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IDC ProductScape: Worldwide Corporate Client Life-Cycle Management for Financial Services, 2026 — Technology Supplier Solution Functionality

Sam Abadir — Thu, 15 Oct 2026 04:00:00 GMT

This IDC ProductScape offers a comprehensive guide on the key functionalities of client life-cycle management for financial services, featuring products from Fenergo, NICE Actimize, Pega, Avaloq, Delta Capita, and EdgeVerve. 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.

Salesforce's Dreamforce 2026: Scaling the Agentic Enterprise — A Deep-Dive on AI for Business

Andrea Siviero — Thu, 15 Oct 2026 04:00:00 GMT

This IDC Perspective focuses on Salesforce's AI strategy for business, looking at what the event means for business units building AI-fueled strategies: closing the execution gap, proving business impact, and driving transformation. Dreamforce 2026 positioned Salesforce's integrated, headless stack as the trusted business layer for AI. IDC's takeaway: Value will depend less on the technology than on closing the execution gap.

"Models are generic and probabilistic, while enterprise systems must be deterministic. Salesforce's metadata, permissions, and business logic supply the context in between, and that integration can play a key differentiating role," said Andrea Siviero, research vice president at IDC. "But with 62% of organizations still at an early stage of AI maturity, execution is the challenge, and Salesforce's own customer zero experience is a practical place to start."

Wearables and Connnected Devices: From Fitness Trend to Health Infrastructure

Silvia Piai — Thu, 15 Oct 2026 04:00:00 GMT

This IDC Tech Buyer Presentation examines how consumers are adopting wearables, remote monitoring, and mood-tracking devices, and what that behavior means for providers and medtech/digital health vendors navigating an increasingly connected consumer health journey.

Wearables and remote health monitoring (RHM) are moving beyond the adoption question. Comfort with device-enabled care is now comparable with other virtual-care modalities, and health-related wearable use is established rather than niche. The next challenge is what happens after adoption. Remote monitoring is used routinely, often weekly, yet much of the data still sits outside clinical workflows. Satisfaction depends on control, fit with daily life, and clear information. Consumers are also broadly willing to share device data for care when the value exchange is clear.

Drawing on IDC's 2026 Connected Health Consumer Survey, this presentation examines what these shifts mean for providers, medtech, and digital health vendors as connected care becomes a more continuous part of individual health journeys and clinical care.

"Device adoption is only the first step," said Silvia Piai, research director, Connected Health and Medical Devices Digital Strategies at IDC. "The real opportunity is to make the data consumers generate useful in care by turning routine monitoring into relevant insight, clinical action, and sustained engagement. That is where adoption starts to translate into value."

Four Operating Logics: Why the Same Arguments Keep Coming Back

Shannon Kalvar, Matthew Flug, Archana Venkatraman — Wed, 14 Oct 2026 04:00:00 GMT

This IDC Perspective sets out four operating logics that coexist inside most enterprise IT organizations: the custodial, procedural, flow, and bounds logics of what good operations is. Each formed under conditions that have not been withdrawn, and all four share a vocabulary, which is why disagreements about principle present themselves as colleagues being unreasonable about something obvious. The document explains why each logic persists, describes what a composed organization requires to function, and gives IT leaders three readings whose pattern of divergence indicates which of four capabilities to build first.

"Every one of the four operating logics answers a question the enterprise still faces," said Shannon Kalvar, senior research director, Enterprise Systems Management, Observability, and AIOps at IDC. "The estate outlives the strategy that bought it, committed money resists redirection, and suppliers set the timing of change. An enterprise funding a program to advance whichever group looks behind is paying to intensify the argument it is trying to end."

Generative AI and Agentic AI in the Grid Control Room — From Operator Assistance to Workflow Orchestration

Jean-François Segalotto — Wed, 14 Oct 2026 04:00:00 GMT

This IDC Tech Buyer Presentation examines how generative AI (GenAI) and agentic AI are beginning to reshape the electric utility grid control room, from operator support and information access toward more advanced decision support, workflow orchestration, and bounded task execution.

The presentation explores how the earliest and most mature use cases focus on reducing information friction and cognitive load. These include operational knowledge copilots, conversational access to live grid data, operational summarization, alarm and event triage, and cross-domain investigation.

It then examines how AI is moving further into the operational workflow through proactive foresight, conversational what-if analysis, corrective action recommendations, and the generation or validation of operational artifacts. These capabilities increasingly combine GenAI interfaces and agentic reasoning with established forecasting, simulation, optimization, and grid analysis tools.

The presentation also considers the emerging role of agentic AI in orchestrating trusted applications and executing bounded workflow steps. It highlights that the near-term opportunity is less about delegating control authority and more about increasing operator leverage by reducing effort, compressing multistep workflows, and accelerating decision-making, while fully autonomous AI-directed grid control remains a longer-term proposition.

It concludes with recommendations for utilities to prioritize use cases that deliver measurable operator value, keep grid calculations and control logic anchored in trusted domain applications, establish clear governance around permissions and human approval, and build reusable data, semantic, integration, and orchestration foundations that can support progressively more agentic workflows over time.

IDC MaturityScape Benchmark: AI-Fueled Organization in Canada, 2026

Nigel Wallis, Claudia Medina — Wed, 14 Oct 2026 04:00:00 GMT

Organizations in Canada post a marginally lower overall AI maturity score than the worldwide average (mean of 2.42 versus 2.43), with governance and people tied as the most advanced of the four dimensions (2.47 each), while technology, at 2.34, remains the least mature, matching the global pattern of persistent data and platform readiness gaps.

This is consistent with Canada's historically risk-averse business posture toward emerging technology: Canadian buyers typically require evidence of governance rigor and risk transparency before they will engage on ROI or business outcome arguments, giving organizations in Canada a strong incentive to mature AI governance in step with, rather than behind, their strategy and technology investments.

This IDC study presents results from IDC's MaturityScape Benchmark AI Survey, released worldwide in May 2026.

"Canadian organizations have made real progress on AI governance and people readiness, which are running tied as the most mature dimensions in this year's benchmark. But that progress has largely been built bottom-up, project by project, rather than against an enterprise-wide road map, and technology remains the clear laggard," says Nigel Wallis, research VP, Americas Industry Insights. "As agentic AI moves from pilots into production, organizations that have not closed their data and platform readiness gaps will find that governance and people maturity alone cannot carry the transformation."

IDC MaturityScape Benchmark: AI-Fueled Process Manufacturing Organization Worldwide, 2026

Jeffrey Hojlo, Nigel Wallis, Claudia Medina — Wed, 14 Oct 2026 04:00:00 GMT

This IDC MaturityScape Benchmark examines the maturity of process manufacturers worldwide in 2026 against four dimensions (Strategy, People, Technology, and Governance) based on methodology laid out in IDC MaturityScape: AI-Fueled Organization 2.0 (IDC #US54450625, April 2026).

“Process manufacturers are still in the early stages of their AI journeys, and that shows up clearly in governance, the most mature of the four dimensions we measured this year, though still far from fully scaled. Leadership in governance is not the same as leadership everywhere. Technology remains the sector’s weakest link, and as agentic AI moves from pilots into production, process manufacturers that have not modernized their data and platform foundations on top of decades of legacy production and quality-management infrastructure will find that governance maturity alone cannot carry the transformation,” said Simon Ellis, group vice president, Worldwide Manufacturing and Supply Chain, IDC. “This is consistent with the sector’s safety- and quality-critical nature: process manufacturers can face significant product recalls, regulatory sanctions, and environmental compliance penalties for governance and quality-management failures, giving them a strong incentive to mature AI governance ahead of other dimensions.”

Modernizing Campus Networks — Security, AI, and Strategic Planning in a Refresh Cycle

Brandon Butler, Taranvir Singh, Chris Barnard — Wed, 14 Oct 2026 04:00:00 GMT

This IDC Perspective guides network leaders through this modernization cycle, sharing survey findings on refresh priorities, examining how enterprises reshape campus strategies for AI workloads and management, and offering frameworks for evaluating AI-enabled investments.

“Campus, branch, and edge networks are undergoing a transformative upgrade cycle as organizations deploy Wi-Fi 7, retire legacy infrastructure, and future proof for AI workloads. AI is fundamentally reshaping network management through agentic-powered automation and optimization, while integrated security protects against both traditional and AI-generated threats. To support high-bandwidth, low-latency agentic workloads while defending against evolving threats, enterprises require unified, AI-powered network platforms with native integrated security and comprehensive analytics — essential for future-ready networks.” — Brandon Butler, senior research manager, Network Infrastructure and Services, IDC

Broadcom's VMware Private AI Cloud Makes Agent Governance the Default

Adam Reeves, Matthew Flug — Tue, 13 Oct 2026 04:00:00 GMT

This IDC Perspective shares an overview of VMware Explore 2026, where Broadcom consolidated infrastructure, data, and security announcements under a new VMware Private AI Cloud banner, applying one governance pattern, identity verification, policy enforcement, and audit logging across three separate control points: the Tanzu Platform AI gateway, the standalone AgentMinder product, and a still-planned VCF-level gateway. Enterprise IT leaders evaluating this stack should treat governance depth, not governance claims, as the deciding factor; confirm what is actually shipping before committing budget; and assign clear ownership across Broadcom's overlapping control points before agentic workloads reach production scale.

"The interesting move here isn't any single control point; it's that Broadcom is holding one governance pattern, identity verification, policy enforcement, and audit logging, constant across three different layers of the stack: the platform gateway, the identity and governance layer, and the infrastructure layer beneath both. That's a deliberate choice to make governance look the same no matter which layer an enterprise is touching, rather than letting each layer define governance on its own terms," says Adam Reeves, research director, PaaS for Developers of Modern and Edge Applications, IDC.

IDC MaturityScape Benchmark: AI-Fueled Discrete Manufacturing Organization Worldwide, 2026

Jeffrey Hojlo, Nigel Wallis, Claudia Medina — Tue, 13 Oct 2026 04:00:00 GMT

This IDC study presents results from IDC’s MaturityScape Benchmark AI Survey, released worldwide in May 2026, drawing on a discrete manufacturing subsample of 162 organizations from the 1,900 organizations surveyed. It is the updated edition of IDC’s inaugural discrete manufacturing benchmark (see IDC MaturityScape Benchmark: AI-Fueled Discrete Manufacturing Organization Worldwide, 2025, IDC #US53335025, May 2025) and applies the framework set out in IDC MaturityScape: AI-Fueled Organization 2.0 (IDC #US54450625, April 2026). The most significant change this year is the elevation of governance to a distinct fourth dimension alongside strategy, people, and technology. Note: Because the underlying survey methodology and question set were revised for 2026, year-over-year figures are not directly comparable to the 2025 discrete manufacturing benchmark, and this document does not present numeric comparisons against prior-year results.

Discrete manufacturers post a marginally higher overall AI maturity score than the worldwide average (mean of 2.44 versus 2.43), led by governance (at 2.61, the most advanced of the sector’s four dimensions, echoing the global pattern), while technology, at 2.28, remains the least mature, reflecting persistent data and platform readiness gaps even as manufacturers digitize factories and connected assets.

“Discrete manufacturers show the most progress on governance, and this is not a coincidence; decades of investment in quality management, traceability, and safety certification gave the sector a head start on the discipline that governance requires,” says Jeff Hojlo, vice president, IDC Manufacturing Insights. “But governance leadership does not offset a comparatively immature technology foundation. As manufacturers work to unify data from connected assets and processes and move from generative to agentic AI, the sector’s data and platform readiness, not its governance approach, will determine how quickly AI-fueled transformation can scale.”

“This is consistent with the sector’s growing quality and safety compliance requirements: Discrete manufacturers can face costly recalls, warranty liabilities, and safety certification setbacks tied to governance and traceability failures, giving them a strong incentive to mature AI governance ahead of the other dimensions.”