U.S. enterprises are rapidly moving beyond experimental uses of advanced analytics and artificial intelligence, integrating these technologies deeply into their core business systems, according to a new research report released by Information Services Group (ISG), a global technology research and advisory firm with a strong focus on AI.
Instead of treating analytics and AI as isolated innovation projects, large organizations across the U.S. are now weaving these capabilities into everyday decision-making, process automation, and performance measurement. As a result, analytics and AI have become foundational elements of enterprise-wide digital transformation strategies.
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The 2025 ISG Provider Lens Advanced Analytics and AI Services reports for the U.S. reveal that enterprises are actively responding to increasingly complex IT environments. With large organizations managing software portfolios that often approach 2,000 applications, fragmented data and disconnected systems have emerged as major challenges. Consequently, enterprises are prioritizing unified data foundations that support predictive analytics and more ambitious AI initiatives. To address these needs, many organizations are partnering with service providers to modernize data architectures while simultaneously advancing analytics and AI programs.
“U.S. enterprises are no longer experimenting with analytics and AI at the margins,” said Kathy Rudy, partner, ISG Data, Analytics and Technology Office. “They are embedding these capabilities into how decisions are made, processes are automated and performance is measured across the organization.”
At the same time, AI investment continues to accelerate. ISG reports that AI spending as a percentage of total IT budgets has nearly tripled over the past two years, reaching close to 6 percent. As enterprises shift AI initiatives from pilot phases into full-scale production, they are reassessing how data, analytics, and AI function across business units. Many large organizations are now adopting formalized operating models for advanced analytics and AI (AAAI), consolidating leadership, governance, and architectural ownership at the enterprise level.
In contrast, midsize enterprises are often taking a more flexible approach. According to ISG, these organizations frequently adopt hybrid operating models that balance centralized oversight with domain-level autonomy. By empowering business-unit leaders to steward AAAI initiatives, midsize firms allow innovation to progress at different speeds. Notably, midsize service providers support this strategy by offering accelerators, pre-configured data models, and adaptable migration frameworks.
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Meanwhile, specialist analytics and AI providers are playing an increasingly critical role. These firms focus on high-value and regulated data types such as customer data, supply chain telemetry, competitive intelligence, and clinical datasets. Their deep vertical expertise spans industries including healthcare, financial services, manufacturing, and digital commerce.
“Enterprises are under increasing pressure to connect analytics and AI investments to measurable business results,” said Gowtham Sampath, principal analyst, ISG Research, and lead author of the report. “The organizations making progress are those that treat data, analytics and AI as a continuous operational capability rather than a series of projects.”
Beyond provider evaluations, the reports also highlight broader market trends, including the growing importance of organizational change readiness, process reengineering, and rising demand for consumption-based and outcome-linked pricing models. Collectively, the findings underscore how analytics and AI are evolving into long-term, value-driven capabilities across U.S. enterprises.
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