Marin Niehues
Big Business, Big Barriers? Stress-Testing AI Initiatives.
#1about 4 minutes
Introducing a case study of a failed AI project
A real-world example from a tire manufacturer is used to illustrate the organizational challenges of implementing an embedded AI for production planning.
#2about 2 minutes
Defining the AI project goals and initial team
The project aimed to use an embedded AI to optimize machine utilization and supply chains, starting with a motivated team of data engineers and scientists.
#3about 4 minutes
Distinguishing true AI from legacy rule-based systems
The project faced its first obstacle when a legacy software owner claimed their if-else system was already an AI, revealing a fundamental misunderstanding of the technology.
#4about 6 minutes
Why data silos and lack of governance kill AI projects
The project stalled when a plant manager refused to share essential data, highlighting that a strong foundation of data literacy and governance must precede AI development.
#5about 4 minutes
How executive micromanagement derails AI initiatives
An escalation to C-level resulted in an unproductive workshop with only managers, which failed to resolve data ownership and instead led to micromanagement.
#6about 5 minutes
The pitfalls of creating a top-heavy AI task force
The project was replaced by a dysfunctional AI task force with a large steering committee but no dedicated operational staff, creating massive overhead and no impact.
#7about 2 minutes
Seven best practices for successful AI implementation
Key takeaways from the failed project include ensuring stakeholder understanding, securing commitment, building a data strategy, removing silos, and focusing on delivery over management.
Related jobs
Jobs that call for the skills explored in this talk.
Wilken GmbH
Ulm, Germany
Senior
Kubernetes
AI Frameworks
+3
msg
Ismaning, Germany
Intermediate
Senior
Data analysis
Cloud (AWS/Google/Azure)
Matching moments
04:57 MIN
Increasing the value of talk recordings post-event
Cat Herding with Lions and Tigers - Christian Heilmann
03:28 MIN
Why corporate AI adoption lags behind the hype
What 2025 Taught Us: A Year-End Special with Hung Lee
01:32 MIN
Organizing a developer conference for 15,000 attendees
Cat Herding with Lions and Tigers - Christian Heilmann
03:48 MIN
Automating formal processes risks losing informal human value
What 2025 Taught Us: A Year-End Special with Hung Lee
04:27 MIN
Moving beyond headcount to solve business problems
What 2025 Taught Us: A Year-End Special with Hung Lee
03:15 MIN
The future of recruiting beyond talent acquisition
What 2025 Taught Us: A Year-End Special with Hung Lee
04:22 MIN
Why HR struggles with technology implementation and adoption
What 2025 Taught Us: A Year-End Special with Hung Lee
05:18 MIN
Incentivizing automation with a 'keep what you kill' policy
What 2025 Taught Us: A Year-End Special with Hung Lee
Featured Partners
Related Videos
30:49AI beyond the code: Master your organisational AI implementation.
Marin Niehues
29:00AI in Action: Real Use Cases with Real Impact - Hanna Hennig, Michael Ameling, Tobias Regenfuss
Hanna Hennig, Michael Ameling & Tobias Regenfuss and Mike Butcher
24:07Beyond the Hype: Real-World AI Strategies Panel
Mike Butcher, Jürgen Müller, Katrin Lehmann & Tobias Regenfuss
31:15The AI Skills Gap: What Tech Leaders Must Get Right
Thomas Wollmann, Gerrit Einhoff, Kara Sprague & Alexandra Wudel
28:19AI in Leadership: How Technology is Reshaping Executive Roles
Jeff Hausmann, Jasmin Kaiser, Bernd Datler & Sonja Alvarez
26:25Bringing AI Everywhere
Stephan Gillich
26:43AI PowerPlay: Building High-Impact Teams & Transformative Solutions
Kadir Mourat
28:09The AI-Ready Stack: Rethinking the Engineering Org of the Future
Jan Oberhauser, Mirko Novakovic, Alex Laubscher & Keno Dreßel
Related Articles
View all articles
From learning to earning
Jobs that call for the skills explored in this talk.
Forschungszentrum Jülich GmbH
Jülich, Germany
Intermediate
Senior
Linux
Docker
AI Frameworks
Machine Learning
team.blue Global
Barcelona, Spain
Senior
JIRA
Confluence
Agile Methodologies
Master Thesis AI Integration for Large Data Analysis, Quality Management, and Predictive Maintenance
Robert Bosch GmbH
C++
Python