Enterprise AI Readiness & Strategy with Srikanth satturi

Enterprise AI Readiness & Architecture Strategy

Many organizations are rushing into GenAI, RAG, AI agents, and enterprise copilots before establishing the foundations required to run them reliably in production. I have seen and experienced such problems at a fortune 500 organization.

This session is designed for technology leaders, architects, engineering leaders, and founders who want to assess where their organization stands and identify the right path forward.

What we’ll evaluate

We will discuss your organization across five areas:

Business & Use Cases

Are you solving the right problems with AI? We’ll look at use-case prioritization, business value, feasibility, and measurable outcomes.

Data & Knowledge Readiness

Is your enterprise data accessible, trustworthy, governed, and structured appropriately for AI and RAG or Agentic workloads?

Architecture & Platform Readiness

We’ll examine your current architecture and discuss patterns for LLMs, RAG, agents, integrations, model gateways, evaluation, observability, and production deployment.

Security & AI Governance

We’ll identify potential gaps around enterprise data exposure, access control, privacy, model risk, auditability, and responsible AI.

Operating Model

We’ll discuss who should own AI capabilities, how platform and product teams should work together, and what capabilities are required to move from experimentation to production.

What you will leave with

By the end of the session, you should have:

• A clearer view of your organization’s AI readiness

• The major gaps that could block production AI adoption

• A prioritized view of what to address first

• Architecture and platform recommendations relevant to your situation

• Guidance on where RAG, agents, LLMs, traditional ML, or even non-AI solutions make sense

• Concrete next steps for moving from experimentation toward production

This is not a AI course but a strategy for enterprise AI adoption

The discussion is focused on architecture, engineering decisions, organizational readiness, and practical AI adoption.

Who this is for

Enterprise/solution architects, engineering leaders, AI leaders, and founders who are:

• Planning an enterprise AI initiative

• Moving from AI PoCs toward production

• Evaluating RAG or agentic architectures

• Building an internal AI platform

• Struggling to prioritize AI use cases

• Trying to understand what foundations need to exist before scaling AI

If you already have an architecture or AI strategy, bring it to the session. We can pressure-test it together and identify potential gaps, unnecessary complexity, and architectural risks.