Looking Back: What Did We Get Wrong?

What we got right
We correctly identified edge AI, specialise sensing and embedded vision as the industry's strongest structural trends. These themes continued strengthening across research, commercialisation and industrial integration.

What surprised us
We underestimated how rapidly industrial vision became intertwined with robotics and autonomous systems. By the end of 2022, vision was increasingly being deployed as part of broader automation platforms rather than traditional inspection stations.

Where we were too optimistic
We expected AI inspection to become more standardized across industries. Instead, deployment remained highly application-specific, with significant variation in data requirements, workflows and engineering effort.

Five Macro Themes for 2023

1. Edge AI Becomes the Operating Model for Intelligent Vision

Confidence: High

By the end of 2022, edge AI is no longer an emerging technology—it has become the default architecture for many industrial vision deployments.

Progress across embedded AI modules, smart cameras, FPGA platforms, software-defined cameras and industrial deployment workflows reflects a growing consensus that image processing, inference and decision-making should occur close to where data is generated.

Why it matters

The industry's most significant shift is architectural. Cameras are evolving from image acquisition devices into intelligent systems capable of analysing and acting locally, strengthening confidence that edge AI will form the long-term foundation of industrial vision.

2. AI Inspection Advances, but Scaling Remains Uneven

Confidence: High

AI inspection continues expanding across defect detection, quality inspection and factory automation. However, evidence still points to selective adoption rather than widespread commodity deployment.

Performance continues to depend heavily on data quality, application complexity and integration expertise.

Why it matters

The question is no longer whether AI can inspect. It is whether AI inspection can become repeatable, reliable and scalable across diverse industrial environments.

3. Sensor Architecture Remains a Strategic Battleground

Confidence: High

Sensor innovation continues to accelerate across SWIR, SPAD, Time-of-Flight, LiDAR, HDR, global shutter CMOS, event-based sensing, hyperspectral imaging and low-light architectures.

Rather than competing primarily on image quality, sensors are increasingly optimized for specific operating environments and industrial applications.

Why it matters

Industrial vision is not moving from sensors to AI. It is moving toward better combinations of sensing and intelligence. As applications become more demanding, specialized sensing increasingly determines overall system performance.

4. 3D Vision Expands, but No Dominant Architecture Emerges

Confidence: Medium–High

Demand for depth perception continues growing across robotics, autonomous systems, logistics and industrial automation.

At the same time, stereo vision, Time-of-Flight, structured light, LiDAR and SPAD continue evolving in parallel, with no clear winner emerging.

Why it matters

The market is converging on the need for depth, but not on a single technology. Success will continue to depend on matching sensing architecture to application requirements rather than expecting one universal solution.

5. Vision Becomes the Perception Layer for Intelligent Machines

Confidence: High

Industrial vision is increasingly embedded inside robots, autonomous vehicles, drones, factory automation systems and intelligent edge devices.

Rather than existing as an independent subsystem, vision is becoming the perception layer that enables autonomous decision-making across a growing range of industrial platforms.

Why it matters

This represents a structural shift in industry value creation. Competitive advantage is increasingly moving toward organizations capable of integrating sensing, computing, AI and automation into complete perception systems.

Outlook at a Glance

• Strongest Signal Industrial vision evolves into a distributed perception ecosystem

• Biggest Technology Shift Edge AI becomes the operating model for intelligent vision

• Fastest-Maturing Theme Embedded AI deployment

• Emerging Opportunity Robotics and automation integration

• Highest Uncertainty Scaling intelligent vision across diverse industrial environments

Technologies Worth Watching in 2023

• Edge AI Becoming the default deployment architecture

• AI Inspection Continued progress, uneven scaling

• Embedded Vision Strong expansion across intelligent devices

• Smart Cameras Increasing onboard intelligence

• SWIR Imaging Growing application-specific relevance

• Time-of-Flight & 3D Vision Broader adoption, fragmented market

• LiDAR Expanding beyond automotive applications

• SPAD Imaging Strong research, selective commercialization

• Event-Based Vision Early but increasingly worth watching

• HDR & Global Shutter CMOS Continued industrial relevance

• Hyperspectral & Multispectral Imaging Expanding specialist applications

• Robotics Vision Strong integration momentum

• Sensor Fusion Increasing importance for autonomous systems

Technologies Requiring More Evidence

Several technologies continue to strengthen as long-term signals but have yet to demonstrate broad industrial adoption.

These include:

• Event-based vision

• Fully autonomous inspection

• General-purpose industrial AI platforms

• Mainstream SPAD-based industrial vision

• Commodity 3D vision

Each shows encouraging progress, but current evidence continues to favour specialized, application-driven deployment over universal adoption.

Areas of Highest Uncertainty

The industry's biggest uncertainties are increasingly practical rather than technical.

Key questions include:

• Can AI inspection become repeatable across diverse production environments?

• Will smart cameras simplify deployment or introduce new system complexity?

• Can edge AI platforms deliver the reliability expected throughout long industrial lifecycles?

• Which depth-sensing technologies will prove most durable across industrial applications?

• Will event-based vision move beyond specialist markets?

• Can sensor fusion become a mainstream industrial vision architecture rather than remaining concentrated in robotics?

Outlook Summary

Industrial vision enters 2023 as an increasingly distributed perception ecosystem rather than a collection of independent technologies.

The strongest evidence available at the end of 2022 suggests the industry's future will be shaped not by a single breakthrough, but by the convergence of specialized sensing, edge AI, embedded computing, 3D perception and automation integration.

Research remains active. Commercialization continues to broaden. Integration is strengthening. Adoption, however, remains selective and application specific.

The defining question for 2023 is no longer whether industrial vision can become intelligent. It is whether intelligent perception can become sufficiently reliable, scalable and trusted to operate as a foundational layer across the next generation of industrial automation systems.

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