Shulou(Shulou.com)11/24 Report--

Another year of tech hype.

Gartner recently published the Emerging Technology Maturity Curve 2022. What "new tricks" did Gartner put together this year?

Emerging Technology Trends 2022 identifies 25 emerging technologies to understand, with three main themes:

1. Evolution of immersive experience

2. Accelerate artificial intelligence automation

3. Optimize technical talent delivery

Gartner's Emerging Technology Maturity Index 2022 contains 25 "must-know" innovations to drive competitive differentiation and efficiency.

Only a few are expected to be mainstream adoption within two years, and many take 10 years or more to be adopted.

Deploying embryonic technologies also means greater risk, but there are potential benefits for early adopters.

"These technologies are in their early stages, some of them embryonic, and there is still a lot of uncertainty about how they will evolve in the future," said Melissa Davis, vice president of analyst at Gartner. "

Theme 1: Evolving/Expanding Immersive Experiences The benefit of these technologies is that they give individuals more control over identity and data and extend the experience to virtual places and ecosystems that can be integrated with digital currency. These technologies also offer new ways to reach customers to open up new revenue streams.

Customer digital twins (DToC) are dynamic virtual representations of customers that can simulate, learn, and predict behavior. It can be used to modify and enhance customer experiences (CX) and support new digital jobs, products, services and opportunities. DToC takes 5 to 10 years for mainstream adoption and will have a significant impact on organizations.

Other key technologies in immersive experiences include:

Decentralized Identity (DCI) allows entities (usually users) to control their digital identities using blockchain or other distributed ledger technology (DLT) and digital wallets.

A digital human is an AI-driven, interactive representation with some of the characteristics, personalities, knowledge, and ways of thinking of a human.

Internal talent markets match internal and, in some cases, temporary employee talent pools with time-limited projects and job opportunities without recruiting staff involvement.

Meta Universe is a collective virtual 3D shared space created by the fusion of virtual augmented physics and digital reality. The meta-universe is persistent and provides enhanced immersive experiences.

A non-homogeneous token (NFT) is a uniquely programmable blockchain-based digital item that publicly proves ownership of a digital asset (such as digital art or music) or tokenized physical asset (such as a house, car or document).

SuperApp is a composite mobile app built as a platform that provides modular microapps that users can activate for a personalized app experience.

Web3 is a new technology stack for developing decentralized Web applications that give users control over their identity and data.

Theme 2: Accelerating AI Automation Expanding AI adoption is a key way to develop products, services and solutions. This means accelerating the creation of specialized AI models, applying AI to the development and training of models, and deploying them into the delivery of products, services, and solutions.

Autonomous systems are examples of AI automated acceleration. Autonomous systems are self-managing physical or software systems that perform domain-bound tasks with three basic characteristics: autonomy, learning, and agency. Autonomous systems can assist when traditional AI techniques fail to achieve business adaptability, flexibility, and agility. Autonomous systems take 5 to 10 years to be adopted by mainstream.

Other key technologies to accelerate AI automation include:

Causal artificial intelligence (AI) identifies and exploits causal relationships, breaking through predictive models based on correlations and moving AI systems toward recommending actions more efficiently and autonomously.

Base models are models based on Transformer architectures, such as large language models, which embody a deep neural network architecture that computes numerical representations of text in context, emphasizing sequences of words.

Generative design AI or AI-enhanced design is the use of AI, machine learning (ML) and natural language processing (NLP) techniques to automatically generate and develop user flow, screen design, content and presentation layer code for digital products.

Machine learning code generation tools include cloud-hosted ML models that plug into professional developer integrated development environments (IDEs), which are extensions that provide suggested code based on natural language descriptions or partial code snippets.

Theme 3: Optimizing Tech Delivery These technologies focus on key elements of building a digital business: the product, service or solution developer community and the platforms they use. These technologies provide feedback and insight to optimize and accelerate the delivery of products, services and solutions, and improve the sustainability of business operations.

Cloud data ecosystems embody optimized technician delivery. They provide a unified data management environment capable of supporting all data workloads from exploratory data science to production data warehouses. Cloud data ecosystems provide simplified delivery and comprehensive functionality that is easy to deploy, optimize, and maintain. It will take two to five years for them to be mainstream.

Other key technologies to optimize technician delivery include:

Enhanced Agile Finance (FinOps) automates traditional DevOps concepts such as agility, continuous integration and deployment, and end-user feedback on financial governance, budget planning, and cost optimization efforts by applying AI and machine learning (ML) practices.

Cloud sustainability is the use of cloud services to achieve sustainability benefits in economic, environmental and social systems.

Compute Storage (CS) offloads host processing from the main memory of the central processing unit (CPU) to storage devices.

Network Security Mesh Architecture (CSMA) is an emerging approach to building combinable distributed security controls to improve overall security efficiency.

Data observability is the ability to understand the health of an organization's data environment, data pipeline, and data infrastructure through continuous monitoring, tracking, alerting, analysis, and troubleshooting events.

Dynamic Risk Governance (DRG) is a new approach to the critical task of defining roles and responsibilities for risk management. DRG tailors risk governance appropriately for each risk, enabling organizations to better manage risk and reduce assurance costs.

Industry cloud platforms leverage underlying SaaS, PaaS, and IaaS services to deliver industry-relevant packaged business and technology capabilities for identified verticals and consolidate them into one product.

Minimum Viable Architecture (MVA) is a standardized framework that product teams use to ensure timely, compliant development and iteration of products.

Observability-driven development (ODD) is a software engineering practice that provides fine-grained visibility and context for system state and behavior by designing systems to be observable.

Open Telemetry is a collection of specifications, tools, application programming interfaces (APIs), and software development kits (SDKs) used to describe and support the implementation of open source instrumentation and observability frameworks for software.

Platform Engineering is the discipline of building and operating self-serving internal developer platforms (IDPs) for software delivery and lifecycle management.

Gartner's 2021-2023 Emerging Technology Roadmap for Large Enterprises

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