University Certificate Course (Online)

Chief Customer & AI Manager

This certificate course combines Customer Centricity, Digital Customer Twins, Customer-in-the-Loop, and Generative AI into a practical management approach for modern customer orientation within the company.

Participants learn to gain customer insights faster, evaluate them better, and translate them into concrete actions, AI use cases, and measurable customer impact.

The course is aimed at executives, managers, and decision-makers who want to understand customers better, use AI effectively, and derive concrete improvements for marketing, sales, service, product development, innovation, and management from insights.

During the course, participants work on their own relevant Customer AI use case and develop a concrete implementation approach for their company from it.

Ticket price per participant:in
10% Discount for Pro members in the Federal Association for AI Transformation

2.900 €

Book offer

Provider of this course:

What participants take away from the course

Practical understanding of how modern customer centricity is implemented with AI in the enterprise
Clearer guidance on how to generate better customer insights from customer data, feedback, behavior, and market signals
A sound understanding of digital customer twins as the next evolutionary stage of classic personas
Methods to validate hypotheses, measures, and decisions with a customer-in-the-loop
Concrete approaches to derive effective actions, use cases, and business impact from insights
Structured tools for customer-centric processes, roles, responsibilities, and success measurement
A custom customer AI use case with clear value, ownership, and a transfer plan for your own company

As a participant in this course, you will receive a structured, practical approach to key questions of modern customer centricity in the AI era: from customer insights and digital customer twins to generative AI and customer-in-the-loop, as well as use cases, processes, governance, and measurable customer success.

You work on real-world issues from your company, reflect on existing customer assumptions, and develop concrete approaches to improve customer understanding, decision-making quality, and implementation speed.

Spring semester 2027

03.02.2027, 17.00 – 18.30 Uhr – Kick-off
10.02.2027, 17.00 – 18.30 Uhr – Modul 1
17.02.2027, 17.00 – 18.30 Uhr – Modul 2
24.02.2027, 17.00 – 18.30 Uhr – Modul 3
03.03.2027, 17.00 – 18.30 Uhr – Modul 4
10.03.2027, 17.00 – 18.30 Uhr – Modul 5
17.03.2027, 17.00 – 18.30 Uhr – Modul 6
24.03.2027, 17.00 – 18.30 Uhr – Modul 7
31.03.2027, 17.00 – 18.30 Uhr – Modul 8
07.04.2027, 17.00 – 18.30 Uhr – Modul 9
14.04.2027, 17.00 – 18.30 Uhr – Modul 10
21.04.2027, 09.00 – 17.00 Uhr – Workshop
28.04.2027, 17.00 – 18.30 Uhr – Abschlusspräsentation

Create the foundation for better customer decisions

Customers are changing faster than traditional market research, static personas, and isolated data analyses can capture. Today, companies need a new understanding of what truly motivates customers, what needs will emerge tomorrow, and how to turn these insights into better products, services, communication, and business decisions.

Our goal is to provide you with a sound understanding of how to practically apply customer centricity, AI-driven customer insights, digital customer twins, and customer-in-the-loop within your company.

You will learn how to recognize, evaluate, prioritize, and translate relevant customer signals into concrete actions. The focus is not on technology for technology's sake, but on a central management question:

How do we make better decisions by truly understanding customers, placing them at the center of our actions with new AI options, and consistently involving them in hypotheses, measures, and outcomes?

The course is aimed at executives, managers, and decision-makers from marketing, sales, customer experience, service, product management, innovation, business development, strategy, transformation, data & AI, CRM, and executive management.

Target group: Executives, managers, and decision-makers with responsibility for customers, markets, products, innovation, or transformation
Duration: approx. 2 months (40 learning units of 45 minutes each, incl. 10 learning units of self-study)
Frequency: Weekly online meetings of 90 minutes each
Number of participants: 8-25 people
Previous knowledge: no specific prior AI knowledge required
Location: Network and learning community platform
Technology: PC/MAC with browser and smartphone
Platform access: Immediately after acceptance of the application

What makes this course special!

Modern customer centricity rarely fails because companies talk too little about customers. It fails because customer insights emerge too slowly, provide too little guidance for action, or are not consistently translated into decisions, processes, and responsibilities.

This is precisely where this course comes in: it combines customer centricity with AI, digital customer twins, and customer-in-the-loop. Participants learn to better understand customers, test assumptions more reliably, and derive concrete measures with measurable benefits from them.

In addition to understanding core methods, participants gain a realistic picture of how customer AI initiatives are implemented in companies: with suitable data, clear roles, robust use cases, governance, data protection awareness, and a consistent focus on customer impact.

At the same time, the course offers a practical approach to generative AI, digital customer twins, AI-supported analytics, and the development of concrete customer AI use cases. This creates a program that combines customer understanding, technology, implementation, and entrepreneurial added value.

From Customer Understanding to Customer Success: The course does not stop at analysis, personas, or tools. It shows how customer insights are turned into concrete decisions, experiments, measures, and results.
Digital Customer Twins as the next evolutionary stage of personas: Participants learn how static persona profiles can be developed into dynamic, data- and hypothesis-based Digital Customer Twins.
Customer-in-the-Loop as a management principle: Hypotheses, measures, and results are consistently linked with customer signals and validated.
AI as an accelerator for customer insights: Generative AI, data analysis, customer feedback, interviews, CRM data, support data, research, and market information are combined to create a faster insight process.
Own use case with clear ownership: Each participant works on their own relevant use case and develops a concrete implementation approach from it.
Measurable customer impact: The course helps make impact visible and communicate customer success to management, business units, and stakeholders.
High reliance on transfer payments: The goal is not only the acquisition of knowledge, but also its reflective application in the respective corporate context.

The program of the university certificate course

Customer Centricity, AI & Customer Impact

Module 1: Customer Centricity in the Age of AI

Why traditional customer centricity is often not enough
New customer expectations, new touchpoints, and new decision-making logics
From Customer Experience to Customer Impact
The Role of AI in Marketing, Sales, Service, Product and Innovation
What managers need to know about Customer AI today

Module 2: Customer in the Loop

Meaning and principle of Customer-in-the-Loop
How hypotheses, decisions, and actions are customer-validated
Difference between inside-out and outside-in thinking
How customer signals are integrated into management decisions
Customer impact as a key performance indicator

Personas of tomorrow & Digital Customer Twins

Module 3: From Personas to Digital Customer Twins

Limitations of traditional personas
Building dynamic customer profiles
Customer needs, jobs-to-be-done, barriers to decision-making, and behavioral patterns
How Digital Customer Twins are used as thinking, testing and simulation models
Which data, signals, and hypotheses are relevant for this

Module 4: Digital Customer Twin Design Lab

Development of a proprietary digital customer twin concept
Definition of relevant customer segments and usage contexts
Development of prompt and analysis frameworks
Simulation of customer reactions, objections, and needs
Validation with real customer signals

AI-powered customer insights

Module 5: Faster and better customer insights with AI

what customer data is already available in the company
AI-assisted analysis of interviews, feedback, reviews, CRM, and service data
Research with Generative AI
Identifying patterns, pain points, opportunities, and segments
Quality assurance, bias, data protection, and limitations of AI insights

Module 6: From Insight to Decision

Evaluation and prioritization of customer insights
Which insights are truly actionable
Derivation of hypotheses, measures, and experiments
Customer Journey, Value Proposition, and Use Case Prioritization
Connecting customer insights with business goals

Actions, Use Cases, and Measurable Customer Success

Module 7: Developing Customer AI Use Cases

Use cases for marketing, sales, service, product development, and innovation
Evaluation based on customer value, feasibility, and business impact
Building a Customer AI Use Case Canvas
Definition of owners, processes, and success criteria
From idea to actionable pilot project

Module 8: Deriving successful actions from insights

Translation of insights into concrete actions
Experimental design and test logic
Customer-in-the-Loop Feedback Loops
Measurement of impact and customer success
Scaling successful measures within the company

Roles, processes, and transfer into the company

Module 9: Becoming an Owner of Customer-Centric AI Processes

What role a Customer AI & Digital Twin Manager assumes in the company
Establishment of appropriate processes and governance
Collaboration with business units, Data, IT, Legal, and Management
Convincing stakeholders and making customer impact visible
Communication of personal and corporate added value

Module 10: Practical Workshop and Graduation

Presentation of your own customer AI use case
Feedback from instructors and peers
Assessment of customer value, feasibility, and business impact
Transfer plan for the next 90 days
Graduation with a certificate

Result for participants

Upon completion of the course, participants will have a clear understanding of how to practically apply customer centricity using AI and digital customer twins in the company.

You can gain customer insights faster, evaluate them better, and translate them into concrete actions. You are empowered to think and act in a customer-centric way, build suitable use cases with clear added value, and assume responsibility within the company as the owner of these initiatives.

Upon successful completion, participants receive the certificate:

Certified Customer AI & Digital Twin Manager

This title documents the ability to apply modern customer centricity, AI-powered customer insights, digital customer twins, and customer-in-the-loop methods within the company.

Participants can use this to demonstrate to supervisors, teams, and stakeholders that they are capable of translating customer insights into concrete actions and measurable business value.

Corporate result

Companies benefit from managers and employees who better understand customer needs, do not view AI in isolation, and can derive concrete results from insights.

The training course helps companies to,

making customer-centric decisions faster,
to use customer insights more systematically,
identify relevant AI use cases,
integrating customer feedback more strongly into processes,
Aligning teams to customer impact,
To more effectively connect innovation, marketing, sales, service, and product development.