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Agentic Commerce: Are AI-Generated Answers a New Gateway to Liability?

Heather Hershey, Roger Beharry Lall — Mon, 13 Jul 2026 04:00:00 GMT

This IDC Perspective discusses a landmark Munich court ruling that found Google liable for false AI-generated answers, redefining AI outputs as authored claims rather than mere search results. This signals a shift in legal accountability for AI answer engines, with significant implications for agentic commerce and brand discovery. As AI-generated content becomes central to consumer interactions, organizations must prioritize source accuracy, audit exposure, and update indemnification terms, recognizing that the shield protecting platforms from liability may no longer apply when AI synthesizes and authors information.

"Brand leaders have been racing to appear in AI-generated answers. Munich adds a harder question: What happens when those answers are wrong, and who is left holding the liability?" — Roger Beharry Lall, research director, Advertising Technologies and SMB Marketing Applications at IDC

Best Practices in Leveraging AI, GenAI, and Agentic AI for Retail Operational Workflows

Cristiano Quattrini, Margot Juros — Mon, 13 Jul 2026 04:00:00 GMT

This IDC PeerScape identifies best practices for retailers seeking to apply agentic AI to operational workflows. It focuses on four common challenges: orchestrating fragmented retail data and processes, embedding AI into frontline work, using AI to improve inventory and fresh-product decisions, and governing autonomous actions in sensitive operational environments.

Retailers are entering a phase in which the competitive value of AI depends less on experimentation and more on operationalization. The issue is not whether retailers can build pilots, but whether they can connect agents to the data, systems, teams, and controls required to influence day-to-day decisions. Walmart’s development of Wally illustrates the emerging use of agentic capabilities for merchandising and inventory decisions. Marks & Spencer’s rollout of Microsoft 365 Copilot illustrates how GenAI can improve frontline productivity and decision support. Carrefour’s use of AI for supply chain and fresh-product planning shows the value of advanced forecasting and optimization, while Amazon’s use of multimodal AI for fulfillment quality and compliance demonstrates the potential of AI-enabled operational automation. Together, these examples show how retailers are building the foundations for more autonomous and agentic operational workflows.

The practices discussed in this PeerScape show that agentic AI succeeds when it is deployed around clear operating problems, when users understand its role, when workflows include human oversight, and when retailers measure outcomes such as labor productivity, stock availability, waste reduction, faster decision cycles, improved customer service, and lower operational risk.

“Agentic AI’s real value emerges when it becomes part of the operating model, connecting signals, decisions, actions, and accountability across stores, supply chains, commerce, and customer service. Retailers should start with workflows where AI can reduce decision latency, improve consistency, and free teams from repetitive coordination work while keeping humans responsible for judgment, escalation, and customer impact,” says Cristiano Quattrini, senior associate advisor, IDC Retail Insights.

IDC Presentation: AI Shopping Discovery in Europe

Margot Juros, Ornella Urso, Cristiano Quattrini — Mon, 13 Jul 2026 04:00:00 GMT

This IDC Market Presentation examines how AI-mediated shopping discovery is emerging in Europe and how it is beginning to reshape the consumer decision journey.

AI shopping is not yet a mass autonomous purchasing behavior, but it is already becoming a crucial layer of assisted evaluation before the retailer receives the click, visit, or transaction.

The presentation also analyzes the implications for European retailers as product research, price comparison, review interpretation, and shortlist creation move further upstream into AI answer engines. Retailer readiness depends less on launching standalone shopping bots and more on becoming readable, retrievable, and recommendable by AI systems. This requires stronger product data foundations, structured content, product information management (PIM) and commerce platform integration, credible trust signals, and governance across content, ecommerce, marketing, data, and security teams.

Finally, the presentation assesses the emerging role of generative engine optimization and answer engine optimization, as well as the early development of AI answer-engine visibility measurement. While SEO remains a necessary foundation, retailers are beginning to test new approaches to improve visibility in AI-generated answers, monitor AI share of voice, and understand the revenue influence of zero-click discovery journeys.

Retailers that cannot measure and shape AI-mediated discovery risk losing consideration before shoppers reach their owned channels.

“AI shopping in Europe should not be interpreted as an overnight shift to autonomous purchasing,” said Cristiano Quattrini, senior associate advisor, IDC Retail Insights. “The more immediate and important change is that AI answer engines are becoming a new upstream layer of influence. Consumers are using them to research, compare, summarize, and validate choices before they reach a retailer’s site, app, marketplace listing, or store. For retailers, this means visibility is no longer only about ranking in search results. It is about being understood, trusted, cited, and recommended by AI systems. The next competitive battleground will be the ability to combine structured product data, answer-ready content, credible trust signals, and AI visibility measurement into a new discovery operating model.”

Cybersecurity for Critical Transport Infrastructure: From Regulatory Mandate to Operational Reality

Ravikant Sharma — Fri, 10 Jul 2026 04:00:00 GMT

This IDC Market Presentation examines how the convergence of regulatory enforcement, escalating threat activity, and operational technology modernization has fundamentally changed the cybersecurity landscape for critical transport infrastructure. It establishes the regulatory forcing function that has converted previously discretionary security spending into mandatory procurement obligations, diagnoses the specific capability gaps between what transport operators have built and what regulation now requires, and identifies where the next wave of investment is forming across autonomous transport, IoT, agentic AI, and post-quantum cryptography.

The document covers the market context through IDC survey data and regional budget signals, documents the threat environment through verified 2024–2025 incidents, maps the compliance specification across EU, U.S., and APAC regulatory frameworks, and concludes with six implications and recommendations drawn from the body of evidence.

"Transport cybersecurity has reached a structural inflection point. Regulation has made investment nonnegotiable. The capability gaps are specific, measurable, and documented. And the next wave of risk, from autonomous systems to agentic AI, is already ahead of the frameworks designed to address it. The evidence in this study makes the case for acting now, not when the next mandate arrives," says Ravi Kant Sharma, research director, Government Insights, IDC.

Enterprise Procurement and Partnership in the Age of AI and Outcome-Based Connectivity — Analysis by Region

Paul Hughes — Thu, 09 Jul 2026 04:00:00 GMT

This IDC Perspective is the first in a series of three documents that examine how businesses expect to procure connectivity services and related transformation projects in the era of AI and outcome-based connectivity. Drawing on IDC's 2025 Enterprise Connectivity Infrastructure and Services Survey and other related IDC data sources, this IDC Perspective identifies regional differences for connectivity provider preferences and procurement methods across North America, Europe, and APAC.

"Regional procurement patterns reveal that geography still shapes how enterprises source and evaluate connectivity," commented Paul Hughes, research director, Future Enterprise Connectivity Strategies at IDC. "This comes even as the underlying provider competition converges globally and as AI leadership from the supplier community differs in depth, perspective, and approach."

Market Forecast: Worldwide Telecommunications Capex Forecast, 2026–2030

Peter Chahal, Nikhil Batra, Bruno Teyton — Thu, 09 Jul 2026 04:00:00 GMT

This IDC presentation provides a worldwide forecast for telecommunications service provider capex covering the 2026–2030 period. The capex forecast is broken out between wireless and wireline networks, with data for each one of the three main geographic regions. Capex is defined as capital spending by telcos to acquire or upgrade tangible assets (plant, property, and equipment) and intangible assets, excluding telecommunications and spectrum licenses.

“Telecom service providers are entering a more disciplined investment phase, with global capex expected to decline at a 1.8% CAGR from 2026 to 2030 as markets mature and efficiencies improve,” said Peter Chahal, research director of Worldwide Telecommunications Services and Strategies at IDC. “This shift reflects a sharper focus on capital allocation, with operators prioritizing cost optimization and free cash flow while advancing monetization strategies and AI-driven automation, alongside targeted investments in satellite connectivity and preparation for 6G.”

从数字AI到物理AI：世界模型、仿真数据闭环与中国应用场景观察

Hongyu Cheng — Thu, 09 Jul 2026 04:00:00 GMT

本IDC看法报告围绕AI从数字任务走向真实世界行动的产业演进展开，重点分析物理AI的定义边界、全球产业链、中国市场图谱、软件基础设施方向和典型应用场景。报告指出，物理AI不是单一机器人、自动驾驶系统或仿真平台，而是AI与物理硬件在真实场景中形成“感知—理解—推理—规划—执行”闭环的系统能力。随着AI从Tokens驱动的数字任务，扩展到由连续场景片段Clips支撑的真实世界训练和验证，世界模型、仿真平台、合成数据和场景数据闭环将成为物理AI软件基础设施的重要方向。

报告进一步分析了智能驾驶、机器人、无人机与低空、工业设备和智慧城市相关物理场景的应用路径。智能驾驶由于具备较成熟的数据闭环和安全验证需求，将率先体现物理AI软件基础设施的产业价值；机器人、低空、工业和城市空间场景则将围绕动作片段、飞行片段、工程仿真和多主体推演逐步延展。整体来看，物理AI的落地路径将从场景数据化、数据资产化、仿真验证化，进一步走向模型闭环化和真实部署化。未来竞争重点不只在模型或硬件，而在于谁能更高效地把真实世界转化为可训练、可验证、可部署的数字资产。

IDC智慧城市分析师程鸿宇表示：“物理AI的产业价值不应只从机器人、自动驾驶或无人机等单一应用理解，而应放在AI能力从数字任务向真实世界行动扩展的过程中观察。与数字AI主要围绕Tokens、内容生成和软件流程不同，物理AI更依赖连续场景片段、世界模型、仿真验证和数据闭环。未来，模型能力仍是基础，但决定产业化进度的关键将转向场景数据质量、仿真可信度、安全验证能力和工程集成水平。智能驾驶由于具备较完整的数据回流、仿真测试和量产验证链路，将率先体现物理AI软件基础设施的价值；机器人、低空、工业设备和智慧城市相关物理场景，则会沿着动作片段、飞行片段、虚拟试验和多主体推演等方向逐步延展。整体来看，物理AI的竞争重点将从‘谁的模型更强’转向‘谁能更高效地把真实世界转化为可训练、可验证、可部署的数字资产’。”

Salesforce Connections 2026: Short-Term ROI on Marketing AI to Drive Long-Term Transformation

Gerry Murray, Heather Hershey, Douglas Hayward, Roger Beharry Lall, Tapan Patel — Wed, 08 Jul 2026 04:00:00 GMT

This IDC Perspective summarizes Salesforce Connections 2026 and its implications for CMOs and marketing technology buyers. The document covers Salesforce's Agentforce Marketing and Commerce announcements, including the pipeline generation agents Piper and Hunter, the Contentful acquisition, the Agentforce Marketing Goals Agent, and Headless 360 MCP campaign management capabilities.

"The road to scaling agentic marketing is ultimately an organizational, process, and technological transformation proposition, each step of which will have to pay its way," says Gerry Murray, research director, Enterprise Marketing Apps and Agents, IDC. "By forming its go-to-market strategy on this principle, Salesforce aligns itself with CMO agendas and CFO requirements for funding enterprise-scale investments, which expands account TAM and accelerates Salesforce's ability to capture share of the agentic infrastructure spend."

State and Future of the Automotive Industry in the Age of AI

Jeffrey Hojlo, Wai Yee Lee — Wed, 08 Jul 2026 04:00:00 GMT

This IDC Market Presentation examines the state and future of the automotive industry in the age of AI, analyzing the macro forces reshaping competitive dynamics, namely tariffs and trade disruption, ecosystem orchestration complexity, expanding connectivity and cybersecurity requirements, and tightening sustainability mandates. The presentation evaluates business priorities, factory modernization investments, and technology spending plans spanning powertrain electrification, ADAS and sensor fusion, software-defined vehicles, and AI infrastructure. A dedicated analysis of AI maturity and agentic AI adoption in R&D and engineering is included, alongside findings on connectivity strategy, industry ecosystem collaboration models, and Scope 3 sustainability imperatives.

"The automotive industry has reached an inflection point where AI adoption is table stakes and ecosystem orchestration is the new competitive battleground. Manufacturers that move beyond isolated pilots to a closed-loop system — connecting design, production, supply chain, and field service into a unified digital thread — will compress cycle times, reduce warranty exposure, and build the agility to navigate tariff volatility, the ongoing EV transition, and expanding cybersecurity demands simultaneously. Agentic AI is the mechanism that makes orchestration at scale possible," says Jeff Hojlo, research vice president, Engineering and Product Innovation Strategies, and Manufacturing Insights, IDC.

Challenges to Starlink After SpaceX's Blowout IPO

Simon Baker — Tue, 07 Jul 2026 04:00:00 GMT

The SpaceX IPO propelled the company into the ranks of the world's most valuable companies. Expanding its core Starlink internet service will depend largely on operational issues. Declining ARPUs threaten profitability and increase the need to put Starship into service to launch larger satellites at lower cost.