For years, the Internet of Things industry has been stuck in what veterans call “pilot purgatory” — a frustrating cycle where promising connected-device projects prove their worth in controlled environments but never graduate to full-scale production. At the IoT Tech Expo 2026, held in London’s Olympia venue, the conversation shifted decisively from experimentation to execution, with industry leaders laying out concrete strategies for scaling connectivity across global production networks.

The second day of the expo, as reported by IoT Tech News, was dedicated to the thorny operational realities of moving IoT deployments from isolated test beds to sprawling, multi-site industrial environments. Speakers from major technology firms, telecommunications providers, and manufacturing conglomerates converged on a central theme: the tools, standards, and business models required to make IoT work at scale are finally maturing — but the path forward demands a fundamentally different approach to architecture, partnerships, and data governance.

Breaking Free From Pilot Purgatory

The challenge of scaling IoT has never been purely technical. While early deployments often stumbled on hardware reliability and connectivity gaps, the more persistent barriers have been organizational and economic. Enterprises that successfully ran pilot programs connecting a few hundred sensors in a single factory found that replicating those results across dozens of facilities in different countries introduced exponential complexity — different regulatory regimes, varying network infrastructure, incompatible legacy systems, and workforce readiness gaps that no amount of clever engineering could paper over.

At the expo, presenters emphasized that the industry has learned hard lessons from a decade of false starts. The consensus emerging from London is that successful scaling requires what several speakers described as a “platform-first” mentality, where organizations invest in flexible middleware and integration layers before deploying a single sensor. This approach prioritizes interoperability and data standardization from the outset, rather than treating them as afterthoughts that can be bolted on once a pilot proves its value. The shift represents a maturation of thinking that separates the current generation of IoT deployments from the hype-driven initiatives of the late 2010s.

Connectivity Infrastructure as the Foundation for Industrial Transformation

One of the most substantive discussions at the event centered on the evolution of connectivity options available to industrial IoT deployments. The proliferation of Low Power Wide Area Network (LPWAN) technologies, the continued rollout of 5G standalone networks, and the emergence of satellite-based IoT connectivity through providers like AST SpaceMobile and various LEO constellation operators have collectively eliminated many of the coverage gaps that previously constrained deployments. For manufacturers operating in remote or geographically dispersed locations, the ability to maintain reliable, low-latency connections to thousands of devices is no longer a theoretical promise but an operational reality.

The expo highlighted how telecommunications companies are repositioning themselves not merely as connectivity providers but as end-to-end IoT enablers. Carriers are increasingly offering managed IoT services that bundle connectivity with device management, security monitoring, and analytics platforms. This bundled approach addresses one of the most persistent complaints from enterprise customers: the difficulty of managing relationships with dozens of vendors across the IoT stack. By consolidating these functions, telcos are attempting to reduce the integration burden that has historically slowed deployments and driven up costs.

Data Governance and the Geopolitics of Connected Manufacturing

As IoT networks expand across borders, data governance has emerged as one of the most complex challenges facing global manufacturers. The expo devoted significant attention to the regulatory patchwork that companies must navigate when deploying connected systems internationally. The European Union’s evolving data regulations, China’s strict data localization requirements, and the United States’ sector-specific privacy frameworks create a compliance maze that can paralyze even well-resourced organizations. Speakers noted that companies scaling IoT globally must now employ dedicated data governance teams — a cost center that rarely appears in the optimistic ROI projections of pilot-stage business cases.

The geopolitical dimension of IoT scaling extends beyond data privacy. Supply chain security concerns have prompted several governments to restrict the use of certain IoT hardware and software components based on their country of origin. These restrictions add another layer of complexity to procurement decisions and can force companies to maintain parallel technology stacks for different markets. Industry leaders at the expo argued that open standards and vendor-neutral architectures are the most effective hedge against geopolitical risk, enabling organizations to swap components without redesigning entire systems.

Edge Computing and AI: The Intelligence Layer That Makes Scale Viable

The integration of edge computing and artificial intelligence into IoT architectures was presented at the expo as the critical enabler that makes large-scale deployments economically viable. Raw data from thousands of sensors is essentially worthless — and expensive to transmit — without intelligent processing at the point of collection. Edge AI allows organizations to filter, analyze, and act on data locally, sending only meaningful insights to centralized cloud platforms. This approach dramatically reduces bandwidth costs, improves response times for critical applications, and addresses data sovereignty concerns by keeping sensitive information within local jurisdictions.

Several presenters showcased real-world implementations where edge intelligence had transformed the economics of IoT at scale. Predictive maintenance applications, for instance, have evolved from simple threshold-based alerting systems to sophisticated machine learning models that can identify subtle patterns in equipment behavior weeks before a failure occurs. When deployed across hundreds of machines in multiple facilities, these systems generate millions of dollars in avoided downtime and reduced maintenance costs. The key insight shared at the expo was that the value of IoT scales non-linearly — the more devices and data points connected to an intelligent network, the more accurate and valuable the insights become.

The Business Model Evolution: From CapEx to Outcome-Based Pricing

Perhaps the most significant shift discussed at the IoT Tech Expo was the evolution of business models surrounding IoT deployments. The traditional capital expenditure model, where companies purchase hardware and software licenses upfront, is giving way to outcome-based and as-a-service pricing structures. Under these models, IoT solution providers are compensated based on measurable business outcomes — reduced energy consumption, improved yield rates, decreased unplanned downtime — rather than the volume of hardware deployed.

This shift aligns the incentives of solution providers with those of their customers and removes one of the most significant barriers to scaling: the large upfront investment required to instrument an entire global operation. By converting capital expenditures into operational expenses tied to demonstrated value, outcome-based models make it easier for companies to justify expanding IoT deployments beyond initial pilot sites. Several speakers noted that this approach also forces solution providers to focus relentlessly on delivering measurable results, which elevates the quality and reliability of the entire ecosystem.

Workforce Development and the Human Element of Scaling IoT

Technology alone cannot solve the scaling challenge. Multiple sessions at the expo addressed the critical importance of workforce development in enabling successful IoT deployments at scale. The skills required to design, deploy, and maintain large-scale IoT networks span an unusually broad range of disciplines — from embedded systems engineering and network architecture to data science, cybersecurity, and change management. Finding individuals who can bridge these domains is extraordinarily difficult, and the talent shortage is particularly acute in manufacturing sectors that have historically struggled to attract technology workers.

Companies that have successfully scaled IoT operations shared a common strategy: investing heavily in upskilling existing operational technology (OT) staff rather than relying exclusively on external IT hires. Factory floor technicians who understand the physical processes being monitored bring invaluable domain expertise that pure technologists lack. By equipping these workers with data literacy skills and providing intuitive tools that abstract away the complexity of underlying IoT systems, organizations can build internal capabilities that sustain and expand deployments over time. This human-centered approach to scaling was repeatedly cited as the differentiator between companies that escape pilot purgatory and those that remain trapped in it.

What the Next Phase of Industrial IoT Demands

The IoT Tech Expo 2026 made clear that the industry stands at an inflection point. The foundational technologies — reliable connectivity, affordable sensors, powerful edge computing, and sophisticated AI — are no longer the primary constraints. The challenges that remain are structural and strategic: building interoperable architectures that work across borders, navigating an increasingly complex regulatory environment, developing sustainable business models that justify investment at scale, and cultivating the human talent needed to operate these systems effectively.

For industry insiders, the message from London was both encouraging and sobering. The path from pilot to global production network is now well-mapped, but it demands a level of organizational commitment, cross-functional collaboration, and strategic patience that many companies have yet to demonstrate. Those that master these disciplines will unlock the transformative potential that IoT has promised for more than a decade. Those that don’t will find themselves watching from the sidelines as their competitors build the connected industrial operations of the future.