Skip to main content

IoT Failures Plague Users Worldwide

Half (52%) of consumers worldwide are now using Internet of Things (IoT) devices, yet 64% of those have already encountered performance issues – according to a global survey of 10,000 consumers conducted by Dynatrace, entitled IoT Consumer Confidence Report: Challenges for Enterprise Cloud Monitoring on the Horizon

On average, consumers experience 1.5 digital performance problems every day, and 62% of people fear the number of problems they encounter, and the frequency, will increase due to the rise of IoT.

For organizations deploying IoT strategies, these results indicate a critical need to master two things. Firstly, escalating IT complexity, thanks to new cloud technologies, microservices and the pressure to innovate faster.

Secondly, the necessity to build out well-planned IoT monitoring and performance strategies to ensure sound application delivery and a great digital experience.

Dave Anderson, digital performance expert, elaborated on the report findings and the challenges they pose to corporations, “The delivery chain behind every connected device is extremely complex. Businesses are already struggling with cloud complexity, but IoT magnifies this with sensors, masses of new data and dynamic containerized workloads.

“Consumers are already reporting problems with everything from medical applications, smart meters, car door locks and virtual personal assistants, to smart thermostats and fridges. Their patience is at an all-time low and they simply won’t tolerate a poor experience. Yet, we haven’t even seen the era of IoT take off to its full potential – it’s just getting started. The imperative is on companies to find ways to process, analyze and manage the IoT delivery chain holistically, and with deep insight, so they know exactly what’s happening and where issues are arising in real time. This is not an easy task.”

IoT on the road

The digital performance failures consumers are already experiencing with everyday technology is potentially making them wary of other uses of IoT.

85% of respondents said they are concerned that self-driving cars will malfunction – leading to high-speed collisions. Even more concerning, 72% feel it is likely software glitches in self-driving cars will cause serious injuries and fatalities.

Furthermore, 84% of consumers said they wouldn’t use self-driving cars due to a fear of software glitches.

“The reality is IoT glitches could be fatal. Consumers are understandably concerned and that’s why it will be important for the industry to demonstrate it’s taking a new, more robust approach to ensure software doesn’t compromise our safety,” Anderson continued.

Aside from self-driving cars, 86% of consumers expressed concern that digital locks will see them locked out of their vehicles, while 67% predict serious issues on the roads due to performance problems with smart city traffic lights.

IoT in Healthcare

Concerns around IoT performance were also underlined when consumers were asked about healthcare, another area where software issues are a massive concern. 62% of consumers stated they would not trust IoT devices to administer medication; this sentiment is strongest in the 55+ age range, with 74% expressing distrust.

There were also specific concerns about the use of IoT devices to monitor vital signs, such as heart rate and blood pressure. 85% of consumers expressed concern that performance problems with these types of IoT devices could compromise clinical data.

IoT in the Home

As well as the automotive and healthcare industry, the home is also set to be transformed by the IoT. Smart locks are used for security, while other IoT devices control thermostats, lighting, and cameras. However, the research revealed 83% of consumers are concerned about losing control of their smart home due to digital performance problems. More specifically, the survey showed:

■ 73% of consumers fear being locked in or out of the smart home due to bugs in smart home technology

■ 68% of consumers are worried they won’t be able to control the temperature in the smart home due to malfunctions in smart home technology

■ 64% of consumers fear not being able to control lights in the smart home due to glitches in smart home technology

■ 81% of consumers are concerned that technology or software problems with smart meters will lead to them being overcharged for gas, electricity, and water.

Anderson concluded, “The old ways of managing IT and software simply don’t work against this extremely convoluted IT environment. IoT creates many blind spots and an additional layer of complexity. That’s why the early, successful IoT adopters take the view that AI is the answer; to make sense of the complexity, map the IT environment end-to-end, pick up problems immediately and with precision, and offer up answers for fast resolution. That’s the only way to master the IoT era, which is already upon us. Consumers want perfect IoT experiences. Become masters of this new IT universe or you’ll miss out on the opportunity IoT presents.”

About the Survey: This report, commissioned by Dynatrace, is based on an online survey conducted by Opinium Research, of 10,002 respondents with 2,000 in the UK, 2,000 in the USA, and 1,000 respondents in France, Germany, Australia, Brazil, Singapore, and China respectively. The survey includes responses from 4,796 male and 5,206 female adults grouped by age (18-34, 35-54 and 55+).

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

IoT Failures Plague Users Worldwide

Half (52%) of consumers worldwide are now using Internet of Things (IoT) devices, yet 64% of those have already encountered performance issues – according to a global survey of 10,000 consumers conducted by Dynatrace, entitled IoT Consumer Confidence Report: Challenges for Enterprise Cloud Monitoring on the Horizon

On average, consumers experience 1.5 digital performance problems every day, and 62% of people fear the number of problems they encounter, and the frequency, will increase due to the rise of IoT.

For organizations deploying IoT strategies, these results indicate a critical need to master two things. Firstly, escalating IT complexity, thanks to new cloud technologies, microservices and the pressure to innovate faster.

Secondly, the necessity to build out well-planned IoT monitoring and performance strategies to ensure sound application delivery and a great digital experience.

Dave Anderson, digital performance expert, elaborated on the report findings and the challenges they pose to corporations, “The delivery chain behind every connected device is extremely complex. Businesses are already struggling with cloud complexity, but IoT magnifies this with sensors, masses of new data and dynamic containerized workloads.

“Consumers are already reporting problems with everything from medical applications, smart meters, car door locks and virtual personal assistants, to smart thermostats and fridges. Their patience is at an all-time low and they simply won’t tolerate a poor experience. Yet, we haven’t even seen the era of IoT take off to its full potential – it’s just getting started. The imperative is on companies to find ways to process, analyze and manage the IoT delivery chain holistically, and with deep insight, so they know exactly what’s happening and where issues are arising in real time. This is not an easy task.”

IoT on the road

The digital performance failures consumers are already experiencing with everyday technology is potentially making them wary of other uses of IoT.

85% of respondents said they are concerned that self-driving cars will malfunction – leading to high-speed collisions. Even more concerning, 72% feel it is likely software glitches in self-driving cars will cause serious injuries and fatalities.

Furthermore, 84% of consumers said they wouldn’t use self-driving cars due to a fear of software glitches.

“The reality is IoT glitches could be fatal. Consumers are understandably concerned and that’s why it will be important for the industry to demonstrate it’s taking a new, more robust approach to ensure software doesn’t compromise our safety,” Anderson continued.

Aside from self-driving cars, 86% of consumers expressed concern that digital locks will see them locked out of their vehicles, while 67% predict serious issues on the roads due to performance problems with smart city traffic lights.

IoT in Healthcare

Concerns around IoT performance were also underlined when consumers were asked about healthcare, another area where software issues are a massive concern. 62% of consumers stated they would not trust IoT devices to administer medication; this sentiment is strongest in the 55+ age range, with 74% expressing distrust.

There were also specific concerns about the use of IoT devices to monitor vital signs, such as heart rate and blood pressure. 85% of consumers expressed concern that performance problems with these types of IoT devices could compromise clinical data.

IoT in the Home

As well as the automotive and healthcare industry, the home is also set to be transformed by the IoT. Smart locks are used for security, while other IoT devices control thermostats, lighting, and cameras. However, the research revealed 83% of consumers are concerned about losing control of their smart home due to digital performance problems. More specifically, the survey showed:

■ 73% of consumers fear being locked in or out of the smart home due to bugs in smart home technology

■ 68% of consumers are worried they won’t be able to control the temperature in the smart home due to malfunctions in smart home technology

■ 64% of consumers fear not being able to control lights in the smart home due to glitches in smart home technology

■ 81% of consumers are concerned that technology or software problems with smart meters will lead to them being overcharged for gas, electricity, and water.

Anderson concluded, “The old ways of managing IT and software simply don’t work against this extremely convoluted IT environment. IoT creates many blind spots and an additional layer of complexity. That’s why the early, successful IoT adopters take the view that AI is the answer; to make sense of the complexity, map the IT environment end-to-end, pick up problems immediately and with precision, and offer up answers for fast resolution. That’s the only way to master the IoT era, which is already upon us. Consumers want perfect IoT experiences. Become masters of this new IT universe or you’ll miss out on the opportunity IoT presents.”

About the Survey: This report, commissioned by Dynatrace, is based on an online survey conducted by Opinium Research, of 10,002 respondents with 2,000 in the UK, 2,000 in the USA, and 1,000 respondents in France, Germany, Australia, Brazil, Singapore, and China respectively. The survey includes responses from 4,796 male and 5,206 female adults grouped by age (18-34, 35-54 and 55+).

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...