Executive Insights for Supplier Intelligence

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. 

The 2025 SAP Ecosystem study for the U.S. observes that enterprise clients, like the previous year, continue to have a cautious and risk-averse approach to planning their migration from ECC 6.0 to SAP S/4HANA cloud. External factors such as economic headwinds and tariff conflict and technical factors such as limited reference business use cases, uncertain ROI, legacy systems to support technology such as generative AI (GenAI), longer implementation duration and data migration challenges have made the transition to SAP S/4HANA even more complex. Enterprises in the U.S. are reassessing their strategies for transformation to SAP S/4HANA. They are increasingly focused on an approach that guarantees minimal business disruption and cost-effective solutions. These enterprises are seeking service partners that can offer strong consulting capabilities for a seamless transformation road map. Clients in the U.S. want to assess the risks and implications of accepting SAP’s subscription terms and the future expansion of their ERP systems, leading to an increase in demand for robust risk management and change management tools and solutions. 

The shift toward a Zero Trust Network Access (ZTNA) framework is a strategic move for enterprises aiming for an enhanced security posture. ZTNA operates on the principle of "never trust, always verify," ensuring that every user and device is authenticated and authorized before accessing resources. In this context, Privileged Access Management (PAM) emerges as a critical enabler for an effective ZTNA implementation.

ISG Software Research is expanding our ISG Buyers Guide™ coverage to include the topic of sustainability. Our buyers guide will focus on sustainability exclusively rather than the full spectrum of environmental, social and governance topics. One reason is that gathering, managing, analyzing and reporting environmental data under the various frameworks and statutes presents enterprises with considerably greater challenges than the other two. For most, it is likely the least well defined and the hardest for acquiring and managing environmental-related data. ISG Research asserts that through 2027, one-half of enterprises will have insufficient data and software to adequately measure their environmental, social and governance metrics to inform their governance strategy, risk management and targets.

Frontline work is being reshaped from every direction: tighter labor pools, unpredictable demand and a workforce that expects more than just a paycheck. Yet too many organizations are still treating workforce scheduling like a game of Tetris—moving blocks around and hoping they fit. It’s time to admit that smart scheduling isn’t just a nice-to-have—it’s a frontline imperative. And if the enterprise is still thinking of it as “just logistics,” it's already falling behind.

I have previously described how data as a product was initially closely aligned with data mesh, a cultural and organizational approach to distributed data processing. As a result of data mesh’s association with distributed data, many assumed that the concept was diametrically opposed to the data lake, which offered a platform for combining large volumes of data from multiple data sources. That assumption was always misguided: There was never any reason why data lakes could not be used as a data persistence and processing platform within a data mesh environment. In recent years, data as a product has gained momentum outside the context of data mesh, while data lakes have evolved into data lakehouses. It has become increasingly clear that data lakehouses and data as a product are well matched, as the data intelligence cataloging capabilities of a lakehouse environment can serve as the foundation to enable the development, sharing and management of data as a product.

Conversational automation is one of those software segments that means something different depending on who you are or your role in an organization. According to my colleague Jeff Orr, the core of the idea is that conversational automation tools benefit from artificial intelligence (AI), allowing software agents, chatbots and virtual assistants to automate customer interactions and internal processes. This broad definition hits the mark, I think, because it identifies the core functions without putting too tight a straitjacket on the technology itself, which is developing very quickly. The software provider landscape is analyzed in the ISG Buyers Guide for Conversational Automation.

For decades, organizations have treated sales incentive compensation as a separate entity, isolated from the broader total rewards strategy. This isolation stems from historical operations, where sales compensation is designed and managed within Sales, with periodic budget oversight from Finance, while HR focuses on base pay, benefits and equity. Unfortunately, this siloed approach, further reinforced by outdated technology and entrenched business practices, limits companies from fully leveraging their total rewards strategy. As a result, I predict that by 2028, many companies will find their compensation processes ineffective, prompting a critical assessment of their alignment with desired priorities and values.

The six costliest words in managing a finance department are, “We’ve always done it this way.” The record-to-report (R2R) cycle describes the process of finalizing and summarizing the financial activities of a business for a specific accounting period—typically a month, quarter or fiscal year. It is important to note that R2R exclusively covers the activities between recording (keeping the books) and reporting (publishing financial statements and management accounts). It involves completing various tasks to ensure that all revenue, expense and other financial transactions are properly recorded, accounts are balanced and accurate financial statements can be prepared.

Ten years have passed since artificial intelligence (AI) first appeared in sales technology, and the results are mixed. Early tools applied rudimentary machine learning (ML) models to customer relationship management (CRM) exports, assigning win probability scores or advising on the “ideal” time to call. The mathematics was sound, the demos impressive, yet adoption faltered because little thought was given as to how sellers should use this information.

In an era defined by the relentless advance of cyber threats, enterprise security leaders grapple with an overwhelming landscape. Enterprises face complex challenges as sophisticated attacks and increasing responsibilities stretch security teams thin. Many describe daily experiences as perpetual "firefighting," trapped in cycles of reacting to incidents rather than developing proactive strategies to fortify defenses.

Enterprises are transforming their HR operating models to align with evolving talent strategies, EX goals and digital maturity aspirations. With mounting pressure to deliver hyperpersonalized employee journeys, ensure global compliance and drive cost efficiencies, organizations are increasingly turning to multiprocess human resources outsourcing (MPHRO) providers for scalable, agile solutions. Today’s MPHRO engagements extend beyond  mere transactional efficiency; they have evolved into strategic partnerships that help enterprises build future-ready workforces. From recruitment and onboarding to learning, payroll and employee engagement, MPHRO providers are central to modernizing HR delivery models.

Global market dynamics are currently characterized by uncertainty and turbulence, driving organizations to increase their focus on cloud-related investments aimed at improving business visibility, predictability and resilience. Tech spending for 2025, especially related to the Microsoft AI and Cloud ecosystem, is mainly driven by investments in cybersecurity, cloud-enabled (and AI-fueled) innovation, data and analytics, digital transformation and infrastructure modernization, particularly hardware/device refresh initiatives as Windows 10 approaches the end of life.

Particularly with the integration of generative and agentic artificial intelligence (AI) technologies. Generative AI usecases have quickly proliferated across all aspects and phases of engineering- spanning from R&D, design, build, test, run/ operations, to aftermarkets, field services, and ultimately in the digital business platformization services. These innovations have transformed various sectors, including chip design, precision manufacturing, life sciences, and service platforms in banking, financial services, insurance, and retail. Hyperscalers—large-scale cloud service providers—have played a pivotal role in this transformation by offering advanced AI services tailored to engineering design applications.

The global capability center (GCC) market is undergoing a rapid transformation, evolving from traditional cost-saving hubs to strategic enablers of enterprisewide digitalization. Organizations are increasingly looking beyond labor arbitrage and are instead positioning their GCCs as CoEs that drive innovation, enhance CX and optimize business operations.