The top strategic technology trends for 2021 are:
Internet of Behaviors
The internet of behaviors (IoB) is emerging as many technologies capture and use the “digital dust” of peoples’ daily lives. The IoB combines existing technologies that focus on the individual directly – facial recognition, location tracking, and big data, for example – and connects the resulting data to associated behavioral events, such as cash purchases or device usage. Organizations use the data to influence human behavior. For example, to monitor compliance with health protocols during the ongoing pandemic, organizations might leverage IoB via computer vision to see whether employees are wearing masks or via thermal imaging to identify those with a fever.
Gartner predicts that by year-end 2025, over half of the world’s population will be subject to at least one IoB program, whether it be commercial or governmental. While the IoB is technically possible, there will be extensive ethical and societal debates about the different approaches employed to affect behavior.
Last year, Gartner introduced multiexperience as a top strategic technology trend and is taking it one step further this year with total experience (TX), a strategy that connects multiexperience with customer, employee and user experience disciplines. Organizations need a TX strategy as interactions become more mobile, virtual, and distributed, mainly due to COVID-19. TX strives to improve the experiences of multiple constituents to achieve a transformed business outcome. These intersected experiences are key moments for businesses recovering from the pandemic that are looking to achieve differentiation via capitalizing on new experiential disruptors.
CIOs in every region face more privacy and noncompliance risks than ever before as global data protection legislation matures. Unlike common data-at-rest security controls, privacy-enhancing computation protects data in use while maintaining secrecy or privacy.
Gartner believes that by 2025, half of large organizations will implement privacy-enhancing computation for processing data in untrusted environments and multi-party data analytics use cases. Organizations should start identifying candidates for privacy-enhancing computation by assessing data processing activities that require transfers of personal data, data monetization, fraud analytics and other use cases for highly sensitive data.
Distributed cloud is the distribution of public cloud services to different physical locations, while the operation, governance, and evolution of the services remain the responsibility of the public cloud provider. It provides a nimble environment for organizational scenarios with low-latency, data cost-reduction needs and data residency requirements. It also addresses the need for customers to have cloud computing resources closer to the physical location where data and business activities happen. By 2025, most cloud service platforms will provide at least some distributed cloud services that execute at the point of need.
Anywhere operations refers to an IT operating model designed to support customers everywhere, enable employees everywhere and manage the deployment of business services across distributed infrastructures. It is more than simply working from home or interacting with customers virtually – it also delivers unique value-add experiences across five core areas: Collaboration and productivity, secure remote access, cloud and edge infrastructure, quantification of the digital experience, and automation to support remote operations.
By the end of 2023, 40 percent of organizations will have applied anywhere operations to deliver optimized and blended virtual and physical customer and employee experiences.
The cybersecurity mesh enables anyone to access any digital asset securely, no matter where the asset or person is located. It decouples policy enforcement from policy decision-making via a cloud delivery model and allows identity to become the security perimeter. By 2025, the cybersecurity mesh will support over half of digital access control requests.
Intelligent composable business
An intelligent composable business radically re-engineers decision-making by accessing better information and responding more nimbly to it. For example, machines will enhance decision-making in the future, enabled by a rich fabric of data and insights. Intelligent composable business will pave the way for redesigned digital business moments, new business models, autonomous operations, and new products, services, and channels.
Gartner research shows only 53 percent of projects make it from artificial intelligence (AI) prototypes to production. CIOs and IT leaders find it hard to scale AI projects because they lack the tools to create and manage a production-grade AI pipeline. The road to AI production means turning to AI engineering, a discipline focused on the governance and lifecycle management of a wide range of operationalized AI and decision models, such as machine learning or knowledge graphs.
AI engineering stands on three core pillars: DataOps, ModelOps, and DevOps. A robust AI engineering strategy will facilitate the performance, scalability, interpretability, and reliability of AI models while delivering the full value of AI investments.
Business-driven hyperautomation is a disciplined approach that organizations use to rapidly identify, vet, and automate as many approved business and IT processes as possible. Although hyperautomation has been trending at an unrelenting pace for the past few years, the pandemic has heightened demand with the sudden requirement for everything to be “Digital First.” The backlog of requests from business stakeholders has prompted more than 70 percent of commercial organizations to undertake dozens of hyperautomation initiatives as a result.