The Hidden Pattern at CES 2025

TL;DR

CES 2025 revealed a crucial shift: AI is moving beyond marketing hype into practical implementation thanks to an ecosystem of standardized components. From tiny specialized AI chips to smart displays, the building blocks are finally here for engineers to create meaningful AI-powered products.

The AI Ecosystem Comes of Age

The Marketing Evolution

Walking the floor at CES, we saw the evolution of AI marketing:

• 2023: Everything was "smart"

• 2024: Everything became "AI-powered"

• 2025: Now it's "AI for all"…

This marketing evolution reveals something important: Companies are struggling to differentiate their AI implementations, leading to increasingly abstract and meaningless terminology.

The Technical Building Blocks

For the first time at CES, we're seeing a complete toolkit of AI components emerging, for example:

Specialized AI chips

The foundation of this technological shift lies in specialized AI chips, exemplified by companies like Aizip. These aren't just smaller versions of existing processors – they're purpose-built engines optimized for specific tasks like vision processing, audio analysis, and time-series data interpretation. The beauty of this approach is its efficiency: by focusing on specific tasks, these chips can deliver powerful AI capabilities while minimizing energy consumption and cost.

Display Continues their transparent Trend

The interface layer has evolved significantly as well. We're seeing transparent displays that finally work as intended, smart glasses that people might actually want to wear, and vision-enabled watches that deliver meaningful insights rather than just notifications. These aren't just incremental improvements – they represent a fundamental shift in how we can interact with AI-enabled devices.

The sensor ecosystem has reached a new level of sophistication. Advanced camera modules now work seamlessly with environmental sensors and biometric capabilities, creating a rich data environment that AI can actually use effectively. This integration of sensing capabilities means products can understand their environment and user context in ways that weren't previously possible.

• Smaller, specialized language models

• Built for specific use cases

• Significantly lower resource requirements

• Forces clear problem definition

• Delivers measurable results

Why This Matters: The LEGO Effect

Just as LEGO pieces allow infinite creativity through standardized connections, these AI building blocks are enabling a new wave of product innovation. Here's what we're seeing:

The Impact on Product Development

The emergence of these standardized AI building blocks is revolutionizing how companies approach product development. Teams can now prototype and iterate faster than ever before, mixing and matching capabilities to create unique solutions. Instead of starting from scratch, developers can focus on combining these proven components in innovative ways. This modular approach doesn't just save time – it creates more reliable outcomes by building on tested foundations.

Most importantly, this new ecosystem is fostering genuine innovation. When product teams don't have to reinvent basic AI capabilities, they can focus on solving real user problems and creating meaningful differentiation. The result is a new wave of products that deliver actual value rather than just technical demonstrations.

What is working

After analyzing dozens of products at CES, here's what actually works:

1) Focus Beats General Intelligence

• Specific use cases outperform general AI

• Clearer success metrics

• Easier to maintain and improve

• More reliable outcomes

2) Economic Efficiency Matters

• Smaller models = lower operating costs

• Reduced energy consumption

• Better scalability

• More predictable budgeting

3) Problem-First Approach Wins

• Start with specific problems

• Build focused solutions

• Measure concrete results

• Iterate based on data

What You Can Do Today

1. Audit Your AI Strategy

• List current AI implementations

• Identify specific use cases

• Evaluate whether general AI is really needed

2. Consider Smaller Models

• Map potential focused AI applications

• Calculate resource requirements

• Compare costs with current solutions

3. Start Small, Scale Smart

• Pick one specific problem

• Implement focused solution

• Measure results

• Expand based on success

Looking Ahead: 2026 and Beyond

CES 2025 marked a turning point: the AI toolkit is finally complete enough for meaningful product development. The building blocks are here:

• Specialized AI chips from companies like Aizip

• Smart displays and interfaces that actually work

• Mature sensor technologies

• Standardized integration approaches

We expect CES 2026 to showcase the first wave of products that truly leverage these components in meaningful ways. The question isn't whether AI will be useful, but rather how quickly product teams can master these new building blocks to create solutions that genuinely improve people's lives.

The era of AI marketing is ending.

The era of AI product innovation is just beginning.

PS: Thank you to Toby from OnDiscourse for the invite to their super engaging floor tours at CES, this was the second year I’ve done one and I love the format.