What IoT Means for the Future of Technology Businesses

What is IoT?

IoT (Internet of Things) refers to the expansion of internet connectivity and digital capabilities into objects -- from thermostats to glucometers to industrial equipment to sensors for autonomous vehicles. Effectively, IoT merges the physical and digital worlds, with human-to-object and object-to-object connections that can power ambient intelligence.

Affordable sensors and devices, advances in networking and the growing ubiquity of devices such as mobile phones and wearables have set the stage for IoT to grow. IoT businesses show hardware and software beginning to merge in domains such as smart home applications, a trend that is likely to continue.

How IoT Produces Value

IoT produces value by enabling new digital and physical experiences and reducing friction in existing ones. Here are some of the key drivers:


What IoT Means for the Future of Business Models and Verticals

IoT offers several opportunities for changing business models. One path is optimizing the use and management of physical resources. Another path is automation, as device-to-device communication may be capable of solving problems previously requiring human labor. Key areas that could be transformed by IoT are manufacturing, energy (smart grids), supply chain, health care, smart homes/cities/buildings and cybersecurity.


IoT also has a key role to play as an enabler for other transformative technologies. Companies that lead in IoT adoption will end up with a data advantage that can be leveraged to create an AI and analytics advantage. IoT offers a potential solution to many issues that can impede effective use of AI: data scarcity and the need for human effort in collecting, wrangling and standardizing that data. At the same time, IoT’s physical presence will allow companies to bring applied AI to bear on new domains where historically there has not been a significant digital footprint for analysis.

Additionally, companies adopting IoT will have an advantage in adopting other emerging technologies. IoT sensor networks can provide data for input to AR/VR-based immersive experiences and quantum algorithms, for example.



  • Mesh networks will provide no-dead zone connectivity required for fully embedding AR into daily life
  • Immersive physical and digital worlds are created by using IoT as input, and AR as output


  • IoT sensor networks provide massive volumes of data required to fully realize the potential of quantum algorithms
  • Energy-efficient quantum encryption will deliver lattice-based cryptography for all components in IoT architecture


  • Blockchain-IoT unlocks trust-first use cases such as remote auto asset management (M2M), P2P item delivery and usage insights for consumer goods
  • IoT will enhance transparency and compliance for transactions on the Blockchain, driving overall adoption

IoT will drive several changes for startups. Because of the trust risks and increased data volumes associated with IoT, hiring a Chief Data Officer and/or Chief Trust Officer may become an earlier priority. Teams will need to have knowledge of algorithms capable of handling IoT data and hardware knowledge. IT teams may need to be larger to manage sensors and devices. IoT startups may need increased funding and may need to devote more cycles to interoperability with other components of the IoT ecosystem.

Requirements for an IoT Solution

Mature IoT solutions require the following:


Trust. A proactive trust strategy addressing endpoint security, data privacy and transparency, which are particularly acute challenges for IoT.


Sensors and devices. Sensors gather real-world data. Devices process and store data in real time.


Advanced networking. LPWAN and 5G ensure data velocity and reliability and send data to cloud or on-premise storage and applications.


Data processing and analysis capabilities in a distributed / ubiquitous environment. Edge computing is a required technology due to high data volumes.


Artificial Intelligence. Interpreting sensor data and using it to make predictions and drive downstream actions.

IoT and Trust

Because of the pervasive nature and real-world integration of IoT, trust risks in this space are significant. IoT devices are vulnerable to cybersecurity attacks that could compromise secure communications or data integrity. Devices are vulnerable to environmental damage as well as physical interference by malicious actors. Because IoT may be deployed as a part of critical infrastructure, such as transportation and energy grids, the risks of a breach or reliability failure can be particularly severe.

Given the types and volume of data collected, IoT can also raise privacy concerns. Data from health care settings and smart home applications can be particularly sensitive, and privacy breaches involving smart speakers have made the news repeatedly. While much of IoT’s value comes from knowing data about a specific real-world object, that utility must be balanced with the privacy benefits of aggregating or anonymizing data. Federated learning, a decentralized, privacy-preserving approach to machine learning,  is one promising approach to balancing these considerations.


The white paper will enable you to:

  • Understand why trust is a factor of the value you deliver and the comfort you provide to your customers
  • Build a trust strategy around the value you provide to your customers over their lifecycle
  • Approach security, privacy, fairness, reliability and transparency to build trust
  • Measure your current state and track progress on our maturity model
  • See each principle in context through a case study


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The era of IoT is here. The space has seen ~$20B in investment and billions more in acquisitions such as Ring and Nest. Google and Amazon are making large investments in the space; Microsoft announced a 4-year, $5B fund focused on IoT. Market readiness is high, with both consumers and businesses expressing high interest in IoT. Products such as Alexa and FitBit have already become household names, and mobile devices are ubiquitous.

The underlying technologies powering IoT solutions are quickly advancing. 15 companies are deploying 5G, and 22B IoT devices are already in use. Other key emerging technologies are digital twins, edge computing, anonymization algorithms and distributed/federated learning.

Imagine a not-too-distant future powered by the rise of IoT: a refrigerator is manufactured in a smart factory, where IoT sensors continually monitor equipment for predictive maintenance. It is delivered to consumers by an autonomous vehicle traveling over roads in which embedded traffic sensors send data which influences traffic lights and vehicle routing. Once installed, the refrigerator is integrated into the home’s smart home infrastructure controlled via smart speakers. An in-fridge camera supplies real-time images of the available food in the fridge, and the resulting data is used to generate suggestions in the user’s grocery delivery app.


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