AI Strategy & Transformation Roadmap — The 5 Phases (+ Optional Pilot Phase)
Designed for Microsoft, Snowflake, and Databricks Modern Data Platforms
1. Data & Business Landscape Assessment & Strategic Alignment
We assess your current data estate across Microsoft, Snowflake, and Databricks to understand readiness, gaps, and where AI can deliver measurable value.
Steps:
- Evaluate Azure/Fabric, Snowflake, and Databricks data maturity
- Review Power BI, Synapse, Purview, Unity Catalog, and governance layers
- Identify business processes suited for AI augmentation
- Interview stakeholders across business and IT
- Define AI objectives aligned to your modern data platform
2. Modern AI‑Ready Architecture & Operating Model Design
We design an AI‑ready architecture that leverages the strengths of Microsoft, Snowflake, and Databricks—ensuring scalability, governance, and responsible AI adoption.
Steps:
- Define AI architecture using Azure OpenAI, Snowflake Cortex, or Databricks Mosaic AI
- Establish governance with Purview, Unity Catalog, or Snowflake governance tools
- Create standards for data access, lineage, and quality
- Identify required roles, skills, and operating rhythms
- Document the enterprise AI blueprint aligned to platform best practices
3. Use Case Discovery, Prioritization & Value Modeling
We identify and prioritize AI use cases that align with your platform—leveraging Azure OpenAI, Snowflake ML, Databricks MLflow, or Copilot extensibility.
Steps:
- Facilitate AI use‑case discovery workshops
- Score use cases across value, feasibility, and data readiness
- Model ROI using platform‑native AI and automation capabilities
- Prioritize quick wins vs. strategic enterprise initiatives
- Build a balanced, achievable AI use‑case portfolio
4. AI Roadmap Development & Implementation Planning
We translate strategy into a clear roadmap that sequences AI initiatives across Microsoft, Snowflake, and Databricks.
Steps:
- Define phased implementation timelines
- Map dependencies across Azure, Fabric, Snowflake, and Databricks
- Identify required tools, services, and platform capabilities
- Build a multi‑year roadmap aligned to business and platform goals
- Provide executive‑ready recommendations and investment guidance
5. Governance, Risk Management & Responsible AI Frameworks
We implement responsible AI frameworks using Microsoft, Snowflake, and Databricks governance capabilities to ensure safe, secure AI adoption.
Steps:
- Define Responsible AI guardrails using Microsoft and industry frameworks
- Establish model monitoring, validation, and auditability
- Implement governance with Purview, Unity Catalog, or Snowflake governance
- Create lifecycle processes for model deployment and oversight
- Provide training and enablement for responsible AI adoption
6. (Optional) AI Pilot Execution & Value Realization
We help you launch targeted pilots using Azure OpenAI, Snowflake Cortex, Databricks Mosaic AI, or SLM‑based prototypes to validate value and build momentum.
Steps:
- Select pilot use cases aligned to your platform
- Build proof‑of‑concept models or copilots using Azure, Snowflake, or Databricks
- Validate performance, accuracy, and business impact
- Measure ROI using Fabric, Snowflake, or Databricks analytics
- Recommend next‑step scaling and enterprise rollout
