A conversation with Syed Zaeem ‘Z’ Hosain, Co-Founder of Aeris
Aeris was founded long before “IoT” became a mainstream term. In the early days, connecting remote machines to application servers over cellular networks was expensive, inefficient, and unpredictable. Companies relied on voice-based cellular plans to move small amounts of data, often with little visibility into cost or scale.
That challenge became the starting point for Aeris.
“We didn’t even know exactly what we were going to build at first,” recalls Syed Zaeem ‘Z’ Hosain, a Founder of Aeris. “But we saw a clear problem, companies needed a more predictable, scalable way to connect machines.”
More than three decades later, the scale of connected devices and the data they generate has grown beyond anything imaginable at the time. That growth is now colliding with another major technological shift: Generative AI.
In this edition of Voices of Aeris, we spoke with Z about how decades of innovation cycles shape his perspective on today’s AI moment, where AI delivers the most value in IoT, and why human judgment remains essential.
A Long View on AI
With decades of experience in engineering and telecommunications, Z brings a long- term lens to the current AI conversation.
“Machine Learning and AI can uncover patterns at a speed and scale that humans simply can’t process,” he explains. “But the quality of what you get out still depends on the quality of what goes in.”
For Z, the real risk isn’t AI itself, but the assumption that its outputs are inherently correct. Without experience, context, and oversight, it’s easy to accept answers at face value simply because they came from an AI system.
That’s why judgment matters as much as technology.
Where AI Adds Real Value in IoT
The biggest opportunity for AI in IoT lies in scale. Today, millions of connected devices generate enormous volumes of data every month far faster than any human team can analyze manually.
AI helps surface patterns, anomalies, and insights from that data, enabling faster and more informed decisions. But in many IoT scenarios, timing is critical.
“In some use cases, decisions need to happen immediately,” Z explains. “You can’t afford to send everything back to a centralized system and wait for a response.”
This is where intelligence at the edge becomes essential, processing information close to where it’s generated, while balancing the speed of autonomy with the need for safety.
Balancing Autonomy and Responsibility
As companies scale, AI becomes increasingly necessary. But not all decisions carry the same level of risk.
Some actions are low-impact and well suited to AI-driven automation. Others, especially those that could affect safety, health, or critical infrastructure require additional safeguards and human involvement and oversight.
“The key is understanding where autonomy makes sense and where caution is required,” says Z. “AI should support better decisions, not remove the responsibility to prevent harm to people and our environment.”
This balance is especially important in IoT environments, where automated actions can have real‑world consequences.
A Founder’s Perspective
Throughout Aeris’s history, one principle has remained constant: technology should enable better decisions, not replace accountability.
Used thoughtfully, AI can accelerate insight, improve efficiency, and unlock new possibilities across connected systems. Used without care, it introduces new risks and false confidence.
For Z, the future of AI and IoT isn’t about choosing between humans and machines. It’s about designing systems where each plays the role that they’re best suited for.
That mindset continues to guide Aeris as AI and IoT evolve together.
This conversation is part of our ongoing Voices of Aeris: AI & the Future of Work series, highlighting how leaders across Aeris are thinking about innovation, responsibility, and what comes next.
