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IDC MarketScape: U.S. Care Coordination Application 2026 Vendor Assessment

Jennifer Eaton — Wed, 12 Aug 2026 04:00:00 GMT

This IDC study evaluates U.S. care coordination vendors on the strategies and capabilities that move past record keeping, regulatory checklists, and manual workflows. Care coordination continues to change, pushed by the need to deliver care that is more efficient, more effective, and organized around the patient rather than the visit. That pressure has grown as value-based payment moves from voluntary pilots to models that carry real financial risk, tying an organization's margin to the outcomes and total cost of the populations it manages. U.S. healthcare organizations are responding with a new generation of care coordination technology built to manage complex patients, use limited clinical staff and resources well, raise the quality of care, and improve the experience of both the end user and the patient.

"Care coordination has crossed from a documentation problem to a decision problem. The data finally moves; the question now is whether the technology can turn it into the right action, at the right moment, for the right patient." — Jennifer Eaton, research director, IDC's Health Insights

IDC MarketScape: U.S. Patient Engagement and Enablement Technology Solutions 2026 Vendor Assessment

Jennifer Eaton — Wed, 12 Aug 2026 04:00:00 GMT

This IDC study assesses the U.S. patient engagement and enablement technology market and the vendors that serve it. Patient engagement has moved from a set of add-on tools to a working part of how providers and payers manage cost, quality, and the relationship with the people they serve. Three forces are driving that shift. Patients now expect the digital convenience they get from other industries. Value-based and outcomes-based payment ties revenue to results that depend on reaching and activating patients. And new interoperability rules, together with more capable AI, are putting more usable data within reach while raising expectations for how quickly and clearly organizations communicate with patients and members. Digital access, remote monitoring, multichannel outreach, education, and AI-driven personalization are becoming standard rather than distinguishing features, and the organizations that succeed are the ones that use them to reach people through the channels they actually use.

The study evaluates vendors on the capabilities and strategies that serve both providers and payers while delivering the consumer-grade experience patients expect. It gives technology buyers a factual basis for comparing solutions, separating shipped capability from road map, and matching a vendor's orientation, whether payer rooted, provider facing, or consumer first, to their own populations and goals.

"Healthcare organizations can no longer treat patient engagement and enablement as a siloed, 'one size fits most' effort aimed at marketing and brand loyalty, and they cannot start and stop with a care encounter or an enrollment window. Engagement has to be continuous, proactive, personalized, and grounded in data that follows the person across their care. The tools and the data to do this now exist, and federal policy is pointing the same way, so the question for 2026 is not whether to build data-driven, whole-person engagement but how quickly an organization can. Patients need it, deserve it, and increasingly expect it." — Jennifer Eaton, research director, IDC Health Insights

IDC MarketScape: Worldwide Agentic Contact Center–as-a-Service Platforms 2026 Vendor Assessment

Michelle Morgan — Wed, 12 Aug 2026 04:00:00 GMT

This IDC study explores the evolution of CCaaS from basic call distribution to advanced, AI-driven orchestration platforms. It highlights the shift toward agentic AI, enabling autonomous workflows and broader customer experience integration. This document evaluates vendors based on capabilities, strategy, and market share, offering guidance for buyers on architectural framing, use case alignment, and AI governance to ensure successful deployment and measurable outcomes.

“The real disruption in contact centers isn’t AI itself,” says Michelle Morgan, research manager, AI-Enabled Sales, Customer Service and Contact Center Strategies at IDC. “It’s how agentic platforms redefine what must be orchestrated, measured, and governed across the entire customer journey. Individual AI capabilities are, at this point, table stakes. What changes is the operating model underneath them: When an agent can initiate actions, hand off across systems, and make judgment calls that used to require a human, the unit of work shifts from a single interaction to a chain of them. That shift is where most contact center leaders’ existing governance frameworks start to show their age.”

Market Forecast: Worldwide IT Leasing and Financing Forecast, 2026–2030

Lara Greden — Tue, 11 Aug 2026 04:00:00 GMT

This IDC presentation provides the five-year forecast for the IT leasing and financing market and delivers insights into the drivers and inhibitors of growth.

"Financing and leasing enable flexible, OPEX-based procurement that protects against technology obsolescence and depreciation risk while improving budget predictability, particularly valuable for AI infrastructure and rapid refresh cycles. These models conserve capital while also bundling sustainability benefits such as circularity and ITAD, which most buyers weigh as important decision criteria." — Lara Greden, senior research director, Networking and Infrastructure Services, Enterprise Infrastructure at IDC

IDC MarketScape: Worldwide AI-Enabled Order Orchestration and Fulfillment Applications for B2B and Manufacturing 2026 Vendor Assessment

Heather Hershey — Mon, 10 Aug 2026 04:00:00 GMT

This IDC study evaluates vendors of worldwide AI-enabled order orchestration and fulfillment applications for B2B and manufacturing in 2026. The vendor assessment examines a market shaped by contractual complexity, multitier distribution networks, and extended production cycles, where order management sits at the critical intersection of front-end commercial activity and back-end supply chain execution. The document evaluates vendors on their ability to orchestrate complex, multiparty, contract-governed trade at scale. It also considers the role of deterministic AI and proven automation capabilities in recognition of the reliability and control that B2B buyers demand. Furthermore, tariff volatility and shifting regulatory environments across the global supply chain elevate trade compliance automation as a top-of-mind requirement. This IDC MarketScape serves as a guide for pragmatic buyers in search of platforms that deliver measurable efficiency gains once fully deployed.

"In B2B manufacturing, order management and orchestration succeeds not through the flashiest AI, but through platforms that hold up under contractual complexity and prove their value in consistency, auditability, operational efficiency, and measurable return on investment over the long haul," said Heather Hershey, research director, Worldwide Digital Commerce, IDC

IDC’s Impact Analysis of AI in the Energy Transition of Industrial Energy Users: Mapping Conventional and Agentic AI Across IDC’s Entergy Transition for Industrial Energy Users DX Use Cases

Roberta Bigliani — Mon, 10 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation overlays AI onto the 190 value cases in IDC’s Worldwide Digital Transformation Use Case Taxonomy, 2026: Energy Transition for Industrial Energy Users — Capability Priorities, Programs, and Value Cases (IDC #EUR154782326, July 2026). Each value case is assigned a horizon based on maturity, and its business contribution is scored against three lenses: Growth, Efficiency, and Productivity.

This report answers three questions. The first is where AI fits: conventional and agentic AI are mapped to every industrial energy transition value case, so readers can see which parts of the portfolio are already served by predictive models and analytics, and which are open to agent-based approaches. The second is where systems can act: decision-support use cases (where AI recommends and a human decides) are separated from autonomous, closed-loop use cases (where agents execute within defined guardrails). The distinction matters for safety, governance, skills, and vendor selection, and it shapes how quickly value shows up in plant operations. The third question is where value concentrates: Growth, Efficiency, and Productivity scores are compared at the strategic-priority level, so leaders can see which priorities offer the strongest AI-driven upside and which remain dependent on non-AI levers.

The intended audience is industrial operations, energy, procurement, sustainability, finance, and technology leaders. The document helps these teams sequence AI investments to support energy transition across individual plants and full industrial portfolios, rather than treat AI as a horizontal add-on to existing decarbonization and efficiency programs.

IDC’s Worldwide Digital Transformation Use Case Taxonomy, 2026: Energy Transition for Industrial Energy Users — Capability Priorities, Programs, and Value Cases

Roberta Bigliani — Mon, 10 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation provides a structured framework for mapping the strategic technology transformation underlying the energy transition for industrial energy users. This taxonomy covers 9 strategic priorities, 47 programs, and 190 use cases. Every use case has an investment horizon tag (H1, H2, or H3) based on current adoption evidence from IDC’s Energy Transition Survey (June 2026). Executive voices ground every priority in real-world action.

Technology leaders, sustainability executives, operations heads, and strategy teams in chemicals, steel, cement, automotive, food and beverage, consumer goods, life sciences, and heavy industry can use this taxonomy to frame their energy transition initiatives, identify capability gaps, prioritize investments, and align their timing with industry peers and regulatory milestones.

IDC’s Worldwide Digital Transformation Use Case Taxonomy, 2026: Manufacturing Asset-Oriented Value Chains (AOVCs)

Simon Ellis, Reid Paquin, Sarah Lee — Mon, 10 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation updates IDC’s digital transformation use case taxonomy for asset-oriented value chains (AOVCs) through 2026, including relevant generative and agentic AI use cases. Asset-oriented value chains are characterized as process-oriented manufacturing segments that invest heavily in manufacturing plants and equipment to efficiently produce large volumes of materials such as chemicals, metals, and pulp/paper.

This taxonomy provides a structured framework for mapping the strategic technology transformation underway across the manufacturing industry. The taxonomy follows a hierarchical structure that begins with that industry’s digital mission, the strategic priorities that support the mission, the programs to be initiated to satisfy these priorities, and the funded projects or use cases to be implemented under those programs. Additionally, each use case is assigned to one of three investment horizons based on industry adoption rates to balance near- and long-term goals.

The goal is to provide AOVC executives, technology leaders, and their vendor and advisory partners with a comprehensive, evidence-based map that answers three questions at once: what capabilities the industry must master to compete in the digital economy, how those capabilities organize into coherent investment domains, and where each is located on the maturity curve. This enables capital, talent, and technology decisions to be prioritized against a shared industry benchmark rather than ad hoc internal assessments.

IDC’s Worldwide Digital Transformation Use Case Taxonomy, 2026: Manufacturing Brand-Oriented Value Chains (BOVCs)

Simon Ellis, Reid Paquin, Sarah Lee — Mon, 10 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation updates IDC’s digital transformation use case taxonomy for brand-oriented value chains (BOVCs) through 2026, including relevant generative and agentic AI use cases. Brand-oriented value chains are characterized by branded products that experience high demand variability (e.g., consumer products, food and beverage, health and beauty, footwear, and household products).

This taxonomy provides a structured framework for mapping the strategic technology transformation underway across the manufacturing industry. The taxonomy follows a hierarchical structure that begins with that industry’s digital mission, the strategic priorities that support that mission, the programs to be initiated to satisfy these priorities, and the funded projects or use cases to be implemented under those programs. Additionally, each use case is assigned to one of three investment horizons based on industry adoption rates to balance near- and long-term goals.

The goal is to provide BOVC executives, technology leaders, and their vendor and advisory partners with a comprehensive, evidence-based map that answers three questions at once: what capabilities the industry must master to compete in the digital economy, how those capabilities organize into coherent investment domains, and where each is located on the maturity curve. This enables capital, talent, and technology decisions to be prioritized against a shared industry benchmark rather than ad hoc internal assessments.

IDC’s Worldwide Digital Transformation Use Case Taxonomy, 2026: Manufacturing Engineering-Oriented Value Chains (EOVCs)

Simon Ellis, Reid Paquin, Sarah Lee — Mon, 10 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation updates IDC’s digital transformation use case taxonomy for engineering-oriented value chains (EOVCs) through 2026, including relevant generative and agentic AI use cases. Engineering-oriented value chains are characterized by complex, highly engineered products, including aerospace, automotive, consumer durables, and farming, construction, and industrial machinery (FCIM).

The goal is to provide EOVC executives, technology leaders, and their vendor and advisory partners with a comprehensive, evidence-based map that answers three questions at once: what capabilities the industry must master to compete in the digital economy, how those capabilities organize into coherent investment domains, and where each stands on the maturity curve. This enables capital, talent, and technology decisions to be prioritized against a shared industry benchmark rather than ad hoc internal assessments.