Snowflake Summit 2026 | Unlocking Hidden Business Value: How Industry Leaders Are Turning Sprawling Data into Immediate Action

For many C-suite leaders and business executives, the journey to achieving data-driven transformation often comes with a frustrating reality: massive investments in technology, yet agonizingly slow business results.

Your company collects petabytes of information: customer feedback, sales numbers, supply chain logs, engineering blueprints and vendor contracts. But why does it still take weeks to get a straight answer to a critical business question? Why do strategic initiatives get delayed while waiting for technical teams to manually extract, clean and move the information?

The root cause isn't a lack of data — it's how data is managed and accessed.

For decades, companies built separate, isolated silos for every department. Marketing had its system, but so did manufacturing and finance. To bring it all together, technical teams spent millions building complex bridges to copy data from one place to another, turning to solutions such as ETL pipelines.

Far too often, it’s created a mess of duplicated storage costs, fragile systems and business teams trapped in months-long holding patterns waiting for IT and data engineering to build, update or run reports, which are out of date by the time they’re finally done.

During Snowflake Summit 2026, global industry leaders Panasonic Connect, Siemens Energy and Daimler Truck North America (DTNA) shared how they’re navigating this challenge. Their real-world use cases demonstrate that a fundamental shift is happening across the enterprise: executive teams are moving away from legacy copy-and-paste data strategies and embracing a simpler, faster model built on zero-copy data architecture paired and AI embedded directly into daily workflows.

Here’s what business leaders need to know about this transformation and how it directly impacts the bottom line.

The power of zero-copy

When executives look at cloud infrastructure bills, a huge portion goes toward moving and copying data between systems. Every time data is moved, you pay twice: once for the transfer/storage, and again in lost time while teams wait for the move to finish. Worse, having multiple copies creates major governance and security risks.

Modern data strategy revolves around zero-copy architecture. Instead of physically moving data into new locations, platforms now connect directly to the source data in its original home using universal, open table formats (like Apache Iceberg). The data stays put in a single location, but every authorized team gets instant, secure, real-time access.

Real-world business impact:

• Drastic cost reductions: Siemens Energy designed a unified data framework around zero-copy principles to eliminate duplicated systems, pointing toward a multimillion-euro reduction in unnecessary operational costs.
  

• Real-time agility: Daimler Truck North America unlocked mission-critical data trapped in legacy mainframe systems. Instead of waiting hours for batch reports, plant leaders now get operational data in under five minutes — processing over 130 million daily updates without breaking a sweat.
  

• Built-in compliance: Keeping data in one place makes complying with privacy laws and regulations (like the EU Data Act) dramatically simpler and less risky.
  

Turning documents into business results

Up to 80% of an enterprise’s most valuable information isn't neatly organized in spreadsheets. It’s buried in unstructured files: open-ended customer survey comments, PDF specifications, contract documents, emails and messages and so much more.

Historically, reading and analyzing these documents required hundreds of hours of manual labor. Today, embedding AI directly where your data already lives and running it within your company’s existing security boundary transforms tedious document reading into instant business decisions without ever letting sensitive data leave your control.

Real impact: How Panasonic Connect solved two major bottlenecks

Panasonic Connect used native AI to streamline operations across two completely different business units:

1. Transforming customer voice into sales action:
   

   • The problem: Analyzing ~200 free-text customer survey responses took six-and-a-half hours of manual work in Excel. Producing company-wide reports took up to three months, meaning front-line sales managers got insights far too late to save at-risk accounts.

   • The AI solution: They built an automated app that immediately categorizes feedback sentiment (positive, negative, neutral) and highlights main themes.

   • The business result: Analysis time dropped by 90% (from ~200 hours to 20 hours annually). Sales reps now receive instant, tailored action plans for specific accounts right after surveys are filled out.
     

2. Dramatically accelerating engineering checks:
   

   • The problem: Engineers had to manually compare 50-page technical specifications against detailed product drawings side-by-side to prevent manufacturing defects — a tedious process prone to human error.

   • The AI solution: Engineers drag and drop PDFs into a simple app, where AI reads the documents, compares specs and automatically highlights inconsistencies.

   • The business result: Document cross-checking times dropped from 340 minutes down to just 10 minutes (a 97% time savings). Engineers freed up time to focus on complex decisions rather than manual reading.
     

Beyond dashboards: Moving to talk to your data

For decades, executive management relied on Business Intelligence (BI) dashboards. But static dashboards have big flaws: they only tell you what happened yesterday, can’t answer why it happened and changing them requires opening a ticket with IT.

The industry is rapidly shifting from passive dashboards to conversational AI, or talking with your data, so to speak.

The industry is rapidly pivoting away from these dashboard bottlenecks toward a conversational future. In the traditional model, a business user with a new question had to submit an IT request, wait for a technical team to pull the data and eventually receive a static visual report. In the new conversational model, that friction disappears. Business teams simply ask questions in plain English, and AI assistants query the enterprise data directly to deliver immediate answers rooted in your company’s operations, connecting the dots across your systems.

How conversational AI works on the assembly floor

At Daimler Truck North America, plant managers on the assembly line no longer wait for shift-end reports. Instead, they use a conversational AI assistant on the floor to ask simple questions in plain English:

"Which trucks are currently delayed offline, what is causing the bottleneck on the line and are we facing part shortages?"

The AI instantly searches live production metrics, scans unstructured assembly documentation and gives the plant manager a clear, accurate answer in seconds.

Technology means nothing without adoption

A modern data architecture is useless if business teams refuse to use it. The most successful corporate transformations rely on three key cultural principles:

• IT as a business partner, not an order-taker: Historically, business teams have often tossed requirements over the wall to IT. But in successful organizations where those teams instead work in lockstep with one another, IT sets up secure, easy-to-use platforms, giving business leaders the tools to explore data and build solutions themselves.
  

• Start small and prove value first: Avoid multi-year, monolithic "transformation programs" that take forever to show ROI. Panasonic Connect scaled its company-wide data culture by starting with a single project in marketing, proving quick business value and spreading that working model to other divisions.
  

• Focus on decision quality, not just speed: Speed is great, but avoiding costly mistakes is better. Giving employees instant data access reduces burnout, cuts out manual, rote work and gives teams the clarity needed to make smarter, higher-value choices.
  

Questions to ask today

If you want to evaluate where your business stands on this journey, ask these three questions:

1. "How many copies of our core operational data exist, and how much are we paying to move data between systems?" (Goal: Push toward a zero-copy architecture).
   

2. "How are we leveraging AI on our unstructured data, such as PDFs, customer reviews or internal reports?" (Goal: Bring AI directly to where your data lives securely).
   

3. "Can our front-line managers get immediate answers in plain English, or are they still waiting on IT for static dashboards?" (Goal: Empower teams with conversational AI tools).

Want to learn more? Watch Panasonic, Siemens, and Daimler’s Snowflake Summit 2026 presentations to hear directly from them about their data and AI transformations.