Technology, Cloud & Digital Solutions

The quantum computing in the cloud market across the U.S. and North America is expected to grow from $1.2B in 2025 to $7.9B by 2030, reflecting a CAGR of 45.1%. Fueled by expanding R&D investments, cloud-based quantum services are moving toward commercial scalability. By 2030, over 70% of enterprises using advanced analytics will integrate quantum cloud access for optimization, simulation, and cybersecurity applications. Strategic partnerships between hyperscalers (AWS, IBM, Google Cloud) and quantum hardware startups are accelerating innovation cycles, while federal funding and corporate consortia are driving the U.S. toward leadership in quantum infrastructure and commercialization.

Edge-to-cloud integration is rapidly emerging as a cornerstone of IoT expansion in Asia-Pacific, especially in China and India. Spending is expected to rise from ~$2.0B in 2025 to ~$7.2B by 2030, driven by demand for real-time analytics and low-latency performance. Adoption will grow from 30% to 76%, led by industrial, manufacturing, retail, and logistics sectors. IoT-related costs are projected to drop by ~45%, while ROI improves from 12% to 30%. With benefits like faster processing and enhanced decision-making, and risks mitigated through cybersecurity and phased adoption, edge-to-cloud integration will become essential to APAC’s digital infrastructure by 2030.

North American enterprises are adopting AI-driven cloud optimization to manage costs, enhance reliability, and accelerate delivery across hybrid estates. Platform and services spend is expected to rise from ~$3.6B in 2025 to ~$13.6B by 2030. Key improvements include a 37% reduction in compute costs, lower idle waste (28% to 10%), increased rightsized workloads (42% to 78%), and faster MTTR (9.0 to 3.5 hours). Program IRR is projected to improve from ~10% to ~21%. The architecture includes telemetry ingestion, RL heuristics, and policy-as-code for budgets and SLAs. Risks like configuration drift and egress lock-in are mitigated with explainable recommendations and data mesh strategies. AI-driven optimization will create self-tuning cloud platforms with measurable cost and performance gains.