Master in Business Administration in Artificial Intelligence (MBA in AI)
Welcome to a future-focused learning experience at our Berlin campus, where Europe’s leading tech landscape meets world-class business education. We are proud to offer our Master in Business Administration in Artificial Intelligence (MBA in AI), delivered in prestigious partnership with the Universidad Católica San Antonio de Murcia (UCAM), Spain.
This isn't just a postgraduate degree; it’s a high-impact journey designed to turn your interest in emerging technology into visionary leadership. In an era where data and automation are redefining every industry, we bridge the gap between complex algorithmic potential and the strategic realities of corporate management. Whether you envision yourself leading an AI transformation at a Fortune 500 company, overseeing ethical tech integration, or launching your own AI-driven venture, our curriculum provides the executive acumen and technical intuition needed to thrive.
At EIIET, we recognize that the future of business is intelligent. To help you carve out your specific niche in this rapidly evolving market, the MBA in AI programme offers three distinct specialization tracks. This allows you to tailor your expertise to your specific professional goals—ensuring you graduate not just with an
| Type of Study: | Master of Business Administration (MBA) |
| Major: | Artificial Intelligence and Business Strategy |
| Field of Study: | Economic Sciences & Digital Transformation |
| Speciality subjects (choose one): |
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| Campus Location: |
Hamburg, Germany |
| Study Mode: |
Full-time (on campus) |
| Duration: | 18 Months |
Offered Specialty Courses
- Introduction to Artificial Intelligence
- Business Administration Fundamentals
- Data Analytics for Business
- Project Management for AI Integration
- Leadership in AI-Driven Organisations
This module takes you behind the curtain of the most significant technological shift of our time. It moves beyond the hype of "robots" and "sci-fi" to explore the engine of the modern world: the ability of machines to learn, reason, and solve complex problems. You will learn to navigate the bridge between raw data and strategic decision-making, understanding not just how the technology works, but why it is fundamentally changing the way we lead organizations.
You will learn to balance the immense power of automation with the critical responsibility of human oversight. From understanding how a neural network "thinks" to evaluating the ethical implications of algorithmic bias, this subject ensures you can lead tech-driven teams with both technical confidence and a moral compass. In a world where data is the new oil, you will become the architect who knows how to refine it into meaningful, actionable intelligence.
- The Evolution of Intelligence: Trace the journey from simple automation to deep learning, understanding the transition from "if-then" logic to machines that recognize patterns and predict outcomes.
- Machine Learning Fundamentals: Master the core concepts of supervised and unsupervised learning—the building blocks that allow AI to improve its performance through experience.
- Natural Language & Perception: Dive into how machines interpret the human world, from understanding spoken language (NLP) to "seeing" through computer vision.
- The Ethics of Algorithms: Tackle the "black box" problem. Learn to identify bias, ensure data privacy, and maintain transparency in automated systems to protect both consumers and brand reputation.
- Strategic AI Integration: Explore how to identify "AI-ready" problems within a business, learning to distinguish between expensive trends and high-impact technological investments.
Career Opportunities
Expertise in the fundamentals of AI positions you as a translator between the technical world and the boardroom. As industries across the globe scramble to integrate smart systems, your ability to oversee AI projects with a strategic lens makes you an indispensable asset in the digital-first economy.
- AI Project Manager: Leading cross-functional teams of data scientists and engineers to deliver smart solutions on time and within budget.
- Chief Digital Officer (CDO): Shaping the long-term technological vision of an organization and overseeing the transition to AI-integrated operations.
- AI Ethics & Compliance Officer: Ensuring that an organization’s use of automation meets global legal standards and maintains public trust.
- Business Intelligence Lead: Leveraging predictive analytics to identify market shifts before they happen, giving your company a proactive edge.
- Strategy Consultant (Digital Transformation): Advising firms on how to modernize their legacy systems and adopt AI without disrupting their core culture.
- AI Product Owner: Managing the lifecycle of tech products, from initial concept and training data selection to user experience and market launch.
- Innovation Lab Director: Running corporate "think tanks" that prototype new AI applications to disrupt traditional business models.
- Technical Liaison: Acting as the vital link between non-technical stakeholders and engineering teams to ensure business goals are reflected in the code.
This module provides the bedrock upon which all successful leadership is built. It’s designed to transform you from a specialist into a generalist who understands how the different gears of a global organization mesh together. In the fast-paced world of AI and tech, having a brilliant algorithm is only half the battle; the other half is knowing how to build a sustainable, profitable, and human-centric organization around it.
You will learn to master the language of the boardroom. From the nuances of corporate finance to the psychology of organizational behavior, this subject ensures you can see the "big picture" of a business. You’ll develop the ability to manage resources—both financial and human—with precision, ensuring that innovation never comes at the expense of operational stability. This is where you learn to turn a visionary idea into a functioning, scalable reality.
- Organizational Architecture: Understand how to structure a company for maximum efficiency and agility, exploring the balance between traditional hierarchies and modern "flat" management styles.
- Strategic Financial Management: Demystify the balance sheet. Learn to interpret financial health, manage budgets, and make data-driven investment decisions that ensure long-term growth.
- Marketing in the Digital Age: Explore how to position products in a crowded market, focusing on brand equity, consumer behavior, and the shift from transactional selling to relationship building.
- Human Capital & Leadership: Master the art of managing people. Learn how to foster a culture of high performance, navigate conflict, and lead diverse teams through periods of intense change.
- Operations & Supply Chain: Dive into the logistics of value creation. Learn how to optimize processes to reduce waste and ensure that your product or service reaches the customer seamlessly.
Career Opportunities
A mastery of Business Administration Fundamentals creates a "versatile leader" profile. Whether you are entering a startup or a multinational corporation, your ability to oversee multiple departments and understand the financial implications of every decision makes you a prime candidate for executive roles.
- Operations Manager: Overseeing the day-to-day inner workings of a company to ensure maximum productivity and streamlined workflows.
- Business Development Director: Identifying new market opportunities and building the strategic partnerships necessary to expand a company’s footprint.
- General Manager (GM): Taking full "P&L" (Profit and Loss) responsibility for a business unit, coordinating between finance, marketing, and HR.
- Corporate Strategy Lead: Working directly with the C-suite to define the long-term goals of the organization and the roadmap to achieve them.
- Entrepreneur / Founder: Using your holistic understanding of business to launch and scale your own venture with a solid structural foundation.
- Management Consultant: Solving complex organizational problems for external clients by analyzing their financial and operational bottlenecks.
- Financial Controller: Monitoring and managing a company's financial reporting and compliance, ensuring every dollar is accounted for and working toward growth.
- Change Management Specialist: Guiding organizations through structural shifts, such as mergers, acquisitions, or large-scale digital pivots.
This module transforms numbers into a narrative. In an age where every click, purchase, and sensor pulse generates data, the real competitive advantage lies not in owning that information, but in interpreting it. We move beyond the "what" of raw data to discover the "why" and "how," teaching you to spot patterns that the human eye misses and turn them into strategic gold.
You will learn to bridge the gap between technical data science and executive action. This isn't just about crunching numbers in a vacuum; it’s about learning which questions to ask and how to visualize the answers so they can drive real-world impact. From predicting customer churn to optimizing global supply chains, you will become a leader who doesn't just "gut-check" decisions, but validates them with rigorous, evidence-based insights.
- Descriptive & Diagnostic Analytics: Master the art of looking backward to understand performance. Learn to analyze historical data to identify exactly what happened and the underlying reasons why.
- Predictive Modeling: Shift your perspective to the future. Explore how to use statistical tools and machine learning to forecast trends, anticipate market shifts, and mitigate risks before they materialize.
- Data Visualization & Storytelling: Learn to communicate complexity with clarity. Master the tools and techniques used to create compelling visual dashboards that make data accessible to stakeholders at all levels.
- Big Data Ecosystems: Understand the infrastructure behind the insights. Explore how modern businesses handle vast volumes of structured and unstructured data across cloud and on-premise systems.
- Prescriptive Strategy: Move from "what will happen" to "what should we do." Learn to use optimization algorithms to determine the best course of action in complex, multi-variable business scenarios.
Career Opportunities
A specialist in Data Analytics for Business is the "intelligence hub" of any modern organization. As companies move away from intuition-based leadership, your ability to translate complex datasets into clear, profitable strategies makes you a vital asset in any sector.
- Senior Business Analyst: Interpreting data to provide actionable recommendations that improve business processes and financial performance.
- Data Strategy Consultant: Advising organizations on how to build their data infrastructure and cultivate a data-driven corporate culture.
- Market Intelligence Manager: Analyzing competitor data and consumer trends to help the marketing department capture new demographics.
- Revenue Management Lead: Using predictive analytics to optimize pricing and inventory, common in the airline, hospitality, and retail sectors.
- Supply Chain Analyst: Identifying bottlenecks and inefficiencies in the production and distribution line to save costs and improve delivery times.
- Customer Insights Director: Deep-diving into user behavior data to improve product design, customer retention, and overall brand loyalty.
- Risk Assessment Manager: Utilizing statistical models to predict financial or operational risks and developing strategies to minimize their impact.
- Chief Data Officer (CDO) Path: Positioning yourself for executive leadership by overseeing the entire lifecycle of an organization’s most valuable asset: its data.
This module moves beyond traditional "waterfall" timelines to master the dynamic, iterative world of AI deployment. Unlike standard IT projects, AI integration is a journey of constant experimentation and refinement. You will learn how to lead projects where the requirements aren't always fixed and the "finish line" involves continuous learning loops. We bridge the gap between high-level business goals and the technical sprints of data scientists and engineers.
You will learn to manage the unique risks of the AI lifecycle—from "data debt" and model drift to the complexities of cross-functional team dynamics. This subject ensures you can maintain momentum when results are unpredictable and pivot strategies based on real-time performance metrics. In a landscape where nearly half of AI initiatives stall due to a lack of clear management, you will become the leader who ensures innovation actually reaches the production line and delivers measurable ROI.
- The AI Project Lifecycle: Master the specific stages of AI development, from initial problem scoping and "use case validation" to the complexities of model deployment and scaling.
- Agile for AI: Learn to adapt Scrum and Kanban frameworks to handle the experimental nature of machine learning, where "failure" in an early sprint is often a necessary step toward a breakthrough.
- Managing the "Human-in-the-Loop": Explore the art of leading cross-functional teams, acting as the vital translator between technical specialists (Data Scientists/ML Engineers) and business stakeholders.
- AI Risk & Quality Governance: Develop frameworks for monitoring model performance, identifying algorithmic bias, and ensuring data privacy compliance (GDPR/EU AI Act) throughout the project.
- Vendor & Tool Selection: Learn how to evaluate the "Build vs. Buy" dilemma—deciding when to develop custom in-house models and when to integrate third-party AI platforms.
Career Opportunities
Mastering AI Project Management positions you as a high-value "Integrator." As organizations shift from exploring AI to fully operationalizing it, the demand for leaders who can handle the friction of tech integration is skyrocketing across every sector from finance to healthcare.
- AI Project Manager: Taking full ownership of AI initiatives, ensuring they stay aligned with business objectives while managing budgets and technical roadmaps.
- Digital Transformation Lead: Steering entire departments through the cultural and operational shifts required to adopt intelligent automation.
- AI Product Owner: Bridging the gap between customer needs and technical capabilities, defining the features and "vision" for AI-powered products.
- MLOps Coordinator: Managing the "Operations" side of machine learning—ensuring that once a model is built, it is successfully integrated into the company’s existing software ecosystem.
- Technical Program Manager: Overseeing a portfolio of related AI projects to ensure they share resources effectively and move the company toward its strategic goals.
- AI Strategy Consultant: Helping external clients identify high-impact AI use cases and designing the project plans to bring them to life.
- Solution Architect (Business Focus): Designing the high-level blueprint for how AI tools will interact with an organization’s current data and people.
- Innovation Delivery Lead: Managing "Pilot" programs and Proof-of-Concepts (PoCs) to test new technologies before they are scaled across the enterprise.
This module moves beyond traditional management to explore the "multiplier effect" of leading in an intelligent enterprise. In an AI-driven world, leadership is no longer about having all the answers—it’s about asking the right questions and fostering a culture where humans and machines augment each other’s strengths. You will learn to navigate the shift from being a "commander" to being an "orchestrator," managing teams where algorithms handle the heavy lifting of data analysis while humans provide the empathy, intuition, and ethical judgment.
You will learn to manage the "human elements" of technological change. From mitigating the fear of automation to redesigning roles for a "human-AI" hybrid workforce, this subject ensures you can lead with psychological safety and strategic clarity. In an era where tech moves fast but people and cultures move slow, you will become the leader who can synchronize the two, ensuring that AI becomes a tool for empowerment rather than a source of displacement.
- The Augmented Leader: Explore how to use AI-driven insights to enhance your own decision-making, moving from "gut-feel" leadership to evidence-based strategy.
- Redesigning the Future of Work: Learn how to deconstruct traditional jobs into tasks, identifying which should be automated, which should be augmented, and which must remain uniquely human.
- Cultivating an AI-First Culture: Master the art of change management in a digital context—fostering curiosity, rewarding experimentation, and building "AI fluency" across all levels of the organization.
- Responsible & Inclusive Leadership: Tackle the challenges of "algorithmic transparency" and learn to build diverse teams that can identify and remediate bias in the systems they deploy.
- Strategic Orchestration: Learn to manage cross-functional "pods" where data scientists, designers, and business leads collaborate seamlessly to turn technology into intellectual property and competitive advantage.
Career Opportunities
Leadership in AI-Driven Organisations prepares you for the "C-Suite of the future." As every company becomes a tech company, the demand for leaders who can bridge the gap between technical potential and organizational culture is critical for long-term viability.
- Chief AI Officer (CAIO): Holding the highest level of responsibility for the organization’s AI vision, ethics, and strategic implementation.
- VP of Organizational Transformation: Leading large-scale shifts in corporate structure and culture to support digital and autonomous technologies.
- Human-Machine Collaboration Lead: Designing the workflows and protocols that govern how employees interact with intelligent agents and automated systems.
- Talent & Upskilling Strategist: Overseeing the professional development of the workforce to ensure skills remain relevant in an automated economy.
- Ethical Governance Director: Managing the frameworks that ensure the organization’s AI use aligns with social values, legal regulations, and brand trust.
- Digital Change Management Consultant: Advising external firms on how to navigate the "people side" of technology adoption to prevent burnout and resistance.
- Innovation Ecosystem Director: Building partnerships between the organization, AI startups, and academic institutions to stay at the cutting edge of industry trends.
- Strategic Business Architect: Reimagining the company’s business model to leverage "AI-native" advantages, such as extreme personalization or autonomous operations.
Eligibility Requirements
Academic Qualifications:
- Certificate of your higher secondary education.
- A valid certificate of an undergraduate degree from a recognized university.
English language requirements:
- Recognized English tests:
1.1 IELTS — Overall 6.0
1.2 TOEFL:
1.2.1 PBT (Paper-Based Test) — 550 points
1.2.2 CBT (Computer-Based Test) — 213 points
1.2.3 iBT (Internet-Based Test) — 79–93 points - Nationals from English-speaking countries can skip taking an English test. They should write a letter of motivation for themselves.
- A minimum of 50% of grades in English subjects at higher secondary education or the medium of studies should be English in the last school of education.
Intakes
January/April/July/October
Course Fee
International student fee: €13,999 | EU student fee: €12,599
Admissions are open for the 2026 intake
You can start applying for an Master in Business Administration in Artificial Intelligence now.
Program Advisor
Contact: +49 30 233618555
Email: admission@eiiet.com