USA
AI Is Shifting Connected Products From Devices to Outcomes
3 min read
Connected products have spent years generating enormous volumes of data — sensor readings, telemetry, historical logs. Yet much of this information was rarely used to drive decisions or create measurable business value. It accumulated in storage systems, occasionally appearing in dashboards, but without making products meaningfully smarter or more reliable. According to Evgeniy Yakovlev, Vice President at Sigma Software, AI is changing this dynamic by adding a layer that finally makes long‑standing promises of connected devices work in practice.
AI doesn’t necessarily introduce new capabilities. Rather, it enhances the effectiveness of existing ones. Predictive maintenance becomes more dependable instead of theoretical. Automation relies less on manual configuration and more on adaptive behavior that adjusts to real‑world conditions.
Devices require fewer settings, demand less attention from the user, and behave more predictably over time. This is not so much a revolution in features as a shift in the operational quality of the product itself.
One of the most significant areas where this shift is already visible is energy. Devices have measured consumption for years, but with AI, they begin actively optimizing it — predicting peaks, adjusting performance to reduce waste, and responding to changing conditions with far greater precision.
Even relatively small improvements can translate into meaningful impact, especially now, when energy has become one of the major cost drivers for many industries. This combination of cost pressure, competition, and regulatory expectations is one of the reasons interest in AI‑enhanced optimization continues to grow rapidly.
As the role of AI expands, questions around data ownership are becoming more critical. For many companies, especially in industrial and infrastructure‑heavy sectors, data is a core strategic asset.
Looking for help to start building efficient connected products?
Not everyone is ready to share it externally, and concerns about intellectual property, control, and confidentiality are growing rather than diminishing. This is one of the drivers behind the increasing interest in private and in‑house AI implementations. Even though they are often more complex and resource‑intensive to build, they offer a level of control that organizations consider essential.
At the same time, the rapid growth of the AI market brings a flood of solutions that vary widely in quality. It is becoming harder for companies to navigate this space, because many tools look promising on the surface but fail to deliver under real‑world conditions.
As Evgeniy notes, the challenge is shifting: it is no longer about deciding whether to adopt AI, but about understanding how to evaluate it and developing enough internal expertise not to get lost in the noise.
Looking ahead, Evgeniy shares a personal view on how AI may influence business models in connected products. If a device continuously learns, adapts, and optimizes its own performance, the center of value may gradually move away from the physical hardware toward the result the product provides.
This could eventually lead to a shift from selling devices to delivering outcomes — not an air conditioner, but a consistently comfortable indoor environment; not a vacuum cleaner, but a home that remains clean without intervention; not a device, but a result the user no longer needs to think about. This isn’t something that will happen overnight. Yet early signs of such a shift can already be observed in sectors where the boundary between hardware, software, and services continues to blur.
See also: From Simulation to Reality: Building Predictive Maintenance for Connected Vehicles
Share article:
Sigma Software Group provides IT services to enterprises, software product houses, and startups. Working since 2002, we have build deep domain knowledge in AdTech, automotive, aviation, gaming industry, telecom, e-learning, FinTech, PropTech. We constantly work to enrich our expertise with machine learning, cybersecurity, AR/VR, IoT, and other technologies. Here we share insights into tech news, software engineering tips, business methods, and company life.
Linkedin profile
Related Articles
How Connected Product Enablement Turns Equipm...
For decades, the manufacturing formula for success was the same – build great equipment, ship to the Client, and get the profit. Now, more OEMs are discovering ...
The EU Data Act: A Practical Guide for Connec...
If you own a product line, run an embedded or connectivity team, or look after the cloud and data stack for connected devices, the EU Data Act probably didn’t a...
Building a Web Version in 10% of the Estimate...
At Sigma Software, we constantly explore how emerging technologies can amplify engineering efficiency. Recently, a team from Sigma Software that develops Dovkol...