Another Crazy Day in AI: How Top Companies Build Reliable Data Systems
- Wowza Team
- Jun 16
- 4 min read
Hello, AI Enthusiasts.
Hope your week’s off to a decent start. But while inboxes filled up, some in AI were tackling the harder stuff.
A veteran tech journalist says CIOs are finally realizing that to get good AI, you need better data—and that means rethinking how it’s stored, governed, and used across the org.
On the creative front, AI video tools are now quietly powering major film work. One studio exec put it bluntly: “It’s like Ozempic. Everyone’s using it. No one’s saying it.”
And Adobe’s latest tool helps brands understand how they show up in AI-generated content—because increasingly, customers start their journey in a chatbot.
Here's another crazy day in AI:
Why data architecture matters more than ever
Runway’s film festival shows where AI video is headed
Adobe’s new tool helps brands get seen by AI
Some AI tools to try out
TODAY'S FEATURED ITEM: Data Foundations That Actually Work
Image Credit: Wowza (created with Ideogram)
Is your organization's data foundation strong enough to support the transformative power of artificial intelligence, or are you building on quicksand?
Seasoned tech journalist Stan Gibson explores how leading organizations across industries are addressing the challenges of building AI systems that deliver meaningful results—not by chasing the latest AI model, but by focusing on the quality, structure, and governance of the data behind it. His piece offers firsthand perspectives from leaders in semiconductors, wine production, pharmaceuticals, and energy, all working to strengthen their data foundations for smarter, more reliable AI.
Lessons from the field:
Data maturity creates measurable business impact - Organizations with advanced data quality and governance practices see substantially higher success rates with AI projects, including documented improvements in customer retention and operational efficiency
Layered data architecture provides stability - Companies organize their information into progressively refined tiers, creating structured foundations that can support multiple AI applications without compromising quality or performance
Private implementations protect competitive advantage - Leading firms develop internal versions of AI tools and maintain control over their language models to safeguard proprietary information while accessing AI capabilities
Practical governance enables innovation - Successful data strategies balance oversight with accessibility, ensuring teams can leverage systems effectively without getting bogged down in bureaucratic processes
Cross-functional collaboration drives real adoption - Technical excellence requires business partnership, with ongoing dialogue needed to establish meaningful metrics and encourage actual usage across departments
Talent challenges affect everyone - Even well-resourced organizations face difficulties finding professionals who understand both technical data requirements and business implications of modern governance frameworks
Gibson's reporting reveals how these companies navigate the practical realities of implementing robust data strategies. At Gallo, their approach to using AI for data cleanup demonstrates how these technologies can become self-improving systems—automatically identifying when wine descriptions use "spicy" instead of the preferred "peppery," then making corrections based on context. This kind of application shows AI working as a data quality tool rather than just an analytical engine. Meanwhile, Servier Pharmaceuticals built their own ChatGPT implementation on Azure not just for security reasons, but to create a controlled environment where teams could experiment with AI while maintaining the strict regulatory compliance required in pharmaceutical development.
The experiences shared in this piece also underscore the less glamorous but equally important aspects of data strategy. AES's work creating consistency across their clean energy sites involves the unglamorous task of standardizing how operational data gets collected and defined—work that becomes essential when trying to predict market demand and optimize energy pricing. Skyworks Solutions processes terabytes of manufacturing data daily, requiring systems capable of handling both volume and variety while maintaining the quality standards necessary for reliable AI outputs. These examples illustrate how successful AI implementation often depends more on solving fundamental data management challenges than on deploying cutting-edge algorithms.
Read the full article here.
OTHER INTERESTING AI HIGHLIGHTS:
Runway’s Film Festival Shows Where AI Video Is Headed
/Angela Yang, Culture & Trends Reporter, on NBC News
AI video tools may still be controversial, but they’re becoming surprisingly common in film production—even if no one talks about it. Lionsgate’s Michael Burns compares them to Ozempic: discreet, but everywhere. At Runway’s AI Film Festival, execs and creatives gathered to explore generative tools already being used in major studio deals. With tools like Runway and OpenAI’s Sora making their way into everything from short films to marketing assets, the line between traditional and AI-enhanced filmmaking continues to blur—even as labor concerns and ethical questions remain front and center.
Read more here.
Adobe’s New Tool Helps Brands Get Seen by AI
/Adobe Newsroom
Adobe’s new LLM Optimizer is designed to help brands stand out in an AI-first world, especially as generative tools like AI-powered search and chatbots transform how consumers interact with content. Traffic from AI sources has surged—up to 3,500% in retail—indicating a shift in digital behavior. The tool offers insights into where and how a brand shows up in AI-generated answers and recommends content improvements to enhance visibility and engagement. Adobe positions it as a way for businesses to stay discoverable and competitive as customer journeys increasingly begin in a chatbot or AI assistant.
Read more here.
SOME AI TOOLS TO TRY OUT:
That’s a wrap on today’s Almost Daily craziness.
Catch us almost every day—almost! 😉
EXCITING NEWS:
The Another Crazy Day in AI newsletter is on LinkedIn!!!
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