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Atlassian's FY26 Historic Moment: Why Enterprise Customers are Buying

Stephen Elliot, Jevin Jensen, Jim Mercer — Thu, 13 Aug 2026 04:00:00 GMT

Autonomy on a Leash: A Framework for Agentic AI Governance

Thu, 13 Aug 2026 04:00:00 GMT

This IDC Perspective provides enterprise IT and GRC leaders with a foundational definitional framework for agentic AI governance — what it is, why it is structurally different from prior AI governance models, and what it requires specifically across every major domain of IT investment. Agentic AI governance is harder than generative AI governance not in degree, but in kind: agents act autonomously, delegate to other agents, and initiate consequential outcomes without per-step human authorization, making accountability without proximity the defining governance challenge. The document establishes a three-sentence definition, five operational pillars, ten domain-specific governance definitions mapped to those pillars, and fifteen cross-domain alignment frameworks that connect agentic governance to existing enterprise disciplines.

The document's central argument is direct: organizations that treat agentic AI governance as a post-deployment compliance layer are building governance debt that will compound as agent populations scale, regulatory obligations crystallize, and legal frameworks governing AI-initiated actions mature. Governance must be designed before deployment, enforced at machine speed during operation, and maintained as a continuous discipline as models, agents, and regulatory requirements evolve. The fifteen advice points for technology buyers translate this analytical framework into a prioritized, actionable road map — from agent inventory and NHI life-cycle management through to RACI model design, TPRM extension, PQC migration, and governance standards engagement — providing the evidence enterprise IT and GRC leaders need to navigate their next move with confidence.

"Agentic AI governance is not a compliance checkbox; it's the operational foundation that determines whether agentic AI delivers enterprise value or creates enterprise liability. Organizations that wait to implement governance until after deployment are not avoiding cost; they're compounding risk," said Duncan Brown, Group VP, IDC.

Dynatrace Acquires Arize AI to Define Emerging AI Engineering Category and Accelerate Growth Vectors

Stephen Elliot, Shannon Kalvar, Jim Mercer, Archana Venkatraman — Thu, 13 Aug 2026 04:00:00 GMT

On August 13, Dynatrace announced its intent to acquire AI Engineering platform provider Arize AI ($915 million in stock and cash, 200 employees, founded in 2020) to accelerate growth and add emerging AI Agent performance and MLOps capabilities for evaluations, debugging, testing, tracing, and continuous feedback loops for agent improvement opportunities from two products: Phoenix OSS (open-source AI observability and evaluation platform) and Arize AX (managed enterprise platform for AI observability, evaluation, and continuous improvement). Arize AI raised a total of $131 million in funding across four major rounds; the most recent being a $70 million Series C round announced in February 2025. The products use an open-source PLG model to offer freemium/Community-to-Commercial plans that provide users with production ML analytics and workflows to identify model and data issues, diagnose root causes, and continuously improve performance for end-user products. This is a potentially transformational acquisition for Dynatrace as an organization, for customers, and partners.

Dynatrace Q1FY27 Results: Steady AI and Customer Growth; What's Next?

Stephen Elliot — Thu, 13 Aug 2026 04:00:00 GMT

Several of the key financial and business highlights include:

Total ARR of $2,136 million, an increase of 17% on an as reported and constant currency basis

Total revenue of $555 million, an increase of 16%, or 15% on a constant currency basis

Subscription revenue of $530 million, an increase of 16%, or 15% on a constant currency basis

GAAP income from operations of $71 million and non-GAAP income from operations of $162 million

Demonstrated four consecutive quarters of acceleration in trailing-twelve-month organic net new ARR growth.

Nearly doubled annualized logs consumption in the last two quarters to $200 million, growing well over 100% year-over-year.

Delivered significant advancements of Dynatrace Intelligence, extending the power of the Dynatrace platform. New capabilities include Autonomous SRE Agent, Cloud SRE Agent, and Agent Builder to help customers move beyond analysis and recommendations into trusted, autonomous execution.

IDC MarketScape: Worldwide Insurance Customer Experience Platforms 2026 Vendor Assessment

Inci Kaya — Thu, 13 Aug 2026 04:00:00 GMT

This IDC study evaluates leading CX platform vendors serving the insurance sector, providing a comprehensive, evidence-based assessment of their capabilities, strategies, and fit for a range of insurance use cases. Insurance is undergoing a fundamental transformation as customer experience (CX) becomes a primary driver of competitive differentiation, retention, and growth.

Our research finds that the most successful insurers are those that leverage modern CX platforms to orchestrate seamless, omni-channel journeys, unify customer data, and embed AI-driven automation and analytics throughout the policyholder life cycle. The vendor landscape is diverse, with solutions ranging from cloud-native, modular platforms to process-driven transformation partners. Leading vendors distinguish themselves through deep insurance domain expertise, robust integration ecosystems, rapid deployment models, and measurable business outcomes such as improved NPS, faster claims resolution, and increased digital adoption.

Insurance buyers should use this IDC MarketScape as a strategic guide to assess vendor strengths and challenges, align technology investments with business objectives, and accelerate their CX transformation. As a result, insurers can expect to identify partners that will help close the experience gap and help position carriers as differentiated, desirable brands.

"Customer satisfaction is no longer a byproduct of efficient operations; it's the outcome of intelligent, proactive engagement powered by next-generation AI." — Inci Kaya, senior research manager, Digital Strategies, Insurance Worldwide

IDC PlanScape: AI Software Engineering Intelligence

George Mironescu — Thu, 13 Aug 2026 04:00:00 GMT

This IDC PlanScape presents guidance about:

Capability areas that enable organizations to measure, attribute, benchmark, and govern how AI participates in software delivery
Needs and concerns of key stakeholders concerning AI usage in software engineering activities
Benefits, approaches, and considerations related to deploying intelligence environments
Tactical and higher-order aspects when strategizing around adoption programs

Together, this guidance helps engineering and technology leaders move from anecdotal AI adoption to evidence-based decision-making.

"We are rapidly entering a period of adoption realism and questioning of AI consumption, efficiency, and returns. Starting from the most elite software engineering entities to the average organization, many are realizing that they need to become more intentional about capturing, measuring, and addressing the returns of their AI software engineering investments in a structured and objective way," says George Mironescu, associate research director, Software Development, Delivery, and Engineering, IDC.

IDC's Impact Analysis on the Role of AI for Energy Transition of Buildings and Facilities

Roberta Bigliani — Thu, 13 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation overlays AI onto 187 value cases in IDC's Worldwide Digital Transformation Use Case Taxonomy, 2026: Energy Transition for Buildings and Facilities (IDC #EUR154783426, August 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 IDC study answers three questions. First is where AI fits: conventional and agentic AI are mapped to every building and facility's 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. 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 inside defined guardrails. The distinction matters for governance, skills, and vendor selection, and it shapes how quickly value shows up in 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 carry the strongest AI-driven upside and which remain dependent on non-AI levers.

The intended audience includes building owners and real estate, facilities, energy, sustainability, finance, and technology leaders working alongside them. This document is created to help these teams sequence their AI investments in support of energy transition across individual sites and full building and facilities portfolios, rather than treat AI as a horizontal add-on to existing programs.

IDC's Worldwide AI-Enabled Managed Services Deals Analysis for Technology Outsourcing Services, 2023–2025

David Tapper — Thu, 13 Aug 2026 04:00:00 GMT

This IDC Perspective provides an overview of how adoption of AI-enabled managed services deals is evolving based on an analysis of more than 1,600 technology outsourcing services deals from 2023 to 2025 worth more than $144 billion in total contract value (TCV), while also highlighting key market and industry trends that will shape the investments that managed service providers (SPs) need to pursue to optimize their opportunities in this dynamically shifting market.

"AI, particularly agentic AI, is rewriting the rules and means by which managed service providers will need to compete, which requires making fundamental changes to their financial and operating models that will help grow their businesses and win deals," says David Tapper, VP, Outsourcing and Managed Cloud Services at IDC. "Ensuring success will require that managed SPs incorporate greater flexibility into contracts to accommodate use of agentic AI, invest in an autonomous operating platform with industry IP and private clouds, define new metrics of success, develop an AI services inventory management capability, and create an effective means of managing service provider partners."

Beyond the Prompt: The Hidden Data and Storage Implications of Generative AI

Adam Wright — Wed, 12 Aug 2026 04:00:00 GMT

This IDC Perspective analyzes the intersection of accelerating global data growth and the rise of generative AI. Drawing on IDC's Global DataSphere and Global StorageSphere forecasts and findings from IDC's 2026 Worldwide Data Utilization Survey, this document provides IT decision-makers with actionable guidance on adapting data infrastructure strategies to meet the demands of an AI-driven enterprise.

"The question IT leaders should be asking is not whether generative AI will increase their data volumes," says Adam Wright, research manager for IDC's Global DataSphere and Global StorageSphere. "Survey data makes clear that it will, and significantly so. The question is whether their infrastructure and governance strategies are built for this reality."

C-Suite Strategies to Maximize AI Factory Business Benefits

Wed, 12 Aug 2026 04:00:00 GMT

This IDC Tech Buyer Presentation gives C-suite decision-makers the insight they need to guide strategic conversations about AI factory investment and operational priorities. AI factories industrialize the conversion of enterprise data into AI-driven intelligence, using purpose-built, co-engineered infrastructure stacks deployed across dedicated on-premises datacenter, edge locations, and public cloud services. Business-led governance, compliance, and cost controls are required to keep AI factory spending and operating models aligned with strategic business priorities and AI workload-specific performance, security, and ROI expectations. The growth of AI inference and agentic AI deployments will dramatically increase infrastructure operational complexity and scale. This IDC Tech Buyer Presentation also helps tech buyers get ahead of the curve by providing guidance on how to build and implement a robust AI factory strategy that delivers business benefits.