Gartner Identifies Key Emerging Technologies Spurring Innovation

Engineering trust, accelerating growth and sculpting change are the three overarching trends on the Gartner, Inc. Hype Cycle for Emerging Technologies, 2021 that will drive organizations to explore emerging technologies such as nonfungible tokens (NFT), sovereign cloud, data fabric, generative AI and composable networks to help secure competitive advantage.

"Technology innovation is a key enabler of competitive differentiation and is the catalyst for transforming many industries. Breakthrough technologies are continually appearing, challenging even the most innovative organizations to keep up," said Brian Burke, Research VP at Gartner. "Leading organizations will lean on the emerging technologies in this year's Hype Cycle to build trust and new growth opportunities against a background of continued strategic change and economic uncertainty."

The Hype Cycle for Emerging Technologies is unique among most Gartner Hype Cycles because it distils insights from more than 1,500 technologies into a succinct set of "must know" emerging technologies and trends that show promise in delivering a high degree of competitive advantage over the next five to 10 years.

"As organizations continue their focus on digital business transformation, they must accelerate change and cut through the hype surrounding emerging technologies," said Melissa Davis, Research VP at Gartner.

"This Hype Cycle provides a high-level view of important emerging trends that organizations must track, as well as the specific technologies that must be monitored through the themes of Trust, Growth and Change," said Philip Dawson, Research VP at Gartner.

Three Themes of Emerging Technology Trends

Engineering Trust: Trust demands security and reliability. However, it can also extend to building innovations as a resilient core and foundation for IT to deliver business value. This foundation must consist of engineered, repeatable, trusted, proven and scalable working practices and innovations.

For example, the market for digital and cloud technology and services is currently dominated by US and Asian providers. As a result, many European companies store their data in these regions, creating political uneasiness as well as concerns about retaining data control and complying with local regulations. Countries can engage a sovereign cloud to achieve digital and data sovereignty, which will in turn provide legal requirements to apply data protection controls, residency requirements, protectionism and intelligence gathering.

The technologies to watch to engineer trust are sovereign cloud, NFT, machine-readable legislation, decentralized identity, decentralized finance, homomorphic encryption, active metadata management, data fabric, real-time incident center and employee communications applications.

Accelerating Growth: After the trusted core business is established, recovery and growth can happen. Organizations should balance technology risk with the appetite for business risk to ensure near-term objectives are attainable. Once the innovation-led core is scaling, accelerated growth extends delivery and value.

For example, generative AI is an emerging technology that the pharmaceutical industry is using to help reduce costs and time in drug discovery. Gartner predicts that by 2025, more than 30% of new drugs and materials will be systematically discovered using generative AI techniques. Generative AI will not only augment and accelerate design in many fields; it also has the potential to "invent" novel designs that humans may have otherwise missed.

To accelerate growth, the following technologies should be explored: multiexperience, industry cloud, AI-driven innovation, quantum machine learning (ML), generative AI and digital humans.

Sculpting Change: Change is traditionally disruptive and often is tied to chaos, but organizations can use innovations to sculpt change and bring order to chaos. The art is to anticipate and auto-tune to the needs of change.

For example, composable business applications enable a better match of application experiences to a changing, operational business context. Composable business, founded on composable application technology and built with composable thinking, positions organizations to recognize and exploit business opportunities, respond to unexpected disruptions, and meet customers' changing demands at their pace, retaining their loyalty.

Organizations looking to sculpt change should consider composable applications, composable networks, AI-augmented design, AI-augmented software engineering, physics-informed AI, influence engineering, digital platform conductor tools, named data networking and self-integrating applications.

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Gartner Identifies Key Emerging Technologies Spurring Innovation

Engineering trust, accelerating growth and sculpting change are the three overarching trends on the Gartner, Inc. Hype Cycle for Emerging Technologies, 2021 that will drive organizations to explore emerging technologies such as nonfungible tokens (NFT), sovereign cloud, data fabric, generative AI and composable networks to help secure competitive advantage.

"Technology innovation is a key enabler of competitive differentiation and is the catalyst for transforming many industries. Breakthrough technologies are continually appearing, challenging even the most innovative organizations to keep up," said Brian Burke, Research VP at Gartner. "Leading organizations will lean on the emerging technologies in this year's Hype Cycle to build trust and new growth opportunities against a background of continued strategic change and economic uncertainty."

The Hype Cycle for Emerging Technologies is unique among most Gartner Hype Cycles because it distils insights from more than 1,500 technologies into a succinct set of "must know" emerging technologies and trends that show promise in delivering a high degree of competitive advantage over the next five to 10 years.

"As organizations continue their focus on digital business transformation, they must accelerate change and cut through the hype surrounding emerging technologies," said Melissa Davis, Research VP at Gartner.

"This Hype Cycle provides a high-level view of important emerging trends that organizations must track, as well as the specific technologies that must be monitored through the themes of Trust, Growth and Change," said Philip Dawson, Research VP at Gartner.

Three Themes of Emerging Technology Trends

Engineering Trust: Trust demands security and reliability. However, it can also extend to building innovations as a resilient core and foundation for IT to deliver business value. This foundation must consist of engineered, repeatable, trusted, proven and scalable working practices and innovations.

For example, the market for digital and cloud technology and services is currently dominated by US and Asian providers. As a result, many European companies store their data in these regions, creating political uneasiness as well as concerns about retaining data control and complying with local regulations. Countries can engage a sovereign cloud to achieve digital and data sovereignty, which will in turn provide legal requirements to apply data protection controls, residency requirements, protectionism and intelligence gathering.

The technologies to watch to engineer trust are sovereign cloud, NFT, machine-readable legislation, decentralized identity, decentralized finance, homomorphic encryption, active metadata management, data fabric, real-time incident center and employee communications applications.

Accelerating Growth: After the trusted core business is established, recovery and growth can happen. Organizations should balance technology risk with the appetite for business risk to ensure near-term objectives are attainable. Once the innovation-led core is scaling, accelerated growth extends delivery and value.

For example, generative AI is an emerging technology that the pharmaceutical industry is using to help reduce costs and time in drug discovery. Gartner predicts that by 2025, more than 30% of new drugs and materials will be systematically discovered using generative AI techniques. Generative AI will not only augment and accelerate design in many fields; it also has the potential to "invent" novel designs that humans may have otherwise missed.

To accelerate growth, the following technologies should be explored: multiexperience, industry cloud, AI-driven innovation, quantum machine learning (ML), generative AI and digital humans.

Sculpting Change: Change is traditionally disruptive and often is tied to chaos, but organizations can use innovations to sculpt change and bring order to chaos. The art is to anticipate and auto-tune to the needs of change.

For example, composable business applications enable a better match of application experiences to a changing, operational business context. Composable business, founded on composable application technology and built with composable thinking, positions organizations to recognize and exploit business opportunities, respond to unexpected disruptions, and meet customers' changing demands at their pace, retaining their loyalty.

Organizations looking to sculpt change should consider composable applications, composable networks, AI-augmented design, AI-augmented software engineering, physics-informed AI, influence engineering, digital platform conductor tools, named data networking and self-integrating applications.

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Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

The Hidden Data Engineering Work Required to Make Enterprise AI Viable

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

Why AI Is the Differentiator for Operationally Resilient Organizations

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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