Automated pre-checks before approvals
• Compliance managers focus only on complex or high-risk cases
Executive Search
• AI-supported executive identification, evaluation, and benchmarking
• Leadership quality becomes measurable — including how well AI is used
AI Use Case Identification
• Why teams struggle to find impactful AI use cases on their own
• A structured management method to identify high-impact AI use cases beyond ChatGPT thinking
Key takeaway:
These systems are often cheaper than traditional software — and deliver significantly higher impact.
12:00 – Enterprise AI Platform: What Managers Need to Know
• What an Enterprise AI Platform looks like in practice
• What management controls — and what runs autonomously
• How productivity, usage, and adoption are measured with real reports
Key management questions answered:
• How long does implementation realistically take?
• What does scaling look like?
• Why traditional software vendors struggle to compete in this space
12:30 Lunch Break
14:00 – Enterprise AI Managed Services: What to Keep, What to Delegate
Enterprise AI introduces a new Agentic IT Layer on top of existing systems.
We explain:
• What Enterprise AI Managed Service Providers actually do
• What remains a management responsibility
• How risk, security, and availability are handled
Business impact:
• Shift from CAPEX to OPEX
• From fixed cost to variable, usage-based models
14:30 – AI Implementation Strategy: From Decision to Daily Execution
Leading the Transformation – how teams actually get AI trained, implement new work flowsand scale across multiple functions.
Topics include:
• A proven AI Implementation Framework
• Moving from pilots to production
• Resource planning, budgets, timelines, and governance
• Managing change without disruption
Transformation & Management principle:
Scale through controlled momentum.
1. Using an AI Implementation Framework to create an EAI strategy as a competitive advantage.
2. Understand what resources, skills, budgets, timelines, and execution support you can expect for your business and how you move from piloting to production and scaling.
3. Some important business model considerations for a pay-per-use model with no user subscription and no application licensing.
15:20 Q+A
15:30 Finish
We will be available for extended Q+A
Artificial Intelligence will be your most Mission Critical System.
- Meet new peers
Build a network with other executives and begin a journey that could not be more captivating. - Enterprise AI is a management discipline, not a technical one AI success depends on leadership decisions, not tools. Managers already have the core skills needed: financial control, KPI thinking, operational oversight. The critical question is not “Can AI do this?” but “Should it, and how do we measure it?”
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Managers must own the decisions, IT enables execution Management defines value creation, priorities, and outcomes. IT ensures security, compliance, and platform reliability. Confusing these roles is the fastest way to stall AI initiatives.
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AI fundamentally changes how daily work is organized Administrative work shifts to autonomous AI systems. Managers spend time on decisions, not preparation. Teams focus on customers, judgment, and exceptions — not reporting.
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The biggest AI gains come from end-to-end use cases, not tools ChatGPT alone delivers limited value. Real impact comes from AI embedded into workflows across: Sales, Innovation, Market & competitive intelligence, Compliance, Executive search and leadership assessment. These systems often outperform traditional software at lower cost.
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Enterprise AI introduces a new Agentic IT layer AI agents operate on top of existing systems, not instead of them. Managed services handle availability, security, and scaling. Management retains control over risk, priorities, and value creation.
Business shift:
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CAPEX → OPEX
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Fixed cost → usage-based economics
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Speaker
Axel Schultze, CEO
Christian Weh, VP Products
Marc Benesch, AI Instructor
