Accelerated Innovation

Providing Scalable GenAI Data and Compute Foundations

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Providing Scalable GenAI Data and Compute Foundations

Description

Scalable GenAI data and compute foundations ensure that AI workloads are supported by reliable, flexible, and high-performance infrastructure. This capability enables teams to provision, manage, and optimize the data pipelines and compute environments required for GenAI experimentation, development, and production.

Why it's Important

GenAI initiatives depend on massive, fast-access data and powerful, adaptable compute resources. Without a scalable foundation, efforts are quickly bottlenecked by infrastructure gaps, inconsistent environments, or performance issues. This limits the ability to experiment freely, scale prototypes, or deliver stable GenAI solutions at speed. A strong data and compute backbone empowers teams to launch more pilots, train larger models, and operate reliably across hybrid or multi-cloud environments-enabling broader innovation, faster time-to-value, and better ROI from GenAI investments.

Why it's Challenging @ Scale

  • Fragmented Infrastructure Ownership: Different teams often manage data and compute separately, leading to mismatches in capacity, performance, or readiness.
  • Inconsistent Environment Provisioning: Without automation, environments for experimentation and production can vary widely, creating instability.
  • Data Access and Quality Gaps: GenAI depends on large, clean, and well-structured data-which is often siloed, incomplete, or ungoverned.
  • High Cost of Scalability: Scaling GenAI workloads can drive exponential infrastructure costs without strong cost control and optimization mechanisms.
  • Tool and Platform Sprawl: Multiple GenAI tools and frameworks can overload infrastructure teams, making standardization and support difficult.

Complexity

High: Maturing this capability requires technical integration across data and compute layers, automation at scale, and alignment across IT, AI, and governance teams.

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Taking Action

Though most organizations begin their GenAI journey with significant knowledge gaps, there are targeted actions that can be taken to accelerate the process. Select your group’s current maturity, based on your assessment results, and act today.

The most important part of any journey is starting… To move from “Exploring” to “Experimenting”, focus on the following key actions:
  • Explore Key Concepts & Best Practices: Complete the GenAI Center of Enablement (CoE) Best Practices workshop (2 hrs.) to understand foundational key concepts and explore applied best practices.
  • Defining the vision and mission of a GenAI CoE.
  • Establishing governance and ownership structures.
  • Cataloging core services and support functions.
  • Communicating value and success metrics.
  • Planning the evolution and scaling of the CoE.
  • Define Your Action Plan: Outline concrete, prioritized steps your organization will take to implement GenAI Strategy.
  • Align on your Current State and define your Target State.
  • Create an actionable enablement plan.
  • Define target timeline and measures of success.
  • Deliver Quick Wins: Small, high-impact GenAI projects that can demonstrate tangible value in a short time frame.
  • Stand up a GenAI sandbox environment: Launch a basic compute and storage environment to support early testing and prototyping.
  • Pilot access controls and data governance practices: Apply lightweight security and compliance policies to protect shared GenAI resources.
  • Enable team-led infrastructure provisioning: Introduce basic infrastructure-as-code templates to allow self-service experimentation.
To move from Experimentation to “Lifting-Off”, prioritize the following actions:
  • Complete one or more of our Deep Dive Courses: Begin exploring key concepts and best practices, including:
  • GenAI Use Case Discovery & Prioritization Best Practices.
  • GenAI R&D Acceleration & Applied Innovation Best Practices.
  • GenAI R&D Acceleration & Applied Innovation Best Practices.
  • Enterprise GenAI Architecture & Tooling Best Practices.
  • GenAI Development Best Practices & Support.
  • Nail It Before You Scale It: Assess and optimize your solution or process before adopting it at scale.
  • Assess Your Proposed Solution or Process: Evaluate your current infrastructure against performance, scalability, and reliability goals.
  • Define in-scope Processes and Guardrails: Establish standards for data ingestion, compute allocation, and workload isolation.
  • Close any Data or Measurement Gaps: Ensure telemetry, usage metrics, and cost tracking are in place to support scaling decisions.
  • Define Your Adoption & Scaling Plan: Create a structured roadmap for how GenAI solutions will be rolled out across teams, workflows, or business units.
  • Define Your Phased Implementation Plan: Sequence the rollout of infrastructure components based on business priority and technical readiness.
  • Build Awareness and Finalize Enablers: Provide enablement sessions, documentation, and access guides for platform onboarding.
  • Operationalize Your Comms Plan: Communicate infrastructure availability, service-level expectations, and escalation paths to all users.
To move from Lifting-Off to “Accelerating”, prioritize the following actions:
  • Formalize Your Best Practices: Document and standardize what’s working to ensure consistent, scalable success across teams and use cases.
  • Establish platform usage guidelines: Create clear standards for environment setup, compute allocation, and data provisioning.
  • Publish infrastructure reference architectures: Provide reusable blueprints that align with security, compliance, and performance needs.
  • Integrate cost and usage tracking: Standardize tools and dashboards to monitor infrastructure consumption across teams.
  • Accelerate Your Adoption: Intensify efforts to embed GenAI across your organization by expanding use cases, increasing user engagement, and removing adoption barriers.
  • Expand infrastructure availability: Ensure that teams across business units have access to the compute and data services they need.
  • Enable self-service provisioning: Automate infrastructure requests to reduce wait times and support agile experimentation.
  • Optimize system performance at scale: Fine-tune compute allocation and storage throughput for large-scale model runs.
  • Celebrate Your Wins: Publicly acknowledge team accomplishments to build and sustain adoption momentum.
  • Showcase infrastructure success stories: Highlight internal wins where scalable foundations unlocked new GenAI capabilities.
  • Recognize enablement and operations teams: Celebrate the behind-the-scenes efforts that make scaling possible.
  • Create internal awards or spotlight moments: Use incentives and visibility to keep infrastructure teams engaged and motivated.
The “Accelerating” stage represents “Target State” for many capabilities. “Breaking Away”, on the other hand, suggests that the specific Capability represents a clear competitive advantage for your business.
  • Streamline & Embed: Integrate GenAI into core workflows while eliminating friction points to make usage seamless and routine.
  • Embed GenAI platforms into standard DevOps workflows: Ensure infrastructure provisioning is a natural part of CI/CD pipelines.
  • Centralize access through a unified portal: Provide a single interface for requesting, managing, and monitoring GenAI infrastructure.
  • Eliminate environment drift: Use templated environments and automation to ensure consistency across experimentation and production.
  • Leverage Automation: Use GenAI-powered tools and workflows to streamline repetitive tasks, enhance operational efficiency, and reduce manual effort.
  • Automate infrastructure scaling and deprovisioning: Dynamically allocate compute and storage based on real-time demand.
  • Enable event-driven infrastructure responses: Trigger resource adjustments based on usage thresholds or operational signals.
  • Implement self-healing infrastructure components: Use monitoring and automation to detect and resolve issues without manual intervention.
  • Evolve & Further Accelerate: Continuously refine GenAI strategies based on insights and outcomes, while expanding into more complex or high-impact use cases.
  • Continuously benchmark platform performance: Compare infrastructure efficiency against internal targets and industry norms.
  • Expand capabilities to support emerging workloads: Adapt infrastructure for multimodal models, streaming inputs, and fine-tuning needs.
  • Refactor for cross-cloud and edge enablement: Extend GenAI foundations to support hybrid, multi-cloud, and low-latency environments.

Key "Watchouts"

As you take action you’ll want to avoid:

  • Overbuilding infrastructure too early: Investing in scale before understanding actual needs can lead to waste and complexity.
  • Underestimating cross-team coordination needs: Success depends on close alignment between infrastructure, data, and product teams.
  • Ignoring cost governance in early stages: Unchecked experimentation can lead to runaway spend without proper controls.
  • Neglecting monitoring and observability: Without usage visibility, it’s difficult to optimize performance or detect issues.
  • Failing to standardize environments: Ad-hoc setups create instability and slow down experimentation and deployment.

Targeted Benefits

While Providing Scalable GenAI Data and Compute Foundations can be challenging, its benefits are clear and compelling, including:

  • Faster GenAI experimentation cycles: Ready-to-use infrastructure enables teams to test ideas without long setup delays.
  • Greater ability to scale successful pilots: Infrastructure readiness allows for seamless transition from prototype to production.
  • Improved infrastructure cost-efficiency: Centralized monitoring and right-sizing help maximize ROI on compute and storage.
  • Higher reliability and performance for GenAI: Consistent infrastructure supports stable, responsive model operations.
  • Accelerated time-to-value from GenAI initiatives: Scalable foundations remove bottlenecks and support enterprise-wide momentum.

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Eddie
Accelerated Innovation

Hi, I'm Eddie 👋

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