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Collaborative Supply Chain Forecasting (CSCF) is a business discipline involving multiple supply chain stakeholders, including suppliers, distributors and sellers, that is aimed at producing a more accurate forecast of future demand and supply. Participants share supply and demand data, forecasts, assumptions and insights to improve visibility, reduce inefficiencies and attenuate supply-demand mismatches. ISG asserts that by 2028, one-third of larger enterprises will have adopted some form of CSCF to reduce costs and improve customer service and supplier relations. However, there are serious challenges to widespread adoption.

The emergence of natural language analytics interfaces driven by generative artificial intelligence (GenAI) models has accelerated enterprise initiatives to enable data democratization—making data available to business decision-makers without the need to train them to use business intelligence (BI) tools. It has also heightened the need for agreed semantic models and business metrics, as well as technologies that facilitate the sharing and consumption of data as a product. As I previously discussed, data as a product is the process of applying product thinking to data initiatives to ensure the outcome—the data product—is designed to be shared and reused for multiple use cases across the business as it enables enterprises to streamline and accelerate the delivery of analytics and artificial intelligence (AI) initiatives. The market for software that enables the design and delivery of data products is evolving rapidly, especially among providers of data catalog-based data intelligence software.

The idea of customer experience (CX) as a business practice relies heavily on being able to understand and track customer journeys. And that can be tricky because there isn’t a standard definition as to what a journey consists of. For example, inside a contact center the journey is perceived in terms of the steps a customer takes to achieve a particular result. Sometimes that is broadened out to include aspects of the customer’s history, especially when the business wants to use historical data to craft an offer or change a tactic.

The advances in data, analytics, Generative AI (GenAI) and agentic AI are transforming how healthcare and life sciences (HCLS) organizations deliver care, accelerate research, manage operations and engage patients. These innovations are driving measurable improvements in efficiency, accuracy and patient outcomes; however, adoption is not without challenges. Regulatory complexity, talent shortages, operational pressures and the need for responsible AI use demand thoughtful strategies. Organizations that can simultaneously innovate, scale responsibly and work closely with analytics partners to translate analytics goals into tangible outcomes will be the ones to succeed.

The Finance and Accounting Outsourcing (FAO) market in 2025 is undergoing one of the most significant shifts it has seen in the past decade. In contrast to 2024, when discussions surrounding AI, generative AI (GenAI) and advanced analytics primarily focused on pilots and early-stage PoCs, the current landscape is defined by operationalized innovation. Providers have transitioned from experimentation to deployment, embedding these technologies into live delivery environments and demonstrating measurable business impact.

Supply chains are being reimagined with intelligent orchestration, adaptability and resilience. Globally, they are under mounting pressure due to complexities driven by multitier supplier ecosystems, distributed manufacturing setups, hyperlocalized demand patterns and operational dependencies arising from geopolitical shifts. Supply chain companies
are increasingly recognizing that data and AI are essential for transforming supply chains, enabling responsive and even preemptive actions to minimize disruptions and their economic impact.

The dynamics of cybersecurity in the U.S. public sector are marked by an escalating threat environment, requiring a shift beyond operational continuity to comprehensive mission resilience. Government agencies at the federal, state and local levels face a complex array of sophisticated cyberthreats while pursuing critical digital transformation initiatives, including AI integration.

The cybersecurity threat landscape in the U.S. remains highly dynamic, presenting continuous challenges for organizations. Analysis of recent incidents by industry and public sector organizations reveals ongoing evolution in
adversary tactics and a concerning increase in the scale and impact of attacks.

The need for robust identity and access management (IAM) has become critical due to escalating cyberthreats, the expansion of hybrid work models and the widespread adoption of cloud technologies. IAM provides the foundation for secure operations, enabling organizations to innovate while meeting rigorous regulatory requirements.

In 2025, the Google Cloud partner ecosystem is driving significant enterprise value within the U.S. by leveraging Google Cloud’s strengths in AI, data modernization and analytics, security, and open, scalable infrastructure. Global system integrators (GSIs) with a strong U.S. presence collaborate with Google Cloud to deliver customized solutions and expert services (consulting, implementation, managed services, enterprise data infrastructure, and generative AI [GenAI] and AI services). This collaboration helps enterprises navigate complexity, accelerate cloud adoption and modernization, harness the transformative power of GenAI with platforms such as Gemini and Vertex AI, and achieve tangible business outcomes in an increasingly hybrid cloud and multicloud environment.

The U.S. state, local and education (SLED) IT infrastructure services market is projected to grow approximately to $150 billion by the end of 2025, with expectations to reach over $170 billion by 2028, with a moderately flat growth rate when compared to last year, mainly due to budget constraints and the changes brought in by the new government. High-impact services in modernization, cybersecurity and hybrid cloud technologies will drive spending as agencies will need to replace their legacy IT infrastructure. Hybrid cloud infrastructure managed services are gaining traction, as 90 percent of SLED agencies are expected to adopt hybrid cloud models, highlighting their importance in the U.S. public sector organizations.

In the realm of enterprise software-defined networking (SD-networking) solutions and services, organizations face a rapidly evolving landscape shaped by various strategic factors, including the emergence of new technologies, business imperatives and organizational processes. These factors are intricately aligned with global trends, such as enterprise
digitalization, business transformation, the need for enhanced security and the growing momentum toward cloudification. This study, conducted by the ISG Provider Lens™, focuses specifically on SD-networking within the U.S. market. It encompasses a broad spectrum of services and technologies, including managed SD-WAN, transformation services (consulting and advisory), edge technologies (including private enterprise 5G) and secure access service edge (SASE).

Advanced analytics and AI are fundamentally reshaping retail and consumer packaged goods (CPG) businesses. Analytics leaders are increasingly embedding data-driven capabilities across the entire value chain, from product innovation and supply chain to merchandising, sales and customer engagement. While implementation is still scaling up, ISG anticipates that comprehensive AI-driven transformation can deliver substantial profit uplift across retailer/CPG operations. This report explores key areas where analytics leaders are integrating advanced analytics and AI.

The life sciences industry is undergoing a profound transformation, shaped by digital disruption, patient-first innovation and an unrelenting drive toward operational sustainability. Service providers that lead in this space are moving beyond traditional models by embracing AI, generative AI (GenAI), IoT and advanced analytics to reimagine value delivery across clinical development, manufacturing, commercial operations and patient engagement. At this pivotal juncture, the strategic imperative is clear: those who embed intelligence, interoperability and inclusivity across their value chain will accelerate innovation and redefine outcomes.

I am struck by the blizzard of software announcements this year describing new features for CX tools that are “agentic,” meaning autonomous tools take actions without (much) human intervention. Industry conversation about agentic AI has proceeded ahead of clarifying definitions and a sense of how it fits on a continuum of rapid AI development.

The IT department of any enterprise is integral to implementing and managing the execution of its data objectives, just as the finance department is integral to implementing and managing financial objectives. Few enterprises would allow the finance department complete autonomy to define financial strategies; however, too many enterprises allow the IT department to define data strategies. Treating data as a business discipline—rather than a technical one—is a critical component of delivering competitive advantage through investment in data processing, analytics and artificial intelligence. This can be facilitated by adopting the most appropriate organizational approach, depending on the data activity.

The need for effective cybersecurity strategies remains a priority as enterprises face ever-increasing complex cyber threats. Nonetheless, the conventional approach in which IT departments, especially Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs), exclusively manage the procurement of cybersecurity software, is showing its limitations. A crucial shift is occurring: Cybersecurity is no longer solely the domain of IT but has become a strategic business imperative. Leaders across different departments, from finance to operations, must appreciate the indispensable role they play in guiding cybersecurity decisions. This Analyst Perspective explores the influences in cybersecurity software procurement beyond IT and security teams, highlighting the necessity for unified communication, collaboration and strategic alignment between technical needs and overarching business goals.

SAP Business Data Cloud (BDC) is the unification of capabilities that previously existed in two separate offerings: SAP Datasphere and SAP Analytics Cloud. As its name implies, Analytics Cloud was SAP’s analytics offering. However, unlike many of its competitors, it also included planning capabilities. SAP Datasphere was the evolution of SAP’s data warehouse as a service (formerly called SAP Data Warehouse Cloud) and included data management, data integration, data federation, data governance and data catalog capabilities.

Our 2025 research divides the workforce-management landscape into five focused guides—WFM Basics, WFM Suites, WFM for Healthcare, WFM for Manufacturing and WFM for Retail. Each report applies a common evaluation lens yet weights criteria to reflect the operational realities, compliance pressures and innovation priorities unique to its scope. Together, they provide a panoramic view of the market and a set of targeted benchmarks that let buyers zero in on the capabilities—and partners—best aligned to their context.

As enterprises navigate their digital transformation journeys, several key trends are shaping the adoption and utilization of SAP solutions. Many businesses face difficulties constructing a robust business case for migrating from SAP ERP to SAP S/4HANA. Understanding the TCO for the initial years remains a significant hurdle, with organizations seeking more clarity and frameworks to evaluate potential returns and justify the transition investment effectively. While pressure exists to migrate to SAP S/4HANA, firms are taking a cautious approach globally to ensure business continuity and pace the timing of the migration to minimize impact.