A study from Eseye is warning that billions in artificial intelligence (AI) investment is being threatened by what it calls “fundamentally unreliable” internet of things (IoT) connectivity.
Now in its fifth year, the 2025 edition of the State of IoT report from the global IoT firm surveyed 1,200 senior IoT decision-makers and implementers of IoT strategy who had undertaken at least one IoT project in the past 12 months, with IoT devices deployed across at least three countries and connecting through cellular networks. The data was collected between 28 May and 3 June 2025.
The research stressed that among the key elements of strategic IoT were device reliability, global connectivity, security and, now more than ever, sustainability. Yet it also warned that unreliable data streams were putting corporate AI strategies at risk, with findings showing only 2% of firms had achieved the high levels of connectivity required. In addition, poor connectivity from IoT devices was seen to be hindering the adoption of AI in a third of businesses (34%).
Moreover, the study highlighted that this so-called performance gap existed despite the majority of business leaders stating that high-connectivity performance is essential for device uptime. The research found that 74% agreed with the statement that “achieving near-100% global connectivity is crucial to my business case”.
It also warned that such unreliability has direct operational consequences. More than a third of businesses cited an “inability to gather timely and accurate data due to device downtime, leading to poor business decisions” (36%) and damage to their company’s reputation (36%) as key risks. A similar number pointed to a “loss of operational efficiency and increased costs due to unreliable connections” (35%).
“We all hear about the incredible promise of AI to help us solve major global challenges, from creating smarter healthcare and more sustainable cities, to managing our energy and water resources,” said Eseye co-founder and chief customer officer Paul Marshall. “But what’s often missed is that these revolutionary AI models are completely dependent on a constant stream of real-world data from a vast network of IoT sensors.
“Our research reveals a critical flaw in this foundation. We found that only 2% of these IoT deployments are achieving the near-100% connectivity they need. This means we may be building our transformative AI ambitions on a network that isn’t yet consistently dependable. This isn’t just a risk to business ROI, it’s a risk to the evolution of AI applications.”
Marshall also stressed just how important this could be in real-world applications, adding that in mission-critical IoT scenarios, failure isn’t just inconvenient, it’s potentially life-threatening.
“Imagine a life-saving medical sensor detecting a dangerous drop in a patient’s oxygen levels,” he said. “If that data point can’t be transmitted and then analysed by AI applications due to a failed connection, the alert never reaches clinicians in time. The result? A missed opportunity to intervene, and potentially a preventable fatality. To make the promise of AI a reality for everyone, we must first solve this foundational IoT connectivity challenge.”
