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AI-Infused GRC Tooling

Erik Werson — Fri, 02 Oct 2026 04:00:00 GMT

This IDC Perspective discusses how artificial intelligence represents the next evolution of governance, risk, and compliance (GRC) platforms. Traditional GRC solutions have long automated workflows, compliance monitoring, and control management through rules-based processes and system integrations. Modern AI builds on these foundations by introducing predictive intelligence, natural language capabilities, and increasingly autonomous decision support.

AI enhances the core GRC functions through capabilities such as regulatory change management, predictive risk analytics, intelligent control mapping, and automated evidence collection. Beyond these functions, AI-powered assistants, workflow automation, and decision-support capabilities improve operational efficiency while allowing GRC professionals to focus on strategic responsibilities.

However, AI should augment rather than replace human judgment, with accountability for governance and compliance decisions remaining firmly under human oversight. As AI capabilities evolve toward predictive, generative, and agentic models, organizations must also ensure explainability, transparency, and responsible AI governance.

When selecting an AI-infused GRC platform, organizations should evaluate alignment with business objectives, AI capabilities, capability maturity, and the trustworthiness of AI-generated outputs to maximize long-term business value and organizational resilience.

"The success of an AI-infused GRC platform is determined by more than the sophistication of its AI capabilities," says Erik Werson, adjunct research advisor for IDC's IT Executive Programs (IEP). "Organizations should evaluate whether the platform aligns with their business objectives, provides mature and trustworthy AI capabilities, and supports transparent, explainable decision-making to maximize long-term business value and organizational resilience."

When to Sunset Applications Rather than Re-Architect Them

Dr. Ken Knapton — Fri, 02 Oct 2026 04:00:00 GMT

This IDC Perspective examines how enterprises can identify the point at which continued optimization of legacy systems no longer produces sufficient value and should give way to planned replacement, consolidation, or controlled deferral. It provides a decision framework that links application rationalization to risk, operational resilience, governance discipline, and enterprise leverage.

"A legacy system does not need to fail before it becomes the wrong platform for the business," says Dr. Ken Knapton, adjunct research advisor for IDC's IT Executive Programs (IEP). "When continued optimization consumes capacity, compounds risk, and delays strategic capability, retirement becomes a leadership decision — not a technical preference."

AMD validates the importance of world models for physical AI with the acquisition of World Labs

Dan Everett — Thu, 01 Oct 2026 04:00:00 GMT

AMD's $8.2B all-stock acquisition of World Labs, about 64% above the $5B valuation reported for the company's February funding round, is a bet that physical AI is the next growth cycle and that spatial intelligence and world models are what make it work. Physical AI systems have to predict how physical objects move and what their actions will cause, and AMD is paying a premium to get a leading world model company and research team to address this need.

AMD's $8.2 billion World Labs deal is a bet that model research belongs inside its hardware roadmap

Jeff Janukowicz, Brent Ellis — Thu, 01 Oct 2026 04:00:00 GMT

AMD announced a definitive agreement on September 28, 2026 to acquire World Labs, the spatial-intelligence lab led by Dr. Fei-Fei Li, in an all-stock deal valued at about $8.2 billion and expected to close by the end of 2026, with Dr. Li joining as executive vice president and chief scientist reporting to Lisa Su. IDC believes the deal deepens AMD's open AI ecosystem and extends its shift from component supplier toward a full-stack AI infrastructure provider, with the main payoff being closer ties between leading-edge model research and systems and silicon design, so AMD can build emerging workload needs into its hardware, software, and systems roadmaps sooner.

Acumatica 2026 R2: Intelligence for the Mid-market with Embedded AI

Mickey North Rizza — Thu, 01 Oct 2026 04:00:00 GMT

Acumatica released R2 2026 today. The new GA product release brings Acumatica to the AI levels of many of their peers. While these AI updates may appear late, Acumatica clients find this new AI journey well timed, as told to IDC earlier this year. Many organizations, while trying AI, are leery of it and would prefer to walk before they run. With this next release, Acumatica is enabling their clients to do more at their own pace and with greater confidence.

The R2 2026 updates bring mid-market businesses embedded AI, modern analytics, a streamlined user experience and industry specific enhancements that are designed to help organizations improve productivity, make faster decisions, and scale more efficiently. The R2 2026 release brings forward new capabilities:

AI Assistant and AI Automation: Mid-size businesses will find a huge uplift with quicker and faster business answers, anomaly detection, the automation of repetitive tasks, and trigger prompt-driven workflows within Acumatica.

Modern user interface: As organizations move to R2 they will automatically transition to Acumatica’s modern user interface which provides a more consistent and intuitive experience across the Acumatica platform.

Modern Analytics for Faster Decision-Making: Acumatica R2 2026 lays the foundation for a unified, always-current view of the business with a high-performance governed data source that surfaces everywhere teams need it — in dashboards, financial statements, and now in the AI tools they already use. There are two advances anchoring this shift:

Native Data Warehouse: Reporting and analytics now run against a dedicated, performance-optimized copy of ERP data instead of the live transactional database, so reports don’t compete for system resources with day-to-day order entry, invoicing, and approvals. This foundational layer of centralized ERP data and performance optimization will be enhanced in future updates.

Model Context Protocol (MCP) Connection: Organizations can securely connect Claude, ChatGPT, Gemini, and other MCP-compatible AI tools directly to their Acumatica data without exporting, uploading, or duplicating information in a separate AI workspace. Role-based permissions, inherited security, and field level data masking automatically carry over, allowing teams to use the AI tools they already rely on while IT retains centralized governance and auditability for every query. Together with existing capabilities such as InsightXL, which connects live Acumatica data directly to Excel, these advances extend Acumatica's analytics so the same governed data reaches finance and operations teams through whichever surface the moment calls for — a dashboard, spreadsheet, AI assistant, or AI tool of their choice.

IDC's Worldwide Event-Driven Automation and Analytics Survey, 2026

Carlos Gonzalez — Thu, 01 Oct 2026 04:00:00 GMT

This IDC Survey reports results from the July 2026 IDC Event-Driven Automation and Analytics Survey, conducted with 635 IT and data decision-makers from organizations worldwide. These organizations have at least 500 employees and generate $500 million or more in annual revenue across 16 countries. The survey assesses how extensively enterprises implement real-time data infrastructure across five software areas—real-time data movement, stream processing and analytics, event stream processing, event brokering software, and IoT platforms—and examines whether this deployment aligns with the operational needs of agentic AI.

The data shows that 16.2% of organizations have extended real-time data movement to all workflows that require it. The main challenge is trust, not speed: data quality and consistency are the main technical barriers at 30.6%, significantly higher than latency and performance at 16.9%. Outcomes driven by agentic AI closely follow data maturity, with the percentage running multiple agentic applications in production rising from 8.0% among those with limited real-time data integration to 53.4% among those with comprehensive coverage. Investment plans are not keeping pace: 43.8% intend to increase AI and agentic AI spending by 25% or more, compared to 31.7% for data governance and observability, while only 6.6% plan a 50% or greater increase in governance.

"Agentic AI has turned real-time data from an efficiency project into a gating condition," says Carlos M. González, research manager, Event-Driven Automation and Analytics at IDC. "The model layer is largely commoditized. What separates an organization running one pilot from one running several agents in production is whether the data estate beneath them can supply current, governed state on demand."

Infobip Vendor Profile: AgentOS Connects Communications Scale with AI Interaction Orchestration

Denise Lund, Masarra Mohamed — Thu, 01 Oct 2026 04:00:00 GMT

This IDC Vendor Profile examines Infobip's transition toward a broader AI interaction orchestration proposition, with AgentOS as the central focus. Current deployments remain concentrated in customer engagement and service workflows, but Infobip's longer-term ambition extends to orchestration across customer-facing and internal interactions. This document assesses the company's operating foundation, product capabilities and maturity, commercial model, implementation ecosystem, and outlook.

NATO's Quantum Technology Roadmap: Strategic Competition Does Not Wait for Technological Certainty

Heather West, PhD — Thu, 01 Oct 2026 04:00:00 GMT

NATO's Quantum Technology Roadmap moves quantum beyond research priorities by establishing a structured path for evaluating, testing, securing, and integrating quantum capabilities across the Alliance. IDC expects this approach to accelerate demand not only for quantum technologies, but also for the broader infrastructure and integration capabilities needed to translate quantum advances into operational value.

Navigating the Agentic Shift: AI Strategies for Wealth Management

Dr. Chris Marshall, Michael Sek Pheng Yeo — Thu, 01 Oct 2026 04:00:00 GMT

This IDC Perspective examines the agentic AI moving from pilot to production in wealth management in 2026, productivity and ROI evidence supporting it, and governance practices technology buyers need to scale autonomy safely.

"The wealth managers winning with agentic AI are not the ones moving fastest; they are the ones who built the strongest foundations in platforms and governance before building the autonomy functions as well as those who are constantly evolving their budgets and decision-making based on the rapid cadence of development in the industry," says Michael Yeo, associate research director, IDC Financial Insights.

AI-ification of Retail Media

Ananda Chakravarty — Wed, 30 Sep 2026 04:00:00 GMT

This IDC Perspective provides a viewpoint of how AI is changing the game with respect to mapping current attribution metrics in retail media. The report also reviews how AI addresses audience targeting as well as attribution through a set of techniques being pioneered by firms such as Amazon, Walmart, and other retail media networks (RMNs). The report also highlights marketing mix modeling and how this may move the market toward a more holistic view of retail media. Finally, the report identifies the flaws of return on ad spend (ROAS) attribution and how AI may overcome these flaws through new attribution methods.

"When your retail media metrics say 10x returns, but you're barely breaking even, it's time to revisit attribution. AI is changing the retail media game. New AI models are being rolled out by the most sophisticated RMNs to drive precise attribution. It's time for a reset," said Ananda Chakravarty, research vice president, IDC Retail Insights.