We are thrilled to be published by Gartner on Emerging Technologies and Trends Impact Radar on Internet of Things and Artificial Intelligence, 2021.
1. Emerging Technologies and Trends Impact Radar: Internet of Things
Product leaders building IoT-enabled business solutions face a rapidly evolving technology and market landscape. IoT product leaders must use a balanced differentiation and risk approach as they adopt emerging technologies to gain advantage and help enable their customer’s composable enterprise.
- New technology acceleration is creating disruptive innovation opportunities for TSPs to augment and replace OT systems.
- Data gravity drives data to be processed where and when it is valuable. There is a continued drive toward balancing edge and cloud capabilities to process data where most appropriate.
- The strategic focus in IoT is increasingly shifting from platforms to applications, requiring packaged application-centric solutions to deliver value.
Product leaders responsible for evaluating IoT technologies for their growth and impact potential for products and services must:
- Accelerate their adoption of IoT + edge + AI containerized solutions to capitalize on short- to medium-term replacement opportunities. Look to ongoing innovations in AI, ML and automation for longer-term roadmap development.
- Implement a hybrid IoT edge and cloud business strategy by building a flexible hybrid technology architecture that enables data processing when and where it adds maximum customer value.
- Drive customer value by augmenting platform offerings with use-case-specific packaged business capabilities and applications delivered through partner ecosystems and dedicated marketplaces.
Overview of the Emerging Technologies and Trends Impact Radar
The Emerging Technologies and Trends Impact Radar is an analysis of the maturity, market momentum and influence of emerging technologies and trends. In this Emerging Technologies and Trends Impact Radar, Gartner includes 18 emerging technologies and trends (ETTs) with horizontal impact on IoT technology and service providers (TSPs), as related to the TSPs’ ability to pivot forward and accelerate their business opportunities. These 18 technology profiles cover both the “what” and the “how” — areas for product investment, foundational technologies and related nontechnology trends (see Figure 1).
In analyzing the 18 profiles, Gartner has identified three overarching themes and trends:
- New technology acceleration is creating disruptive innovation opportunities for TSPs to augment and replace operational technology (OT).
- Data gravity drives data to be processed where and when it is valuable.
- The IoT market is increasingly being driven by applications, artificial intelligence (AI) and machine learning (ML).
2. Emerging Technologies and Trends Impact Radar:Artificial Intelligence, 2021
The latest AI innovations in 2021 are clustered around next-generation AI, productive and responsible AI, and AI-enabled applications. Product leaders must understand AI advancement timing and impact to effectively employ AI and gain competitive advantage.
- Advancements in core AI technologies — such as transformer-based language models, AI maker and teaching kits, or TinyML — are improving model accuracy, functionality and potential application.
- AI is being leveraged to increase organizations’ productivity via various data and analytics techniques to make sense of business and IoT data, as well as helping AI- enabled decisions to be not only more accurate but also explainable and ethical.
- AI techniques are being applied to a growing range of applications, such as delivery robots, smart spaces with real-time occupancy tracking or brain wearables, improving intelligence and advisory capabilities of solutions and disrupting existing business models.
- Future revolutionary advancements to AI will be enabled by multiple next-gen AI technologies, including composite AI, physics-informed AI, neuromorphic computing and bio-inspired algorithms.
Product leaders developing or expanding their portfolio of AI-enabled products and services must:
- Reduce development time of AI-enabled solutions by either using AI toolkits or joining AI marketplaces to acquire and collaborate on models, APIs, datasets and solution accelerators.
- Support customers in developing responsible AI by using human-centered AI principles and covering issues around transparency, interpretability, privacy and ethics.
- Ideate how to increase the capabilities and user experience for AI-enabled solutions in roadmap phases by integrating automation, advisory, creative and self-learning capabilities and selected adjacent technologies, like machine vision, emotion AI and multimodal UI.
- Assess the potential business opportunities with various next-gen AI technologies by analyzing impacts for specific industry use cases, piloting small research initiatives to build skills or partnering.
The Emerging Technologies and Trends Impact Radar is an analysis of the maturity, market momentum and influence of emerging technologies (see Figure 1). The innovations around AI technologies continue to emerge, and we have identified four overarching themes by analyzing 30 artificial intelligence (AI)-related technologies:
- Core AI technologies encompass foundational AI techniques, such as transformer- based language models, graph technologies that continue to deliver improvements to AI and further support of democratizing AI.
- Next-gen AI highlights the most promising emerging techniques, such as composite AI, physics-informed AI, neuromorphic computing or biology-inspired algorithms, which will support future revolutionary advancements to AI.
- Productive AI explores various data and analytics techniques to make sense of business and Internet of Things (IoT)/sensor data, as well as pushing AI-enabled decisions to be not only more accurate but also explainable and ethical. AI systems operating with various degrees of autonomy have to be trusted and their risks managed.
- AI-enabled applications (or AI solutions) and new use cases will expand to transform many business, social and human-machine interactions with conversational and multimodal user interfaces (UIs) around smart spaces, smart robots or autonomous vehicles.
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