Enterprise-wide digital threads and agentic AI systems enable self-optimizing operations and measurable outcomes, ISG Provider Lens® report says
Enterprises in the U.S. are integrating AI into digital engineering at scale, building self-optimizing autonomous ecosystems that encompass all physical assets and digital platforms, according to a new research report published today by Information Services Group (ISG) (Nasdaq: III), a global AI-centered technology research and advisory firm.
Leading enterprises in the U.S. are creating AI-based digital threads that link digital twins, processes and products, eliminating fragmentation and technical debt. This enables a profound shift toward systems that continuously translate data into action.Share
The 2026 ISG Provider Lens® Digital Engineering Services (DES) Midsize Providers report for the U.S. finds that organizations are replacing fragmented technology deployments with cohesive architectures that connect R&D, operations and customer functions, enabling real-time visibility and measurable performance improvements across the value chain. Midsize service providers play a critical role in this shift, contributing domain expertise and agility to help enterprises implement tailored solutions without the complexity of large-scale delivery models.
“Leading organizations in the U.S. are creating AI-based digital threads that link digital twins, processes and products, eliminating fragmentation and technical debt,” said Matteo Gallina, Americas lead, Digital Engineering Solutions, ISG. “This enables a profound shift toward systems that continuously translate data into action, identifying and correcting performance gaps even as requirements change.”
At the heart of this transition are agentic AI systems that automate complex workflows across multiple functions. These systems plan, execute and adjust processes in real time, reducing inefficiencies caused by disconnected data and manual intervention. They allow organizations to take full advantage of enterprise-wide data streams that inform automated decisions and actions. This approach enables continuous optimization of performance metrics such as cost efficiency and production speed while improving responsiveness to changing conditions.
Organizations are also prioritizing traceability and transparency in automated decision-making as regulatory expectations increase. Digital twins are central to this effort, serving as continuously updated representations of physical assets for design, monitoring and reporting purposes. At the same time, increased investment in smart manufacturing and connected infrastructure is enabling real-time coordination between physical systems and digital platforms.
Cloud strategies in the U.S. are evolving toward hybrid architectures that balance scalability with control over sensitive data and high-frequency workloads. Enterprises are placing critical AI inference closer to operations, using specialized silicon, while placing centralized analytics in the cloud. This strategy supports faster processing, reduced latency and improved system performance for mission-critical applications. It also enables tighter integration between digital platforms and physical operations, increasing enterprise agility, ISG says.
“The competitive advantage for enterprises is shifting from deployment of intelligent systems to coordinating how they operate across environments,” said Shirish Kulkarni, lead author of the report. “Midsize providers are acting as catalysts in digital engineering transitions, helping clients translate complex architectures into practical execution models.”
