WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
World Congress 2026 Europe • Jul 10, 2026 • Session details

Data: The Deciding Factor in AI Success

Damandeep Kochhar , Jörg Tewes , Siddhika Nevrekar , Ed Huang , Laura Moritz

Meta's $14.3 billion investment in Scale AI proves one thing. Real-world AI initiatives don't fail from model limitations. They fail from incomplete, poorly governed enterprise data.

Pause
Mute Enter Fullscreen
#1 about 3 min

Meta's investment in Scale AI and training data

Since capital alone cannot create essential foundations for frontier models, Meta strategically invested billions directly into specialized training data acquisition.

#2 about 3 min

Introduction of panelists and their roles in AI engineering

Understanding the specific structural challenges of data processing requires insights from established specialists in geospatial computing and distributed databases.

#3 about 3 min

Identifying data trust and clean data as AI bottlenecks

Because incomplete or delayed enterprise data drastically undercuts functionality, securing clean institutional knowledge takes precedence over expanding model sizes.

#4 about 2 min

Synthesizing real-world sensor data and managing model drift

Synthesizing massive volumes of disparate sensor readings demands accurate continuous labeling pipelines to successfully reverse inevitable model drift.

#5 about 3 min

Processing edge computing models for rapid feedback loops

Operating efficiently within restricted hardware memory constraints forces developers to carefully curate edge scenarios while relying on robust cloud fallbacks.

#6 about 1 min

Balancing centralized data architectures with distributed edge playgrounds

Processing highly fragmented institutional sources requires building centralized data hubs that function alongside isolated operational playgrounds for autonomous actions.

#7 about 3 min

Governing autonomous agent actions and protecting enterprise systems

Unpredictable dynamic queries generated by autonomous tooling force engineering teams to implement advanced access governance interfaces stopping critical systemic failures.

#8 about 2 min

Balancing security compliance regulations with rapid AI experimentation

Preventing the unauthorized leakage of highly sensitive corporate records means establishing strict function-specific boundaries that safely accommodate unrestricted technological experimentation.

#9 about 3 min

Transitioning models from rapid prototyping to reliable production environments

Stabilizing unpredictable agent-driven workflows requires distilling unverified scripts into reproducible systemic interactions within heavily isolated production sandboxes.

#10 about 3 min

Ensuring model transparency and safety guardrails in autonomous vehicles

Overcoming heavy industry regulations around autonomous navigation demands exposing transparent operational decision observability alongside deeply integrated routing protections.

#11 about 3 min

Defining organizational ownership for centralized enterprise metadata frameworks

Recognizing that automated systems steadily replace decentralized reporting structures highlights why organizations must systematically aggregate an interconnected strategic metadata layer.

#12 about 4 min

Establishing foundational data trust and flexible enterprise architecture

Deploying robust machine learning successfully hinges on treating fundamental institutional records as aggressively prioritized products within a flexible technical architecture.

Matching moments

2:39 min

Identifying the scaling crisis in enterprise AI

Olga Woschitz Olga Woschitz +1 · Europe 2026 Virtual

1:35 min

Root causes of underlying AI initiative failures

Deivids Vilkinsons Deivids Vilkinsons +3 · World Congress 2026 Europe

1:50 min

The future of data engineering and AI mesh

Sandhya Menon Sandhya Menon · World Congress 2026 Europe

3:52 min

Establishing a structured framework for enterprise AI

Julian Joseph · LIVE

1:43 min

Core foundations for successful artificial intelligence transformation

Alexander Birke Alexander Birke +1 · World Congress 2024

1:41 min

Overcoming artificial intelligence silos in the enterprise

Kapil Gupta Kapil Gupta · World Congress 2025

More from World Congress 2026 Europe

Building the Nervous System of AI - Michael Kagan (NVIDIA) thumbnail
29:17
3 months ago

Building the Nervous System of AI - Michael Kagan (NVIDIA)

Michael Kagan, Sead Ahmetović

Five Things in Tech that Matter Now - WeAreDevelopers World Congress 2026 Closing Keynote thumbnail
19:41
3 months ago

Five Things in Tech that Matter Now - WeAreDevelopers World Congress 2026 Closing Keynote

Christian Heilmann

The Sound of Your Secrets: Teaching Your Model to Spy, So You Can Learn to Defend thumbnail
32:06
3 months ago

The Sound of Your Secrets: Teaching Your Model to Spy, So You Can Learn to Defend

David vonThenen

Super scaling for the Super Bowl: How to survive 30 million users hitting your backend in 30 minutes thumbnail
35:13
3 months ago

Super scaling for the Super Bowl: How to survive 30 million users hitting your backend in 30 minutes

Irina Branovic

Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬 thumbnail
24:23
3 months ago

Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬

Jeremy Murray

Angstfreude - AI and Corporate Culture - The Thrill and the Threat thumbnail
30:26
3 months ago

Angstfreude - AI and Corporate Culture - The Thrill and the Threat

Axel Ebert, Karin Krobath

Upcoming sessions on this topic

Open session

World Congress 2026 North America

September 24, 2026 · 15:30–16:00

Outdoor Stage

From Boardroom to Build Pipeline: What AI Governance Actually Looks Like in Practice

Anita Ganti

Board Director & Technology Executive

Anita Ganti
Open session

World Congress 2026 North America

September 25, 2026 · 09:00–09:30

Mainstage

Building AI that fits your business

Benny Chen

Co-Founder of Fireworks

Benny Chen
Open session

World Congress 2026 North America

September 25, 2026 · 16:10–16:40

Stage 3

The Five Percent Club: The Culture and Technological Shift Behind Successful AI Deployments

Tara Hernandez

Tara Hernandez, VP of Developer Productivity at MongoDB

Tara Hernandez
Open session

World Congress 2026 North America

September 24, 2026 · 10:20–10:50

Stage 4

AI Decision Observability: Enabling Transparency and Trust in Intelligent Systems

Amjad Shaikh, Soumil Mandal

Amjad Shaikh
Soumil Mandal
Open session

World Congress 2026 North America

September 24, 2026 · 12:15–12:45

Stage 4

It's Not About the Models

Bob Wambach

VP, Market and Customer Insights at Dynatrace

Bob Wambach
Open session

World Congress 2026 North America

September 24, 2026 · 16:50–17:20

Mainstage

Building AI Products vs. Building With AI

Aparna Dhinakaran, Rukmini Reddy, Tamar Bercovici

Aparna Dhinakaran
Rukmini Reddy
Tamar Bercovici

Related videos

Big Business, Big Barriers? Stress-Testing AI Initiatives. thumbnail
27:53
World Congress 2024 • about 2 years ago

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

Marin Niehues

Running AI at Scale: The Secret Ingredients thumbnail
30:04
World Congress 2026 Europe • 3 months ago

Running AI at Scale: The Secret Ingredients

Boris Hecker, Max Tschochohei, Peter Kürpick, Tomislav Tipurić

The Missing Layer Between Enterprise Data and AI Agents thumbnail
30:17
World Congress 2026 Europe • 3 months ago

The Missing Layer Between Enterprise Data and AI Agents

Jannis Eickenroth, Sebastian Klenke

The Limits of LLMs in Real-World Applications thumbnail
31:07
World Congress 2026 Europe • 3 months ago

The Limits of LLMs in Real-World Applications

Deivids Vilkinsons, Guillaume Esnou, Laura Moritz, Mariam Hakobyan

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact thumbnail
23:33
World Congress 2025 • about 1 year ago

Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact

Oliver Will

AI in High-Stakes Industries: Lessons Learned thumbnail
31:27
World Congress 2026 Europe • 3 months ago

AI in High-Stakes Industries: Lessons Learned

Alexandre Guenoun, Jaipal Singh, Nicolò Robba, Tomislav Tipurić

Related articles

From learning to earning

Jobs that call for the skills explored in this talk.