Having to act without knowing the limits.
AI in the company
You partly know what it's about and what would need to be done, and partly also how. But with AI, boundaries blur: technology, processes, roles, products, and leadership all affect one another. I guide you from an initial assessment through real pilots to lasting practice. Together with the people who work with it.
Schedule an initial conversationHow you can tell
What is it about, and what isn’t it about?
Processes, products, knowledge, customer contact, security: AI touches almost everything. Where the boundaries of the topic lie is still open.
What affects what?
A tool changes processes, processes change roles, roles change leadership. The interactions are hard to predict.
What is already clear?
You know some things: first ideas, first experiments, maybe shadow AI in the company. What’s missing is the overall picture you can base decisions on.
Realism, not hype
What AI can really do today, and what it can’t. Concrete use cases instead of promises.
With the people
Your team helps shape it instead of having something imposed on it. That determines acceptance.
Built to last
No flash in the pan: AI that sticks in daily work, with the know-how staying in-house.
Your path to AI that works
The three steps follow the three stages: clarify, design, implement.
Stage 1 · AI assessment
One workshop day for clarity.
Strategic orientation: Where does your company stand, where does AI help in concrete terms (and where not), and what are sensible steps?
Outcome: A solid basis for decisions, an AI landscape map, first prioritized use cases, clear grounds for go/no-go
1 day · Terms in the initial conversation
Stage 2 · AI strategy & pilots
Strategy development and testing in practice
We develop your AI strategy and get the first use cases running as real pilots. With your team, in a participatory way.
Outcome: AI roadmap, governance structure, prioritized use cases, 2–3 running pilots, enabled employees, and training.
Scope based on context
Stage 3 · Integration & AI leadership
From pilots to practice & infrastructure
Systematic optimization, transfer into line operations and processes, clear responsibilities, and capability that now keeps growing.
Outcome: AI as infrastructure, an AI leadership strategy, a scaling plan, and capability that stays in-house and grows.
Scope based on context
Most AI projects don’t fail because of the technology.
They fail because of knee-jerk action, buying tools without a strategy, shadow AI operating out of sight, and pilot projects that fizzle out in isolation.
The tools are here, and so is the pressure. The snag is elsewhere: Where does AI really help in your processes? Where does your team stand on it? And how does a pilot become lasting practice rather than a flash in the pan?
This is exactly the path I walk with you and your people. Sounds interesting? Let’s talk
Who guides you
I come from leadership, and I understand technology. I assess technology as a whole: what it can do, what it changes in a company, and what it takes for it to hold. I’m not an “AI consultant”: I also see the people, the lines of power, the culture, and the unspoken. These are the dimensions where AI projects fail before the technology even comes into play. That’s why I guide rather than just advise.
More about me personally: patrickschmid.info
Current engagements
Among other engagements, I’m currently guiding a mid-sized company through its AI adoption, from leadership alignment to implementation.
Qualifications
Executive MBA (SMBS Salzburg). Computer science degree. CISIS12 Information Security Officer and IT Security Officer (TÜV). Trained in systemic approaches, agile methods, and leadership diagnostics. German and English (C2). Two decades at the intersection of strategy, communication, leadership, and change.
What else we look at
On the way to AI, four elements come into view. Depending on your situation, we examine one or more of them more closely.
What is part of AI, and what isn’t?
Decision Architecture
Which decisions are coming up, and which others are you locking in along with them without noticing? We clarify what belongs to the topic and what doesn’t.
What does leadership need to learn?
Leadership
How does a leadership team lead when knowledge, roles, and pace are shifting because of AI? We make visible what changes in how people lead.
What changes in the processes?
Organization
Which processes, interfaces, and responsibilities have to change for AI to hold up in daily work? We test them in pilots and in practice.
AI in your offering
Products & services
How do AI features land with your customers, and where do they create disappointment instead of value? We test it with customers.
AI is change. Let’s shape it.
The first step is clarity: the AI assessment.
Approach
The path in three stages
- Initial conversationBefore stage 1: the initial conversation. Clarity on whether to continue, and with what.
- Stage 1ClarifyFindings: what holds up, what blocks, what options there are
- Stage 2Design or decideSolutions, developed and tested with your people in short cycles
- Stage 3ImplementFindings and solutions become practice and structure, as a project or ongoing
Let's get to know each other.
The first step is clarity: an initial conversation.
Schedule an initial conversation