According to the Gartner company, in the next two to ten years, the technologies may offer immersive experiences, rapid AI automation, and optimized technical delivery. Innovative product development idea with researcher focusing on cutting-edge technologies, IoT, robotic process automation, big data, and artificial intelligence-based digital disruption.
The report focuses on promising emerging technologies and compiles key insights from the more than 2,000 technologies that Gartner researches each year to turn it all into a concise set of “must-have” emerging technologies and trends. These technologies and trends have the potential to provide companies with a high degree of competitive advantage over the next two to ten years.
“All these technologies are at an early stage, but some are at an embryonic stage, and great uncertainty exists about how they will evolve. The embryonic technologies present greater risks for deployment but potentially greater benefits for early adopters, which differentiates them from Gartner’s top strategic technology trends,” says Melissa Davis, VP Analyst at Gartner.
Businesses could be transformed by new technologies, but technology innovation executives must scale digital skills and develop resilience in a setting with dwindling resources. In order to drive change with innovations that offer competitive difference and efficiency, organizations must cut through the noise around emerging technology.
There are 25 technologies shown on the graph. The technologies are broken down into 3 sets:
1. Evolving/expanding immersive experiences
2. Accelerated AI automation
3. Optimized technology delivery
Evolving/expanding immersive experiences
Immersive experiences are the trend of the future for digital experiences. Such experiences are supported by a number of new technologies, including settings and ecosystems of users and customers, dynamic virtual mediums of expression, and new user engagement strategies. These technologies let users to maintain identity and data control, as well as build virtual ecosystems that can work with digital currencies. These technologies aid in expanding or creating new revenue streams by assisting in reaching customers in new ways.
Digital twin of the customer (DtoC), Decentralized identity (DCI), digital people, internal staff marketplaces, metaconsciousness, NFT, superapps, and Web3.0 are among the technologies to keep an eye out for that offer a developing and extending immersive experience.
Following technologies are re among the technologies to keep an eye out for, that offer a developing and extending immersive experience.:
- Decentralized identification (DCI) – Distributed ledger technologies (DLT) and Digital wallets etc are used in decentralized identification (DCI), which gives the subject—typically a human user—control over their own digital identity.
- AI-driven digital presonas – representations of people that share some of their traits, personalities, skills, and ways of thinking with real people.
- Internal talent marketplaces – use a pool of contingent workers and internal employees to find candidates on their own for various projects and job openings.
- Metaverse – A collective 3D virtual environment made possible by the merger of virtually augmented physical world and digital reality is known as a meta virtual universe. Because the metavieworld is eternal, it offers a more complete immersive environment
- Non-fungible token (NFT) – a unique programmable blockchain-based digital element that publicly confirms ownership of digital assets, such as digital art or music, or physical assets that are tokenized, such as homes, cars or documents.
- Superapps – is a composite mobile app designed as a platform to deliver modular micro-applications that users can activate to personalize apps.
- Web3 – is a new technology stack for developing decentralized web applications that allow users to control their identity and data.
Accelerated AI automation
The adoption of AI as an integral part of products, services, and solutions is expanding. This accelerates the creation of specialized AI models that can be used to automate the development, training, and deployment of AI models. As a result, predictions and decisions will become more accurate, and expected benefits can be delivered faster. AI automation will refocus the role of humans in AI development. The role of humans will predominantly be to consume, evaluate, and supervise.
Technologies that facilitate accelerated AI automation:
- Causal artificial intelligence (AI) – Technologies contributing to accelerated AI automation: autonomous systems, causal AI, baseline models, AI for generative design, and machine learning tools for code generation.
- Foundation models – In order to move beyond correlation-based predictive models and toward AI systems that can prescribe activities more effectively and operate more autonomously, causal artificial intelligence (AI) seeks out and makes use of cause-and-effect linkages.
- Generative design AI – Large language models, which represent a particular type of deep neural network architecture that computes a numerical representation of text in the context of surrounding words, emphasize word sequences, are examples of transformer architecture-based foundation models.
- Machine learning code generation – Cloud-hosted machine learning models that interact with professional developers’ integrated development environments (IDEs) are examples of machine learning code generation tools. These extensions offer suggested code based on either natural language descriptions or partial code fragments.
Optimized technology delivery
Successful digital businesses are created, not bought. A set of new technologies focus on the communities that create products, services and solutions and the platforms they use. These technologies provide feedback and insights that optimize and accelerate the delivery of products, services and solutions and improve the sustainability of business operations.
Critical technologies that optimize technologists’ work are Augmented FinOps, Cloud sustainability, computational storage, Cybersecurity mesh architecture (CSMA), data observability, dynamic risk management, industry cloud platforms, minimally viable architecture, observability-driven development (ODD), OpenTelemetry and platform design.
- Augmented FinOps – Through the use of artificial intelligence (AI) and machine learning (ML) techniques, augmented finops automates classic devops ideas like agility, continuous integration and deployment, and end-user feedback to financial governance, budgeting, and cost optimization activities.
- Cloud sustainability – The use of cloud services to promote sustainability within economic, environmental, and social systems is known as “cloud sustainability.”
- Computational storage (CS) – A storage device receives host processing that has been offloaded from the CPU’s main memory through computational storage (CS).
- Cybersecurity mesh architecture (CSMA) – An innovative method for designing composable, distributed security controls that enhance overall security effectiveness is called cybersecurity mesh architecture (CSMA).
- Data observability – is the capacity to continually monitor, track, alert, analyze, and troubleshoot issues in order to understand the state of an organization’s data landscape, data pipelines, and data infrastructure.
The 2022 Gartner Hype Cycle includes 25 innovations that need to be known about to ensure competitive differentiation and efficiency. Only a few are likely to be massively diffused in as little as two years; many will take 10 years or more. The embryonic nature of these technologies makes their adoption more risky, but the benefits are potentially greater for those who adopt them early.