Predictions for IoT in 2026: From Connectivity to Capability

As we look to 2026, IoT will be shaped less by connectivity breakthroughs and more by three intersecting forces:

• Rapid operationalisation of AI
• Growing urgency for smarter data strategies
• Non-negotiable requirement for security at every layer.

At the same time, public sector organisations and enterprises are reassessing the role of IoT in a climate of constrained budgets, heightened scrutiny, and rising expectations around service reliability and resilience.

The implication is clear: technology investment must now justify itself through measurable impact. In 2026, successful IoT strategies will be defined by focus, integration, and execution – not experimentation and pilots.

From Data Collection to Intelligence Creation

For years, IoT programmes have been remarkably good at generating data, but far less effective at turning that data into insight. We’ve all seen lots of nice-looking visual dashboards that don’t actually connect to anything! The widespread adoption of AI in 2025 has started to change that equation. When AI is applied deliberately to IoT, it unlocks value from most data that has historically been ignored, stored but unused, or discarded altogether.

This shift is moving use cases such as predictive maintenance, infrastructure health monitoring, and smart place digital twins from future ambition into operational reality. Increasingly, organisations are combining sensor data with machine learning models and external data sources – such as weather or environmental data – to anticipate failure, model scenarios, and intervene earlier.

What matters now is not whether AI can be applied to IoT, but whether organisations have the data foundations, governance, and accountability required to apply it responsibly and efficiently to avoid siloed and shadow implementations. The emergence of formal AI leadership roles within local authorities reflects this growing recognition: intelligence without coordination or trust is not progress.

Edge AI Signals a Structural Change

Edge processing, where inference and analytics occur on-device or in nearby gateways, can reduce latency and improve resilience. Over recent years, we’ve witnessed the surveillance market rapidly shift toward edge AI and on-board camera analytics, reducing the dependency on cloud-centric processing, improving reliability.

Low-power networks such as LoRaWAN and NB-IoT have always prioritised coverage and battery life over bandwidth. Advances in low-power AI acceleration now allow devices to interpret data locally – detecting anomalies, correlating inputs, and determining relevance—before transmitting only what matters.

This fundamentally changes the role of IoT devices. They are no longer passive collectors of raw data, but active participants in decision-making. The result is faster response times, improved resilience, reduced data movement, and better alignment with enterprise strategies around cost, privacy, and decentralised architectures.

In 2026, edge intelligence be the preferred method of initial data interpretation for many core use cases.

Security Is Now a Strategic Differentiator

Local councils and enterprises alike are confronting increasingly sophisticated cyber threats. While resilience is improving and defensive guardrails are being implemented, capability remains uneven and recovery from incidents is more complex.

IoT devices are increasingly operating in widely distributed environments, attack surfaces expand, and security risks escalate. Traditional perimeter defences are insufficient when millions of endpoints connect across public and private networks using varied protocols.

In 2026, embedding protection right from the hardware level with secure boot, identity verification through platforms with end-to-end encrypted communications, and lifecycle management will become more than just best practice but increasingly mandated through regulation and commercial expectation. This shift is already influencing buying behaviour, from those who seek providers with expertise and track record to deliver innovation without compromising on security.

Security will therefore continue to be a core strategic issue shaping procurement and partnership decisions in 2026.

Solving the IoT Data Paradox

Despite growing intelligence at the edge, organisations continue to struggle with a familiar paradox: an abundance of data and a shortage of insight. The winners in the next phase of IoT will be those that can orchestrate data from device to edge to cloud, filtering noise, contextualising signals, and presenting insight in a way that drives action.

Equally important is integration. IoT data rarely delivers value in isolation. Its power is realised when combined across traditionally siloed systems and made accessible, securely and selectively, within broader enterprise and AI platforms.

This is why abstraction layers that unify device management and connectivity across cellular, Wi-Fi, and LPWA networks are becoming critical. Real-world deployments are hybrid by nature, and flexibility is essential as standards, use cases, and operational demands continue to evolve.

Looking Ahead

In 2026, IoT success will not be measured by the size of a deployment, but by the quality of insight, resilience, and outcomes it delivers. Intelligence, security, and data strategy are no longer optional enhancements; they are the foundations on which credible IoT programmes are built.

The organisations that succeed will be those that treat IoT not as a standalone technology, but as a strategic capability – one that connects infrastructure, data, and decision-making into a coherent, trusted system. That is where the next era of value will be created.

By Tom Worley, Head of IoT at North