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IT for Circularity: Vendor Offerings and Best Practices (Part Two)

Katharina Grimme, Melvie Espejo — Fri, 17 Apr 2026 04:00:00 GMT

This IDC Perspective evaluates six leading technology vendors in the IT for circularity space, highlighting their solution portfolios, capabilities, and best practice examples. It provides guidance for tech buyers navigating regulatory requirements that seek to leverage traceability, data management, and AI-powered tools to accelerate circularity initiatives, achieve compliance, and unlock business value. This is the second of two documents analyzing key tech vendor offerings and real-world applications.

"In the race toward circularity, technology is not just an enabler but the catalyst redefining value, resilience, and innovation across tomorrow's supply chains," says Katharina Grimme, AVP and EMEA sustainability research lead, IDC.

SugarCRM Rebrands to SugarAI, Signaling a Shift to AI-Driven Revenue Intelligence

Roger Beharry Lall — Fri, 17 Apr 2026 04:00:00 GMT

SugarCRM's rebrand to SugarAI represents a substantive strategic shift rather than a cosmetic update, as is commonly seen with rebranding efforts. The company is repositioning from a traditional CRM provider toward an AI-driven revenue intelligence platform focused on "precision selling" — leveraging signals from ERP, transactional, and engagement data to guide sales actions in real time.

This direction aligns with a broader industry inflection point, where AI is forcing a reassessment of CRM's core value proposition. Historically, CRM systems have struggled with low seller adoption, inconsistent data quality, and an overreliance on manual data entry, often limiting their effectiveness as decision-making tools. AI is now being applied to address these gaps by automating data capture, enriching context, and shifting systems from passive repositories to proactive guidance engines.

SugarAI's approach reflects this transition by reducing dependence on manual input and emphasizing automated insight generation. However, the strategy also reinforces the company's potentially limiting focus on sales execution, with comparatively less focus across the broader customer experience (CX) stack (i.e., marketing and service), which is critical when addressing the entire customer journey.

Value Density Index: A Practical Framework for Measuring Business Value Against IT Complexity Cost

Dr. Ken Knapton — Fri, 17 Apr 2026 04:00:00 GMT

This IDC Perspective argues that reducing enterprise technical debt requires a shift from simply decreasing application count to increasing value density across the technology portfolio. Although many organizations have reduced application sprawl, they often fail to achieve meaningful gains in agility, cost efficiency, or innovation because underlying complexity, such as fragmented integrations, redundant capabilities, and data inefficiencies, remains unaddressed. The document introduces the value density index (VDI) as a practical framework to measure the business value delivered per dollar of system complexity, enabling IT leaders to prioritize simplification efforts that drive real business outcomes. By reframing rationalization as a value amplification strategy, organizations can identify which systems to invest in, simplify, or retire based on their contribution to agility and innovation. Ultimately, embedding value density into governance, architecture, and funding decisions transforms rationalization into a continuous portfolio discipline that reduces complexity while enhancing enterprise resilience and growth.

“In most enterprises, the real cost of tech debt is not found in the application portfolio, but rather in the integration and data dependency web around it,” says Dr. Ken Knapton, adjunct research advisor, IT Executive Programs, IDC. He also adds, “The value density index provides a practical way to fund what amplifies value and stop investing in what amplifies friction.”

Conquering Observability Challenges for AI Agents

Christopher Tozzi — Thu, 16 Apr 2026 04:00:00 GMT

This IDC Perspective offers guidance on what businesses can do to meet agentic AI observability challenges. Implementing effective observability for AI agents and workflows is critical for ensuring that agents perform adequately and take appropriate and effective actions. It is also essential for mitigating financial waste and security risks. However, the unique nature of agentic AI technology complicates effective observability in several ways. The intrinsically nondeterministic nature of AI systems makes anomaly detection based on agentic workflows difficult, as does the subjective nature of deciding what an agent is “supposed to” do in response to a given prompt or request. Agents’ complex interactions with external tools, alongside the need to design observability systems that can identify agent problems and spur mitigations in real time, further complicate the task of agent observability. Currently, there are no simple solutions to these challenges. Yet, effective actions are available to enterprises for injecting observability into AI agents and workflows.

“Ultimately, enterprises’ goal in the realm of AI agent observability should be ensuring that they collect the insights necessary to determine whether AI agents are supporting business goals without introducing undue costs or security risks,” says Chris Tozzi, adjunct research advisor with IDC’s IT Executive Programs (IEP). “And when agents fall short, enterprises must have the observability data they need to mitigate shortcomings within agentic systems.”

IDC PlanScape: AI Process Optimization to Maximize Benefits and Avoid Risk

Thu, 16 Apr 2026 04:00:00 GMT

This IDC PlanScape examines AI process optimization to maximize benefits and avoid risk.

“Embedding AI into business processes has tremendous potential, but it also can introduce increased risk without the right preparation,” says Karen D. Schwartz, adjunct research analyst, IDC’s IT Executive Programs (IEP). “It’s critical to ensure that processes are ready for AI, along with choosing the best use cases, because some processes aren’t good candidates.”

Maximizing Engineering ROI: Optimizing DevOps, SRE, and Platform Engineering to Accelerate Customer-Centric Innovation

Helen Beal — Thu, 16 Apr 2026 04:00:00 GMT

This IDC Perspective outlines how organizations can reduce cognitive overload, enforce compliance, and directly link technical investments to measurable business outcomes while avoiding the pitfalls of toolchain sprawl and AI hype.

CIOs face mounting complexity as DevOps, SRE, and platform engineering (PE) have become mainstream but remain fragmented, increasing cognitive load and impeding business alignment. In 2026, the imperative is to consolidate these frameworks into unified, platform-centric solutions and leverage agentic AI to automate, standardize, and optimize the digital value stream.

“Labels like DevOps or SRE are just operational scaffolding; outcomes are the architecture. Modern CIOs must bridge the ‘context gap,’ ensuring engineering teams understand the ‘why’ of the market, while the C-suite respects the ‘how’ of the stack. Success requires aligning engineering throughput with value stream delivery, ensuring technical health maps to business outcomes,” says Helen Beal, adjunct research advisor for IDC’s IT Executive Programs (IEP).

Infor Analyst Innovation Summit 2026: Delivering the Agentic Enterprise

Mickey North Rizza — Wed, 15 Apr 2026 04:00:00 GMT

Infor held its 2026 Analyst Innovation Summit in Atlanta, Georgia, on April 14 and 15. The innovation summit showcased Infor's journey from 2025 well into 2026, with particular emphasis on the customer agentic AI journey and the Infor products and ecosystem partners that are helping their clients become an agentic enterprise.

Japan DevOps Software Forecast, 2026–2030

Shinichi Kimura — Wed, 15 Apr 2026 04:00:00 GMT

This IDC presentation provides the 2025 market size and market forecast through 2030 for the Japan DevOps software market, broken down by functional market and by delivery model. It also analyzes the drivers and inhibitors of market growth and key market context, presenting directions, growth opportunities, and recommended actions for IT suppliers as they develop their future strategies.

Across all industrial sectors, digital business initiatives are advancing and accelerating the development and release cycles of the applications that form the foundation of these operations, as well as delivering value through software while maintaining and enhancing quality. These challenges have become critical management priorities that determine a company's competitive advantage. Against this backdrop, an increasing number of companies are adopting DevOps initiatives to transform traditional development and operations processes and structures that hinder software delivery.

Shinichi Kimura, research manager for Software, Services, and IT Spending at IDC Japan, says, "Demand for software that underpins the DevOps practices of enterprises and organizations continues to show solid, sustained growth. In recent years, initiatives to integrate generative AI into DevOps pipelines to further automate and advance software delivery have been gaining real momentum, and the DevOps software market is expected to enter a new phase of growth."

This is the English translation of the Japanese document (IDC #JPJ53499826).

Tech Buyer Survey Spotlight: How Much Are Organizations Spending on AI Efforts?

Mona Liddell — Wed, 15 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Survey Spotlight examines how much organizations are allocating to AI budgets, based on responses from C-level IT leaders in IDC's Future Enterprise Resiliency and Spending (FERS) Survey, Wave 10, December 2025. The findings show that AI spending is shifting toward higher spending tiers, with a growing share of organizations planning larger investments over time alongside generally increasing IT budgets. This directional change highlights how AI funding levels are evolving across enterprises.

AI Under Siege: Jailbreaks, Poisoning, and Other Security Threats

Kathy Lange — Tue, 14 Apr 2026 04:00:00 GMT

This IDC Tech Buyer Presentation examines the evolving AI threat landscape, highlighting how vulnerabilities across data, models, and autonomous systems introduce new security, governance, and trust risks for enterprises. It provides a framework for understanding these risks and outlines strategies for securing AI systems across their life cycle.