Where Enterprise AI Runs
Exclusive 2026 research from BARC and Actian reveals how enterprises are rethinking where AI workloads run as they move from experimentation into production. Based on insights from 320+ enterprise respondents worldwide, the report explores why cloud remains the foundation for enterprise AI, why deployment beyond the cloud is gaining importance, and how organizations are balancing control, sovereignty, performance, cost, and complexity.
Enterprise AI is becoming a workload placement decision
76% say deploying AI outside the cloud has become more important in the past 12 months.
Cloud remains the dominant environment for enterprise AI. But as AI moves into production and becomes more business-critical, organizations are reconsidering whether cloud-only deployment is right for every workload.
Data sensitivity, business criticality, auditability, sovereignty, provider dependency, performance, and resilience are all shaping these decisions. The result isn’t a move away from the cloud. It’s a shift toward deliberate workload placement: choosing cloud, on-premises, edge, or a combination of environments based on the requirements of each workload.
This research examines:
- Why interest in deploying AI beyond the cloud is increasing
- How control, sovereignty, business criticality, and performance shape workload placement
- Where on-premises, edge, and hybrid architectures fit
- How organizations can make more deliberate AI architecture decisions
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What You’ll Learn
- Why cloud remains dominant even as interest in non-cloud AI grows
- Why data sensitivity and business-critical AI are changing infrastructure decisions
- How sovereignty, provider dependency, auditability, cost, performance, and resilience influence workload placement
- Where edge AI fits into enterprise architectures and the use cases driving adoption
- Why hybrid AI architectures are associated with higher AI maturity, and where they add operational complexity
- How to build a workload-specific approach to AI architecture across cloud, on-premises, and edge
Who Should Read This Report?
- CIOs, CTOs, CDOs, and AI leaders
- Enterprise and data architects
- Data & Analytics leaders
- AI/ML and platform leaders
- Data governance, security, and compliance teams
About the Research
This study is based on a quantitative online survey conducted in June and July 2026. The final analysis included 329 qualified respondents across industries and company sizes, primarily from Europe, North America, and Asia-Pacific.
The research examines the current relevance and strategic importance of cloud, on-premises, edge, and hybrid AI architectures, as well as the factors driving organizations to deploy AI outside the public cloud.
About BARC
BARC is the leading analyst firm for data & analytics, AI, corporate performance management (CPM), and ESG with a reputation for unbiased and trusted advice. Their expert analysts deliver a wide range of research, events, and consulting services for the data & analytics community. BARC’s innovative research evaluates software, vendors, and service providers rigorously and highlights market trends, delivering insights that enable their customers to innovate with data, analytics, and AI. BARC’s 25 years of experience with data strategy & culture, data architecture, organization, and software selection helps clients transform into truly data-driven organizations.