Digital Technology Trends for 2022

Nobody could have foreseen that the pandemic would drive digital transformation at an unprecedented speed and scale. COVID-19 profoundly impacted our strategies and assumptions and made us rethink some of our best-laid plans almost immediately. It made governments, businesses, education institutions, healthcare providers, and government more dependent on technology to run their operations. This has led to companies shifting to new systems and processes, redesigning ways to deliver new digital customer experiences and resilient supply chains, and finding new digital methods to ensure business continuity. All this happened in a matter of months.

As you may have seen, digital transformation is now possible with increased connectivity and Cloud services. Cloud adoption (both hybrid and public) played an important role in making Cloud (and multi-clouds) the “new normal”. The Cloud has expanded its services to include the many technologies we will discuss below. Cloud platforms are now the most dominant technology category enabling digital transformation.

The technology trends for 2021 explore the future of the “top 10” technologies and their business applications and impact. Some of these technologies were introduced in 2010 but have evolved over the years to be more useful and widely used by both industries and enterprises.

The IoT Landscape will Transcend Industries with its Applications.

According to the IDC’s Worldwide Semiannual Internet of Things Spending Guide, IoT hardware and software spending is expected to increase by 12.6%, from $726 billion in 2019 to $1.1 trillion by 2023. IoT is essential to enable digital industrials (Industry 4.0) and smart connected systems such as smart buildings and smart infrastructure. Industrial IoT will allow connected product development, intelligent manufacturing, resilient supply chain, and connected service. This will create opportunities for new revenues and better experiences.

The growth of Connected systems has been fueled by the maturation of the IoT Ecosystem, which includes sensors, actuators, edge or gateways, Cloud and connectivity providers, IoT platforms, analytics and machine learning (ML). Both humans and machines will create valuable data that will remain untapped. These vast amounts and varieties of data can be used to generate insight and improve operations and new business models using AI/ML, the Cloud, and other edge technologies such as data engineering and data mining.

5G Will Revolutionize Industries

5G offers significantly faster speeds, with 100x more capacity than 4G and lower power consumption. It also provides massive connectivity for devices that have high availability and reliability. This disruptive technology has transformed experiences in public venues (e.g. stadiums) and enabled smart infrastructure, public safety and Industry 4.0. 5G is flexible and can be used to support a variety of devices, sensors and wearables. This allows for high-density and industrial-scale IoT.

Private 5G Networks are expected to drive enterprise transformation over the next five years, as they can be configured to meet each organization’s and place’s specific needs. Many industrial applications offer better latency and greater security. These opportunities include smart manufacturing, distribution centres and mining operations.

AI/ML will become a core part of business strategy.

McKinsey projects that Artificial Intelligence will contribute approximately $13 trillion to global economic output by 2030. Enterprises will likely use the different categories of AI technologies–computer vision, natural language, virtual assistants, and advanced machine learning–to improve their operations and customer experience. ML can potentially augment and, in some cases, replace human decision-making. AI will be a key part of any business strategy, with ML technology and ML-driven solutions becoming a core component.

AI is already used for personal assistants on smartphones, navigation apps, chatbots and e-mail spam filtering. AI’s evolution will allow for analyzing interactions between consumers and businesses, humans and devices, and connected devices. This will allow companies to identify patterns, uncover anomalies, make decisions and take action, thus enhancing organizational performance. Data-driven digital transformation requires a modern data estate. Innovation is responsible (ethical AI) should minimize risks such as inaccuracies or incomplete data, snags and inefficiencies in data flows, security breaches, and suboptimal models, algorithms and algorithms. To ensure optimal human-machine interactions, effective AI governance and ML Ops (like DevOps) will require continuous validation, monitoring, verification, and verification of AI-driven systems.

Edge Computing will increase IoT’s value.

The growing number of connected devices and the increasing computing power have resulted in large data volumes and a wide variety of data. Enterprises can only analyze a portion of IoT data. Edge computing and edge analytics can help businesses make better decisions by leveraging data closer to its source. Edge computing and analytics provide fast, almost real-time responses to changing conditions.

Gartner predicts that 75% of data processing will occur outside a traditional data centre or in the Cloud by 2025. Cloud computing will be able to take advantage of edge computing. Edge computing promises fast and real-time insights that can be acted on locally. 2020 was the year of edge computing. It will co-exist alongside the Cloud, network and end-point devices (and gateways) as cloud edge computing, mobile edge computing and IoT Edge.

Device security and management are critical prerequisites for deploying IoT applications at scale. Edge intelligence is the next frontier. AI and analytics will be available on or near IoT devices. Edge AI chips can process large data volumes quickly with low latency 5G connectivity.

Digital twins will make businesses more agile.

Initial advocates of digital twins were motivated by their ability to monitor, simulate, and streamline data across different devices. Digital twins can model equipment, processes, people, and other things. Recent developments in this technology have allowed industry leaders to connect with networks of intelligent Twins to create insightful models of factories, supply chains, product life cycles, smart cities, and other related areas.

Digital twins will be supported by reliable, comprehensive, compatible and reliable data. Intelligent twins can help businesses improve operations and detect and predict anomalies to maintain manufacturing processes and assets. They also enable greater autonomy. Organizations can adapt their strategies dynamically to new data, making them smarter and more agile.

Reality Tech will create a rich user experience.

As the line between digital and real continues to blur, augmented, Reality (AR) will revolutionize manufacturing, logistics and shopping. AR provides a new interface for frontline workers that allows them to work in an integrated way, using real-time data from analytics. Virtual reality (VR), which allows for the digital simulation of real-life scenarios, will be a more effective tool for training and education.

Google, Apple, Microsoft and Microsoft already offer their reality tech products for consumers and businesses. Innovative start-ups will use Cloud and 5G to transform AR-VR products and software into portable and scalable solutions. Well-funded start-ups will make the AR-VR device more portable and scalable over the next few years. They will also use 5G and the Cloud to transform the software landscape. There will be some issues to address, including privacy rights and security (of biometric information, device usage history, and the dangers from “reality” mods.

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