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CIO Peer Perspective — Engineering Sustainable AI Economics in the Agentic Era

Heather Herbst, Jevin Jensen, Martina Longo, Robert Parker — Tue, 28 Jul 2026 04:00:00 GMT

This IDC study highlights the growing complexity of AI cost structures, the impact of agentic AI on resource consumption, and the need for robust cost governance. As AI becomes integral to enterprise operations, CIOs are shifting focus from rapid deployment to engineering sustainable AI economics. Best practices include early FinOps integration, architectural optimization, and disciplined vendor management to ensure measurable business value and cost efficiency as AI adoption scales.

“The future of AI leadership isn’t about deploying the fastest—it’s about engineering the most sustainable economics in an era where every token counts,” says Heather Herbst, research director, CFO Buyer Insights at IDC.

IDC TechScape: Worldwide Frictionless Experience-Enabling Innovation in Air Travel, 2026

Dorothy Creamer — Tue, 28 Jul 2026 04:00:00 GMT

This IDC TechScape maps 24 technologies shaping the frictionless airline traveler experience in 2026, organized across transformational, incremental, and opportunistic adoption phases. The study covers the full passenger journey, from booking and pre-trip planning through security, in-flight experience, luggage handling, and post-trip engagement, as well as the crew- and operations-facing technologies that directly determine whether travelers encounter a friction-free journey or a frustrating one.

“Passenger and traveler demands are at an all-time high and the opportunities for disruption and frustration lurk at every digital touch point. The airlines and travel providers that are working to support travelers with proactive and predictive engagement and operational strategies will win with contextualized and frictionless experiences every time,” says Dorothy Creamer, senior research manager, Hospitality and Travel Digital Strategies, IDC. “The constraint separating leaders from laggards in air travel is no longer which vendor relationships they hold; it is whether their data estate is mature enough to let these technologies work together and deliver on their promise.”

Medidata NEXT London 2026: AI Moves from Pilot Purgatory to Platform Scale

Silvia Piai — Tue, 28 Jul 2026 04:00:00 GMT

Medidata Solutions’ (Medidata) NEXT London 2026 marked the shift from AI experimentation to enterprisewide agentic deployment, anchored by the commercial launch of Medidata Plus and the full rollout of Dot. Key innovations include AI-driven simulation workspaces for protocol and enrollment planning, a proprietary Patient Burden Index, GenAI-powered site selection, and an expanded patient engagement platform that integrates continuous sensor data. Customer evidence, including a 37% enrollment uplift in atopic dermatitis trials and up to 70% reduction in budget build times, confirmed operational impact. Medidata also presented its “orchestrated intelligence” vision, extending clinical research intelligence across the life sciences value chain through partnerships with Anthropic, NVIDIA, and Mistral.

Clinical organizations should prioritize data standardization, adopt simulation and site selection tools early in protocol design, and evaluate contract research organization (CRO) partners on AI readiness. Medical device companies navigating the evolving regulatory environment in 2026 should treat early platform engagement as a strategic opportunity.

“Medidata NEXT London 2026 showed an industry moving from AI ambition to AI accountability. The evidence is real. Enrollment gains, faster builds, smarter site selection, and platform models such as Medidata’s offer one indication of how these capabilities can move from pilots to enterprise scale. For medical device companies, the moment to start engaging is now while both the underlying platforms and regulatory landscape are still being defined,” says Silvia Piai, research director, IDC.

Navigating Shortening Obsolescence Cycles: Actions Technology Leaders Should Take Now

Niel Nickolaisen — Tue, 28 Jul 2026 04:00:00 GMT

This IDC Perspective reveals that a critical success factor for technology leaders is the ability to adapt as technologies, technology providers, and organizational needs change. We have entered an environment of increasing change — driven by AI innovation. One of the consequences of increased technological change is the shortening of obsolescence cycles. As technology lifetimes shrink, there is an increased need to shorten technology planning and modernization timelines while also reviewing and changing business practices and decisions regarding the useful life and payback period of technology investments.

Technology leaders, departments, and their broader organizations that perform best in an environment of rapid change are those that make their processes, plans, and architectures more agile and adaptive and that recognize that such capabilities are now the minimum required.

“The pace of technology change has always defined the technology leader’s challenge,” says Niel Nickolaisen, adjunct research advisor for IDC’s IT Executive Programs (IEP) practice. “What is different currently is that the pace itself is accelerating — and the organizational models, planning horizons, and financial assumptions that served technology leaders well at a slower pace are no longer adequate. The technology leaders who recognize this structural shift and adapt their practices accordingly will increase the likelihood of their and their organization’s success.”

Beyond Check the Box: Choosing a Security Framework Built for AI Risk, Quantum Threat, Regulatory, and Your Organization's Reality

Philip D. Harris, CISSP, CCSK — Mon, 27 Jul 2026 04:00:00 GMT

This IDC Perspective updates IDC's foundational guidance on framework selection to reflect a materially changed landscape: NIST CSF 2.0 expanded scope and added a Govern function in 2024; DORA became applicable to approximately 22,000 EU financial entities in January 2025; and PCI DSS v4.0 retired the legacy standard in March 2024. Security framework selection is a risk management decision, not a technical checklist. Organizations that have not revisited their framework strategy since 2022 are likely operating against outdated assumptions about both the available options and the regulatory obligations that may constrain — or drive — their choice.

Two criteria that did not exist as first-order considerations in 2022 now demand explicit attention. AI adoption has introduced new attack surfaces — model poisoning, prompt injection, and agentic system risks — for which NIST published a draft Cyber AI Profile in December 2025. Post-quantum cryptography (PQC) has moved from theoretical concern to operational imperative, with NIST finalizing three PQC standards in August 2024 and regulators establishing migration deadlines. Organizations that embed both considerations into their framework selection process now will be substantially better positioned than those that treat them as future-state concerns.

"The right security framework is a critical factor in adequately managing security risks not only present today but also risks that could appear in the future," says Phil Harris, research director, Cybersecurity GRC Solutions at IDC. "The 2026 landscape demands that organizations evaluate AI governance and post-quantum cryptography readiness as first-order criteria, not future-state considerations. Organizations that apply a structured, criteria-driven approach, supported by capable GRC technology, will make framework choices that are the right fit today and resilient enough to evolve as the threat and regulatory landscape continues to change."

Cinven's Acquisition of Salsify: A Bet on a Retail Network Marketed as a Bet on Bots

Heather Hershey — Mon, 27 Jul 2026 04:00:00 GMT

Cinven, the international private equity firm, announced on July 22, 2026, that it has agreed to acquire Salsify, the Boston-based cloud-native product experience management (PXM) vendor, for undisclosed terms and subject to customary regulatory approvals.

Driving Operational Excellence with Digital Twins in Manufacturing

Sarah Lee, Carlos Gonzalez, Gunjan Bassi — Mon, 27 Jul 2026 04:00:00 GMT

This IDC Perspective examines how digital twins are evolving from visualization tools into the simulation and orchestration backbone of physical AI on the shop floor. It distinguishes between the simulation role, which models processes and assets to support engineering and AI training, and the orchestration role, which coordinates physical systems, AI agents, and workers in real time. It examines divergent adoption patterns across process and discrete manufacturing and profiles the vendor landscape. It provides guidance for operations and plant leaders on sequencing investments, building data foundations, and pairing twin programs with workforce enablement.

"Digital twins are evolving beyond visualization to become the operational backbone of AI-enabled manufacturing. As manufacturers move toward autonomous operations, digital twins provide the simulation environment to train AI and the orchestration layer to coordinate assets, systems, and people in real time," says Sarah Lee, senior research director, Manufacturing IT Strategies at IDC.

"A digital twin may be technically secure yet still become operationally unreliable if its data, models, and assumptions drift from reality. Trust requires both protection and continuous validation," says Gunjan Bassi, research manager, Worldwide Industrial Internet of Things (IIoT) and Intelligence Strategies at IDC.

"A digital twin is only as good as the data beneath it. Without a unified industrial data layer that mirrors real-world plant conditions, even the most sophisticated twin serves only as a virtual mirror. For real digital twins to evolve in the world of physical AI, real-time data analysis and automation must be in sync with digital twin simulation," says Carlos Gonzalez, research manager, Event-Driven Automation and Analytics at IDC.

Emerging Agentic Automation Patterns

Neil Ward-Dutton — Mon, 27 Jul 2026 04:00:00 GMT

This IDC Perspective examines how AI agents are being applied to business operations, beyond early adoption in marketing and software development. Using IDC's Business Automation Blueprint, the document identifies four emerging patterns — agents as task actors, knowledge assistants, orchestrators, and designers/improvers — and explains where each fits alongside established deterministic automation technologies such as workflow tools, RPA, and integration platforms. It closes with practical guidance for technology buyers evaluating where and how to deploy agents within existing operations.

"As AI agents begin to be used within broader business automation initiatives, it's vital to understand the different roles that AI agents can play, and how those roles differ," said Neil Ward-Dutton, research VP, Agentic Automation and AI Technologies at IDC.

Expanding Enterprise Intelligence: IDC’s Future Enterprise Planning Guide

Stewart Bond — Mon, 27 Jul 2026 04:00:00 GMT

This IDC Tech Buyer Presentation provides tech leaders guidance on key considerations for their organization’s enterprise intelligence. Leaders will find steps on framework and strategy, developing key goals and objectives, assessing capabilities, and pursuing ways to fill any gaps. Strategic planning can help modern businesses develop and deliver intelligence to the right decision-makers in a timely fashion. The full value of data is realized only when it is used in business activities, delivering required business outcomes that are driven and informed by data.

IDC finds that many organizations’ struggles with AI implementations are driving a shift toward concentrating investments on data. Enterprise intelligence strategy is key in these efforts to achieve AI-ready data. “Enterprise intelligence relies on data for analytics and decision-making, but definition and context, including relevance, are required to ensure the right data is being used, “ says Stewart Bond, vice president, Data Intelligence and Integration Software Research at IDC. “The foundation of enterprise intelligence is data intelligence. Intelligence about data supports and informs every data-driven learning, analytics, decision, action, and outcome.”

How Ukraine's Drone War Is Rewriting the Rules of Technology Development, and What That Means for Government Procurement

Alison Brooks, Ph.D., Alan Webber, Ruthbea Yesner — Mon, 27 Jul 2026 04:00:00 GMT

This IDC Perspective discusses how Ukraine's drone war has compressed technology development from years to weeks: 3D-printed hardware, AI running directly on the aircraft, open source tools, and a feedback loop in which the engineer who built a drone learns of a battlefield failure within hours. This document examines how this happened — production up roughly 80,000% since 2022, strike success rates rising from 20% to 80% — and what does and doesn't transfer to Western defense and public safety procurement. Most of the conditions behind Ukraine's model — its data scale, its motivational proximity, and its open development culture — are specific to a country fighting for survival and cannot be replicated in peacetime. But the procurement lesson — that acquisition systems built for stability are mismatched to threats iterating weekly — transfers directly.

"Ukraine's drone war didn't just speed up development; it inverted who gets to set the pace. A police department or a defense program can borrow the discipline of fast iteration, but the wartime conditions that make Ukraine's model work — the data scale, the tolerance for field failure, and the total absence of classification friction — aren't something procurement reform can manufacture," says Alan Webber, program vice president, National Security, Defense, and Intelligence at IDC.