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Are You Using the Right XR Training for Work?

Ramon T. Llamas — Wed, 22 Apr 2026 04:00:00 GMT

This IDC Perspective examines the different types of XR training available on XR headsets. XR training has become one of the most popular use cases for XR in the workplace, providing workers with the information they need to complete a task. Training formats can vary in immersion (i.e., the degree to which a user is provided with virtual objects or placed into a virtual environment) and interaction (i.e., the degree to which a user is a passive consumer of or an active participant with the digital content) to address different training needs.

“XR training helps users develop the skills to complete a task,” said Ramon T. Llamas, research director with IDC’s XR Hardware and Interactive Software team. “By bringing information — including text, pictures, and videos — to the user’s eyes as they need it, workers can concentrate on the task at hand instead of looking to a manual or other resource. Just as there are different ways to build proficiency, there are different ways in which XR can help learners, whether it be with simple step-by-step instructions or a completely virtual environment to develop hands-on skills. Behind the scenes, AI can monitor progress and recommend next steps to take in their learning journey.”

IDC ProductScape: Worldwide Utilities Asset Performance Management, 2026

John Villali — Wed, 22 Apr 2026 04:00:00 GMT

This IDC ProductScape offers a comprehensive guide on the key functionalities within the worldwide utilities asset performance management space, featuring products from Emerson’s Aspen Technology, AVEVA, Baker Hughes, Bentley Systems, C3 AI, GE Vernova, Hitachi Energy, Honeywell, IBM, IFS, Octave (formerly Hexagon Asset Lifecycle Intelligence [ALI]), and SAP. The status of each functionality is categorized as fully supported, partially supported, partner provided, road map, or not supported, aiding technology purchasers in quickly identifying which vendors align with their changing requirements.

"In the Loop But Not in the Weeds": Organizational Change and the Path to AI ROI

Grace Trinidad — Tue, 21 Apr 2026 04:00:00 GMT

Artificial intelligence will reshape enterprise operations, much like automation did in healthcare records, financial markets, aviation systems, and industrial manufacturing. These historical transitions show that automation rarely delivers immediate productivity gains; instead, organizations pass through phases of experimentation, disruption, stabilization, and eventual transformation. Therefore, AI should be treated not as a productivity tool add-on but as a shift in how decisions are made. Leaders must redesign workflows, governance, and human roles while maintaining human oversight of automated systems. Organizations that integrate AI into decision processes — and build the infrastructure and operating norms to supervise it — will capture far greater long-term value than those that simply layer AI tools onto existing workflows.

"Organizations looking for immediate ROI from AI are treating it like software. It isn't. AI is closer to autopilot in aviation or algorithmic trading in financial markets: a system that participates in decisions. Those transitions did not pay off simply because the technology was installed. They paid off because institutions rebuilt workflows, governance, and human roles around automation." — Research Director Grace Trinidad, AI Security & Trust, IDC

Digital and AI Business Scorecard in Asia/Pacific, 2026: Empowering Enterprises to Achieve Business Outcomes

Xiao Liu — Tue, 21 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Presentation provides IDC's Digital and AI Business Scorecard analysis, based on survey data from 470 senior IT and business leaders from the Asia/Pacific region. The Digital and AI Business Scorecard evaluates the correlation between the levels of business outcome improvements and levels of digital business model, data and AI, operational processes, and organizational capabilities to calculate an overall status assessment and then differentiates leading enterprises from their peers based on these capabilities and as overall digital businesses.

Across Asia/Pacific, AI is moving from boardroom ambition to business imperative. Organizations are pivotally shifting from experimental AI to AI-fueled business models, with the aspiration for agentic AI and autonomous operations rising sharply. However, a critical gap persists between strategic intent and operational reality.

"This year's Scorecard analysis for Asia/Pacific reveals a distinctive regional dynamic," says Xiao Liu, research manager, AI-Fueled Business Strategies at IDC. "Organizations are investing confidently in digital and AI business models and platforms, yet the data infrastructure and operational processes needed to back those models up are lagging behind. Until that inversion is corrected, digital revenue ambitions will outrun execution reality."

Digital and AI Business Scorecard in EMEA, 2026: Empowering Enterprises to Achieve Business Outcomes

Martina Longo — Tue, 21 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Presentation provides IDC’s Digital and AI Business Scorecard analysis for the EMEA region, based on survey data from 749 senior IT and business leaders. The Digital and AI Business Scorecard assesses organizations’ maturity levels across digital business models, data and AI, operational processes, and organizational capabilities. It also examines how these maturity stages align with business outcome improvements to produce an overall status assessment. It then differentiates leading enterprises from their peers based on these capabilities and as digital businesses. This document also provides a deep dive into the characteristics and behaviors that differentiate leading organizations from those lagging in their AI-fueled transformation journeys.

AI is driving a new wave of business reinvention across EMEA, with organizations moving beyond traditional digital transformation to redesign business and operating models around AI — reshaping processes, accelerating decision‑making, and unlocking new sources of value. However, many still struggle to measure AI’s business impact, balance short‑term efficiency gains with long‑term growth, and establish clear ROI frameworks and use‑case prioritization.

The largest capability gap between leading and nascent organizations is in digital business models, indicating that leaders are far more effective at converting digital and AI capabilities into direct revenue outcomes. On the other hand, all EMEA organizations are struggling to transform their organizational structures, as AI adoption requires robust change management initiatives and large‑scale upskilling and reskilling programs.

From AI Pilots to Transformation: IDC Learnings from 2025 Services Vendor Events and IT Buyer Discussions on AI

Peter Marston — Tue, 21 Apr 2026 04:00:00 GMT

This IDC Perspective reviews how organizations are moving AI initiatives from pilot to production, highlighting key drivers the organizations had, benefits they achieved, and ongoing challenges they continue to overcome. Although early adopters have reported measurable gains, challenges persist around data quality, governance, talent, and responsible AI. This report advises buyers to focus on outcome-based value, industry-specific expertise, and robust change management to maximize AI benefits and ensure sustainable, responsible adoption as AI scales across enterprise environments.

"As organizations race from AI pilots to production, the true challenge is not technology but mastering data, governance, and trust to unlock sustainable business value," explains Pete Marston, senior research director, IDC.

Software Rationalization, Modernization, and Transformation During the Movement to Agents as Apps

Mickey North Rizza — Tue, 21 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Presentation presents new methods for reviewing software technology in the agentic era. The agentic era of software has arrived. This comprehensive, forward-looking guide will help organizations using enterprise software and/or AI agents to strategize and plan their moves to agents as apps. It is meant as a guide to help small, medium-sized, and large businesses of all types to consider new methodologies as they review their software portfolio and agents.

Every organization has a different set of software, agents, and requirements, which must be taken into context as the organization strengthens its technology and its agentic portfolio.

The Complexity Theory of IT: Governing Digital Operations at Machine Scale

Shannon Kalvar — Tue, 21 Apr 2026 04:00:00 GMT

As digital systems become central to enterprise operations, traditional coordination models are overwhelmed by escalating complexity. Observability and AIOps enhance visibility and response, but sustainable progress requires leaders to redesign governance, clarify human-machine boundaries, and shift operational focus from restoration to future-oriented decision making. IT's role is evolving from productivity enabler to governance substrate, demanding new strategies for resilience, accountability, and business performance in machine-scale environments.

"When machine-scale complexity outpaces human-scale governance, the future of business resilience depends not just on smarter technology, but on leaders who can redraw the boundaries between human judgment and automated action," said Shannon Kalvar, research director, Enterprise Systems Management, Enterprise Client Platforms, Observability, and AIOps at IDC.

Industry Ecosystems and Business Networks Study: Overall B2B Collaboration/Networks Findings

Reid Paquin — Sun, 19 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Presentation highlights the B2B collaboration/networks findings from IDC's August 2025 Worldwide Industry Ecosystems and Business Networks Survey. IDC Manufacturing Insights defines a multi-enterprise supply chain commerce network as any platform that both facilitates the exchange of information and enables transactions among disparate parties pertaining to the supply chain or to supply chain processes.

As supply chain disruption continues to be an ongoing challenge, mitigating supply chain risk is top of mind. IDC's supply chain research has drilled further into the topic and showed that the top steps companies need to take to mitigate risk center around visibility, agility, supply diversification, and collaboration.

Owing to these needs, multi-enterprise supply chain commerce networks are becoming a critical element to meet current and future supply chain needs. While the multi-enterprise network is not a magic balm for these issues, it is a modern approach to improve visibility and collaboration in a comprehensive way and an opportunity to drive better overall supply chain performance.

This Tech Buyer Presentation (shared with clients in March 2026) focuses on the overall results from over 1,000 respondents across 8 industry segments and 16 countries across the globe.

Workforce Transformation — The Human Dimension of Physical AI

Sarah Lee, Gunjan Bassi — Sun, 19 Apr 2026 04:00:00 GMT

This IDC Perspective explores the workforce implications of physical AI and AI agents on the shop floor workforce, focusing on the emergence of hybrid roles that blend operational knowledge with digital and automation capabilities. It outlines how manufacturers must adapt roles and skills to enable effective human-machine collaboration.

"As physical AI reshapes the shop floor, the future belongs to those who see workforce transformation as the true engine of innovation, says Sarah Lee, research director, Manufacturing Insights, IDC. "Organizations that focus solely on deploying advanced technologies without equally investing in their people will struggle to realize meaningful returns. The real differentiator lies in how effectively manufacturers equip their workforce with the skills, tools, and frameworks needed to collaborate with intelligent systems, adapt to new roles, and make informed decisions. Those that embed workforce strategy into their AI initiatives from the outset will not only accelerate adoption but also build the agility and resilience required to compete in increasingly automated and dynamic production environments."

"Physical AI is transforming work at its core, laying the groundwork for entirely new categories of roles that will blend technical, operational, and analytical skills in ways traditional job structures were never designed to support," says Gunjan Bassi, research manager, IDC Manufacturing Insights, IDC. "Workforce transformation is emerging as a critical enabler of that value, and it starts with developing human capability alongside the technology, not after it."