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Why Apple Could Become the Next Cloud Giant
Plus: BlackBerry Just Made One of Its Smartest AI Moves Yet
Jafar Najafov
April 20, 2026 • Read this in 3 minutes
In partnership with
Microsoft, Apple, and BlackBerry are taking three very different paths into AI, but each reveals where the next wave of value may emerge. Microsoft is driving real productivity gains inside enterprises, Apple could turn chip demand into a cloud business, and BlackBerry is quietly building the software layer for safety-critical AI systems. Together, they show AI’s future may be less about hype and more about infrastructure, utility, and trust.
In today’s post:
Apple may be sitting on its next AWS
AI is quietly transforming a $20B dairy giant
QNX is building where failure is not allowed.
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RESEARCH
The real AI opportunity for Apple may not be devices
Apple is known for selling premium hardware. But local AI demand could open a much bigger recurring revenue business.
Here's everything you need to know:
Apple Silicon has become one of the best platforms for running local AI models efficiently.
That is driving demand for high-memory Macs like Mac Studio and Mac mini systems.
Right now, Apple profits when users buy the hardware once and move on.
But there may be a better model: rent Apple Silicon compute in the cloud on subscription.
Imagine developers paying monthly for always-on macOS servers built for AI agents, workflows, and private tasks.
Amazon proved infrastructure can become more valuable than the original retail business.
If Apple enters this market, it turns hardware strength into recurring software-like revenue.
Markets reward companies that turn one-time purchases into recurring income. Apple already has the chips, ecosystem, and trust. If AI pushes demand for private compute, Apple may discover its next growth engine looks less like an iPhone and more like a utility.
BREAKTHROUGH
Real AI adoption rarely looks flashy. It looks operational.
Image credits: Microsoft
Fonterra is showing what practical AI deployment looks like. Not demos. Not hype. Just measurable improvements across a global business.
Here's everything you need to know:
Many companies talk about AI strategy while still searching for a real use case.
Fonterra is using AI inside factories, offices, and decision-making systems at scale.
At its Clandeboye site, AI monitors butter packaging and pauses production when faults appear.
Across more than 100 plants, IoT data feeds the cloud to improve predictive maintenance and reduce downtime.
Inside the business, staff are using Microsoft Copilot tools for meetings, drafting, workflows, and faster collaboration.
By February 2026, 35% of Fonterra’s workforce was actively using AI tools, generating nearly one million monthly interactions.
The real lesson: winners treat AI like infrastructure, not marketing.
The market overestimates flashy AI launches and underestimates quiet operational gains. When a company improves speed, uptime, decisions, and consistency across thousands of employees, compounding begins. That is where durable value is built.
PARTNERSHIP
BlackBerry just made a quiet AI move
While others chase headlines BlackBerry and NVIDIA just expanded their partnership. The move targets one of AI’s most valuable markets: systems where mistakes can cost lives.
Here's everything you need to know:
Most AI news focuses on chatbots, image tools, and consumer apps that grab attention fast.
But the harder opportunity sits inside robotics, medical devices, and industrial machines that must perform safely every second.
QNX is integrating its safety-certified operating system with NVIDIA’s IGX Thor platform for edge AI systems.
That means one stack can handle real-time control, safety requirements, and AI workloads together.
For developers, this shortens the path from prototype to production in tightly regulated industries.
For BlackBerry, it shows the company still owns valuable infrastructure where reliability matters more than hype.
Quiet businesses often look boring until the market realizes they power everything important.
Consumer AI gets attention, but industrial AI may create deeper moats. When software becomes trusted inside hospitals, factories, and robots, replacing it gets very hard. Sometimes the best opportunities are hidden behind old brand names.
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