Executive Insights for Supplier Intelligence

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.

The chemicals industry drives the U.S. economy by generating high-paying jobs, fueling R&D investments and supplying essential chemicals for daily life. Trade is crucial to the industry’s competitiveness. As the second - largest manufacturing export sector in the U.S., the chemicals industry recorded a trade surplus exceeding $30 billion in 2023, with exports supporting nearly 200,000 jobs.

In an earlier Analyst Perspective, I discussed data democratization’s role in creating a data-driven enterprise agenda. Building a foundation of self-service data discovery, data-driven organizations provide more workers with the ability to analyze and use data. I’ve also examined how generative artificial intelligence (GenAI) could revolutionize business intelligence software by using natural language interfaces to lower the barriers to working with analytics software. Today, however, data democratization ensures that access is not limited to analytics software. Users in different roles should be able to use data through whatever applications or tools best align with their business workflow and objectives. This is the driver behind growing interest in a new category of products that enable headless BI.

For years, HR technology has been seen primarily as an administrative tool—handling records, payroll and compliance. But what if its real power lies in shaping workforce strategy, building community and driving transformation?

There are contact centers, and there is customer experience. They are not the same thing, even though we have a tendency to conflate them or at least discuss them in tandem for operational and planning purposes. This is mostly fine, but it does obscure one basic difference that will matter more as enterprises succeed at integrating contact centers into enterprise CX strategies. That difference is in metrics and, by extension, how we define success.

AI, like analytics, must lead to action. Too often, in both cases, too much of the exercise is left to the reader. We have tools to provide sophisticated analyses, including AI platforms that can be used to predict many types of behavior, but we fall short in helping the workforce know what to do with that information. Some examples are more obvious, such as fraud detection. If a transaction is predicted to be fraudulent, the transaction should be blocked. But even this example is not as cut and dry as you might think. I’m sure many of you have been frustrated standing at a hotel check-in desk or at a retail counter attempting to make a purchase when your credit card transaction has been denied. What is the appropriate action or set of actions that should be taken?

Agents and “agentic AI” are all the rage now, eclipsing last year’s focus on artificial intelligence (AI) and generative AI (GenAI). They are a way to automate work almost effortlessly so that repetitive and boring tasks get done with the least amount of effort and perhaps, more consistently. In business software, a broad range of software providers are claiming agents to be a panacea that can improve performance and lower costs. They are alluring, with an almost unlimited number of potential use cases. Agents are an important evolutionary step in the design of business software, similar to the transition from procedural programming to event-driven programming that accelerated in the late 1980s. That paradigm shift enabled business software to be more flexible and responsive in replicating how work is performed. Adding agents to the considerable body of well-developed business applications will take the capabilities of these applications to the next level.

Conversational automation leverages artificial intelligence (AI)-powered agents, chatbots and virtual assistants to automate both customer interactions and internal processes. These systems understand natural language, sentiment and intent, generating relevant responses and executing actions based on user input. The software provider landscape is analyzed in the ISG Buyers Guide for Conversational Automation.

Payroll is one of the most universal touchpoints within any organization, impacting every employee on a regular basis. It’s the one thing every employee notices if it does not work perfectly. Yet, despite its far-reaching presence, payroll often operates quietly in the background, treated as an administrative function focused solely on ensuring people are paid accurately and on time. This perception, while understandable, drastically undervalues what payroll can offer.

Based on the number of invitations I have received to speak on the topic, usage pricing (also referred to as consumption pricing) is hot. But as I have remarked elsewhere, it is not new. I recall a conversation with a customer over 30 years ago when I was involved with analytic software who asked, “Why can’t we just pay for the software we use?” And this of course makes sense: only pay for what you use. In fact, I assert that by 2027, over one-half of all enterprises will deploy a mixed revenue model that includes subscriptions and usage pricing in addition to one-time sales as enterprises make adjustments to remain competitive.

Enterprise Resource Planning (ERP) systems are comprehensive software platforms designed to integrate and manage all the core processes of an enterprise while recording transactions and their financial consequences to support the accounting and finance functions. ISG Software Research recently completed our Buyers Guide™ for ERP systems, designed to help enterprises that are replacing their existing ERP software to make the best choice, both in terms of the product’s performance as well as the customer experience. ERP systems are central to the operations of an enterprise, streamlining cross-functional operations using workflows and consolidating data created by departments such as finance, human resources, supply chain and customer relationship management into a unified database. This integration facilitates the accessibility of real-time data, enhancing situational awareness for executives and managers while boosting overall efficiency and productivity.

The manufacturing industry is undergoing a period of significant transformation, driven by a confluence of technological advancements, economic shifts and evolving consumer expectations.

The industry is being impacted in areas such as smart manufacturing, supply chain optimization, aftermarket services and sustainability. Manufacturers are leveraging technologies such as IoT, AI, ML, digital twins, AR, VR and cloud to optimize production processes, improve quality and enhance efficiency. They are also implementing digital solutions to streamline supply chain operations, reduce costs and improve visibility. Aftermarket services are being placed at the forefront and integrated into core business processes to drive customer satisfaction and revenue.

Advancements in AI applications are redefining the landscape of business service automation in the U.S., disrupting use cases and codifying service knowledge using generative AI (GenAI) technologies. These innovations, powered by large language models (LLMs), vision-language models (VLMs), small language models (SLMs), retrieval-augmented generation (RAG) and other appropriate finetuning techniques, are revolutionizing how organizations automate customer service, IT support and business operations.

The transformation of business designs and operating models is a fundamental necessity for North American insurance carriers aiming to sustain competitiveness and effectively navigate the complexities of contemporary market conditions. This imperative arises from several critical factors, including customers’ evolving expectations, volatile geoeconomic circumstances and the increasing frequency and severity of property and life losses primarily attributed to climate change.

The healthcare payer landscape is undergoing a significant transformation, driven by a shift toward value-based care (VBC), the integration of advanced analytics and AI, and a commitment to improved member engagement and interoperability. These trends reflect a broader movement toward patient-centered models that prioritize quality  outcomes and enhance the healthcare experience for all stakeholders.

The U.S. data analytics and AI market is undergoing transformative changes and a dynamic evolution driven by technological advancements, regulatory changes and enterprise demands. The market is also experiencing an accelerating need for enterprises to integrate advanced technologies, especially AI, into their business strategies.

The U.S. data analytics and AI market is undergoing transformative changes and a dynamic evolution driven by technological advancements, regulatory changes and enterprise demands. The market is also experiencing an accelerating need for enterprises to integrate advanced technologies, especially AI, into their business strategies.

Strategic consolidation and an emphasis on improving technology capabilities are driving a noticeable increase in M&A activity in North America’s telecom, media and entertainment (TME) industries. Compared to previous years, the number of deals increased significantly in 2023 and 2024 as private equity groups became more aggressive in purchasing media and technology businesses. As businesses look to safeguard their digital infrastructures in response to growing customer demands for individualized content and services, there is a noticeable movement toward cloud services and  cybersecurity. Furthermore, as businesses manage compliance while seeking expansion through mergers and  acquisitions, regulatory scrutiny continues to influence deal-making tactics. As the economy stabilizes amidst the lowering of interest rates and persistent inflation, there is cautious optimism about future M&A activity.