The Internet of Things represents a technology category where physical devices generate intangible value. A connected sensor, smart device, or industrial IoT platform creates value not through the hardware itself but through the software, data, algorithms, and platform connectivity that make the device intelligent and useful.
Under IFRS 3, IoT technology is classified as a technology-based intangible asset. However, "IoT technology" is not a single asset — it is a stack of interdependent intangible assets, each potentially requiring separate identification and valuation in a business combination.
The IoT market has matured significantly. What was once an emerging technology category is now a multi-hundred-billion-dollar ecosystem spanning industrial automation, smart buildings, connected healthcare, agriculture technology, and consumer devices. The intangible assets embedded in these systems are substantial and growing.
An IoT system typically contains multiple separable intangible assets:
| Layer | Intangible Asset | IFRS 3 Category | Valuation Approach |
|---|---|---|---|
| Firmware | Embedded software in devices | Technology-based (software) | Cost approach |
| Communication protocols | Proprietary connectivity standards | Technology-based (unpatented tech) | Cost or RFR |
| Cloud platform | IoT data ingestion, storage, processing | Technology-based (software) | RFR or income |
| Analytics and AI models | Predictive maintenance, anomaly detection | Technology-based (algorithms) | Income approach |
| Accumulated sensor data | Historical readings, patterns, benchmarks | Technology-based (database) | Cost or income |
| Customer relationships | Device fleet owners and platform subscribers | Customer-related | MPEEM |
| Patents | Novel hardware/software inventions | Technology-based (patents) | RFR |
When acquiring an IoT business, the intangible value is distributed across multiple layers of the technology stack. Firmware, platform software, analytics models, accumulated data, and customer relationships each require separate identification. Treating "the IoT technology" as a single asset oversimplifies the valuation and may misstimate the total intangible value.
IoT businesses frequently operate platform models where the device is the entry point and the recurring value comes from data, analytics, and service subscriptions. This creates a specific valuation dynamic:
Many IoT companies sell hardware at or below cost and monetise through recurring software subscriptions, data services, or analytics products. The intangible assets (software platform, data analytics, customer relationships) are the primary value drivers, while the hardware is a loss-leading distribution mechanism.
Map all subscription, licensing, and data service revenue generated by the IoT platform. Separate hardware revenue from recurring software/data revenue.
Determine how much of the recurring revenue is driven by the platform software, how much by the analytics/AI, and how much by the accumulated data. Each layer may have a different useful life and risk profile.
IoT systems create a data accumulation flywheel: more devices generate more data, which improves analytics, which attracts more customers. The accumulated data and the trained models represent compounding intangible value.
A smart building IoT company is acquired with 50,000 connected sensors deployed across 500 commercial properties. The platform generates £12 million in annual recurring subscription revenue (software + analytics). The accumulated sensor dataset — 3 years of environmental, energy, and occupancy data — enables predictive maintenance models that reduce building operating costs by 15-20%. The platform software is valued at £8 million (RFR, 5-year life), the AI models at £4 million (income approach, 3-year life), and the historical dataset at £6 million (cost approach, 5-year life).
In many IoT acquisitions, the accumulated sensor data is the most irreplaceable asset. The software platform can be rebuilt. The hardware can be redesigned. But years of operational data from thousands of deployed devices — capturing real-world patterns, anomalies, and performance characteristics — cannot be recreated without deploying equivalent devices and waiting equivalent time.
This data has value across multiple dimensions:
Manufacturing and industrial IoT platforms generate the highest-value data because industrial process data directly enables cost reduction, yield improvement, and predictive maintenance — all with quantifiable economic benefit. Valuation can use the income approach based on demonstrated cost savings.
Connected medical devices (remote patient monitoring, wearable diagnostics) generate sensitive health data with significant regulatory implications. The data may be highly valuable for clinical research and AI model training, but GDPR/HIPAA compliance requirements affect how the data can be used and monetised.
Consumer IoT data tends to be high volume but lower per-unit value. The aggregate value lies in user behaviour patterns and household insights that can be monetised through advertising, energy management, or insurance partnerships.
IoT data privacy is an escalating regulatory concern. Data collected through smart devices in homes, workplaces, and public spaces raises surveillance, consent, and privacy issues. Valuation must account for the legal permissions embedded in the data — data collected without proper consent may have zero commercial value, or may represent a regulatory liability.
IoT intangible assets have relatively short useful lives due to rapid technology evolution:
The movement toward edge computing — processing data on the device rather than in the cloud — is shifting where IoT intangible value resides. More sophisticated firmware, on-device AI models, and local data processing increase the value of the device-level software while potentially reducing the value of the centralised cloud platform. Valuation must assess the architectural direction and where the intelligence (and therefore the intangible value) is concentrated.
IoT technology is one of ten technology-based intangible assets under IFRS 3. For the full taxonomy, see 35 types of intangible assets. To explore technology intangible assets more broadly, read our technology and SaaS intangible collateral guide.
Ivan Gowan is the Founder and CEO of Opagio. He brings 25 years of experience building and scaling technology platforms in financial services. Meet the team.
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