Marin Niehues

AI beyond the code: Master your organisational AI implementation.

What's the biggest threat to your AI project? It's not the code, but a manager who says, "This data is mine."

AI beyond the code: Master your organisational AI implementation.
#1about 6 minutes

The challenge of optimizing tire production planning

Manual production planning for expensive machinery leads to inefficiencies and lost revenue, creating a clear business need for an AI-driven solution.

#2about 3 minutes

Assembling the team and building the initial concept

A cross-functional team of data engineers, scientists, and AI engineers is formed and successfully develops the core AI model concept in the initial sprints.

#3about 7 minutes

Distinguishing true AI from legacy rule-based algorithms

The project is challenged by a legacy system mistaken for AI, highlighting the organizational need to understand the difference between basic algorithms and self-learning systems.

#4about 7 minutes

Data silos are the enemy of machine learning

Being denied access to real production data reveals that organizational data silos and a lack of data governance will prevent any machine learning model from succeeding.

#5about 5 minutes

How C-level micromanagement creates organizational overhead

Escalating issues to the C-level results in a series of unproductive workshops and a bloated, unfunded task force, demonstrating how micromanagement stifles progress.

#6about 3 minutes

Six key strategies for successful organizational AI adoption

A summary of crucial lessons learned includes fostering AI understanding, building shared commitment, implementing a data strategy, removing silos, and empowering expert teams.

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Matching moments

Introducing a case study of a failed AI project
00:58 MIN

Introducing a case study of a failed AI project

Big Business, Big Barriers? Stress-Testing AI Initiatives.

Organizational strategies for successful AI adoption
20:39 MIN

Organizational strategies for successful AI adoption

Leading efficiency, empathy, and the human experience with AI

Why data silos and lack of governance kill AI projects
11:11 MIN

Why data silos and lack of governance kill AI projects

Big Business, Big Barriers? Stress-Testing AI Initiatives.

Key lessons for enterprise AI tool implementation
24:12 MIN

Key lessons for enterprise AI tool implementation

AI Pair Programming with GitHub Copilot at SAP: Looking Back, Looking Forward!

Learning from common failures in AI projects
22:20 MIN

Learning from common failures in AI projects

Rethinking Customer Experience in the Age of AI

Seven best practices for successful AI implementation
25:50 MIN

Seven best practices for successful AI implementation

Big Business, Big Barriers? Stress-Testing AI Initiatives.

Adopting a holistic AI strategy across business functions
19:43 MIN

Adopting a holistic AI strategy across business functions

Fireside Chat with Werner Vogels, VP & CTO, Amazon.com & Daniel Gebler, CTO at Picnic

Integrating AI expertise into product and business teams
06:54 MIN

Integrating AI expertise into product and business teams

Rethinking Customer Experience in the Age of AI

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AI Developer

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Remote
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