Bianca J. Schulz – AI Transformation Partner | Founder of 77Applied

I'm an AI Transformation Partner that helps you understand what an AI transformation actually is.

How I help

Every organization is different. That's why we tailor an engagement to your needs. Where are you right now in your AI adoption? I meet you there and explain the next steps in easy-to-understand words.

AI is not an IT project. My focus is on the organization and the way of working, not only on the technology. With deep experience in agile transformations, I bring the organizational depth that a successful AI transformation requires.

And while many in this field focus only on ROI, I also focus on the people behind every transformation: your employees and your customers. Sustainable AI adoption depends on both.

The Discipline Net

A living map of the disciplines you need to master to become an organization that uses AI to transform itself – and to grow into a true learning organization that values both results and the people behind them. Soon, the Discipline Net will also include Agentic AI and Governance & Compliance as interconnected disciplines.

  1. Business Objectives & Customer Orientation
  2. End-2-End Value Stream
  3. Muda – 8 Types of Waste
  4. Simplicity
  5. Work in Progress Limits
  6. Autonomy & Boundaries
  7. Assumptions About People
  8. Innovation
  9. Recognition & Performance
  10. Prioritization & Funding
  11. Winning Hearts & Minds Without Control
  12. Trust, consistency & reliability
  13. Team Design & Hierarchies Outside the Team
  14. Incentives
  15. Transparency
  16. Organizational & Individual Learning
  17. Cadence & Rhythm
  18. Systems Thinking & Problem-Solving
  19. Hypotheses, Experiments, Measure

About me

Bianca J. Schulz. I'm easy to work with, direct, and high-agency. For my full background, see LinkedIn.

Walk the talk – building what I advise on

I'm currently building an agentic AI system on sovereign infrastructure, using open-source frameworks running locally, with a clear path toward fully local models.

Every use case is designed to meet EU AI Act requirements from day one, covering risk classification, transparency, and data residency.

Governance is a core pillar from the start: internal standards for how AI operates within my business, and compliance with the legal frameworks that regulate it.

I document this journey in plain language on Substack. When I advise clients on their AI transformation, I draw on firsthand experience of building a compliant, sovereign AI stack from scratch.

77Applied is currently in formation. Formal registration is pending.

A long career

A long career, starting in database development and software engineering, then moving into roles as Project Lead, Scrum Master and Agile Coach. I've sat in leadership teams with responsibility for up to 7 teams in parallel, driven agile transformations end-to-end, and stayed technically hands-on – close enough to the code, the data and the models to call out what works and what doesn't. I've worked inside or close to nearly 40 companies, from 5-person teams to 800,000-employee enterprises, across 4 continents and in 3 languages.

Learn with me

In the Discipline Net, you see the many questions that my work with you will clarify individually for your organization. I write articles on Substack that explore and explain each topic in depth. On LinkedIn I turn these into small lessons. Soon I will also explain the principles on YouTube. Together it builds the foundation for a system that enables your organization to achieve your goals.

Everything I write about I have successfully applied in many companies, so it is 100% practice-tested. My strength lies in turning principles into practice, getting people excited to join in, and making learning fun.

  • Read my articles on Substack
  • Connect with me on LinkedIn
  • Coming soon: Watch my videos on YouTube

Contact

Bianca J. Schulz
Hublandplatz 1
97074 Würzburg
Germany
Email: office@biancajschulz.de
Phone: +49 170 667 2560
Book a free call

Working hours: 06:00–22:00 Europe/Berlin. Languages: English, German, French.

Full machine-readable version: /llms-full.txt · German: /llms-full-de.txt