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Smart Manufacturing: What Are Organizations Really Investing In?

Smart Manufacturing: What Are Organizations Really Investing In? Everyone is talking about Artificial Intelligence (AI), but when it comes to actual investments in smart manufacturing, what technologies are manufacturers truly prioritizing?  According to Deloitte’s latest survey of 600 manufacturing executives, the answer might surprise you. AI vs. Reality: The Investment Gap Jeff Winter, a known thought leader in Industry 4.0 and digital transformation, recently shared an eye-opening chart that categorizes how manufacturers are approaching different technologies. While the buzz around AI—especially Generative AI—is louder than ever, the real-world funding decisions paint a different picture. The Four Investment Quadrants Deloitte's chart organizes technologies into four strategic quadrants: 1. Strategic Focus (High Use, High Priority) These technologies are being used actively and are also high on the strategic agenda: Data Analytics Active Sensors Cloud Computing Fact...

Smart Manufacturing: What Are Organizations Really Investing In?

Smart Manufacturing: What Are Organizations Really Investing In?
Everyone is talking about Artificial Intelligence (AI), but when it comes to actual investments in smart manufacturing, what technologies are manufacturers truly prioritizing? 

According to Deloitte’s latest survey of 600 manufacturing executives, the answer might surprise you.

AI vs. Reality: The Investment Gap

Jeff Winter, a known thought leader in Industry 4.0 and digital transformation, recently shared an eye-opening chart that categorizes how manufacturers are approaching different technologies. While the buzz around AI—especially Generative AI—is louder than ever, the real-world funding decisions paint a different picture.

The Four Investment Quadrants

Deloitte's chart organizes technologies into four strategic quadrants:

1. Strategic Focus (High Use, High Priority)

These technologies are being used actively and are also high on the strategic agenda:

Data Analytics

Active Sensors

Cloud Computing

Factory Automation Hardware

IoT Platforms

Organizations investing here are the high achievers and innovators, aiming for measurable impact and sustainable growth through proven digital infrastructure.

2. Maintain and Monitor (High Use, Low Priority)

These are technologies already in use but not currently a focus for future investment:

Examples aren’t explicitly named, but it implies legacy systems or stable tech like 5G.


This quadrant represents early adopters and dependable stewards—companies optimizing what’s already working.

3. Emerging Opportunities (Low Use, High Priority)

These are underutilized technologies with strong strategic potential:

AI/ML

Robotics

Wearables

Edge Computing

Vision Systems


Manufacturers here are opportunity seekers and growth catalysts, willing to bet on tech with promising upside.

4. Low Focus (Low Use, Low Priority)

These are either futuristic or underwhelming technologies for most:

Quantum Computing

Blockchain

Humanoid Robots

AR/VR

Virtual PLC

Co-bots


This group includes the late adopters and idlers, choosing to ignore or wait out the maturity curve.

Generative AI: The Most Talked About, Least Funded?

Interestingly, Generative AI, despite dominating headlines, is still categorized in the “not using” area. While there's interest, real-world application in manufacturing remains limited—possibly due to integration challenges or unclear ROI.

What This Means for You

If you're in manufacturing or advising industry clients, this data suggests:

Prioritize proven technologies like cloud, analytics, and IoT.

Prepare for the next wave by monitoring emerging areas like AI/ML and robotics.

Don’t get lost in the hype—just because a tech is trendy doesn't mean it's immediately viable for your operation.

Final Thoughts

Smart manufacturing is not about adopting every new technology—it’s about strategic alignment, operational readiness, and sustainable impact. While AI will certainly play a role, current investment patterns reveal a clear preference for practical, data-driven innovations.

So, the next time someone asks, “Why aren’t we using AI?”—ask them instead: “Are we ready to get value from it?”

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