Asheville powers up its data analytics office -- GCN
This article covers the efforts made by the city of Asheville to update the technology in its data analytics office and the benefits that the city has enjoyed as a result.
What is driving the growing focus on data analytics and AI?
Several trends are pushing data analytics and AI to the top of the agenda for both businesses and governments:
- Exploding data volumes: Scientific research, consumer behavior, and digital services are generating vast and often vague datasets. Turning this raw data into decisions requires more advanced analytics and AI tools.
- Need for faster, better decisions: From retail to energy and public safety, organizations want to move from static reporting to real-time, data-informed decision-making.
- Infrastructure investments: Federal supercomputing funding in the U.S. is boosting national data capacity for scientific research, while in Europe, KKR and Oak Hill have pledged $2 billion to expand data center capacity as AI workloads surge.
- Policy and ecosystem support: The EU is unveiling new research data infrastructure to improve AI access to trusted datasets, and countries like Ireland are committing €5.7 million to expand national AI centers that support Europe-wide digital innovation.
Together, these forces are reshaping how organizations think about data: not just as a byproduct of operations, but as a core asset that can reimagine products, services, and research outcomes.
How are companies using AI-powered data platforms in practice?
Organizations are moving beyond experimentation and putting AI-powered analytics into day-to-day operations in several ways:
- Business intelligence and master data: Companies like Crisp are rolling out AI-powered master data analytics platforms to enhance business intelligence. These platforms help clean, unify, and analyze data from multiple sources so leaders can trust the numbers behind their decisions.
- Customer experience and retail: JD Sports is deploying an AI-driven shopping platform for U.S. customers. By analyzing customer behavior and preferences, the platform can personalize product recommendations and streamline the online shopping journey.
- Cloud analytics at scale: Google is introducing a fully managed remote MCP server offering for BigQuery users, making it easier for teams to run large-scale analytics workloads without managing complex infrastructure.
- Industry-wide experimentation: At major global technology exhibitions and events like CES 2026, AI-led, highly scalable technologies are taking center stage. Many technology companies reported using AI tools extensively in 2025 and seeing positive, measurable outcomes in efficiency and innovation.
These examples show a shift from AI as a side project to AI as a core capability embedded in analytics, operations, and customer-facing platforms.
What new infrastructure is emerging to support AI and data-intensive research?
To keep up with AI and data-heavy workloads, both public and private sectors are investing in new infrastructure and programs:
- AI supercomputing architectures: NVIDIA has introduced its Vera Rubin AI supercomputing architecture at CES 2026, designed to handle demanding AI and data analytics workloads at scale.
- National and federal capacity: Federal supercomputing funding in the U.S. is increasing national data capacity for scientific research, enabling researchers to process and analyze massive datasets more efficiently.
- Mission-focused AI research: The Department of Energy has established the Genesis mission consortium to fast-track AI-powered breakthroughs in scientific research, bringing together expertise, data, and compute resources.
- European data and AI infrastructure: The EU is launching new research data infrastructure to improve AI access to trusted datasets, while European data centers are expanding rapidly, supported by a $2 billion pledge from KKR and Oak Hill to meet rising AI workload demand.
- National AI centers: Ireland is investing €5.7 million to expand its National AI Centre (CeADAR), strengthening Europe-wide digital innovation and providing a hub for applied AI research and industry collaboration.
These efforts are rethinking the foundations of data and AI work—combining compute power, high-quality datasets, and collaborative programs to help organizations move from raw data to actionable insight.
Asheville powers up its data analytics office -- GCN
published by GovDirect
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