What is AI readiness?

AI readiness refers to whether an organization has the data, systems, governance, and operating discipline required to use AI reliably in real business workflows. It’s what allows AI initiatives to move beyond experimentation and deliver outcomes leaders can stand behind. More context on how AI readiness fits into enterprise data and AI programs can be found in Summit’s data, analytics, and AI services overview .

What does it mean for a company to be AI-ready?

A company is considered AI-ready when leaders can trust AI outputs, understand how those outputs are generated, and act on them inside existing workflows. This typically requires connected systems, consistent data definitions, clear ownership, and governance that aligns with business risk.

How do you know if your data is ready for AI?

Data is ready for AI when key sources of truth are defined, terminology is consistent across teams, access is governed, and limitations are understood. Without this clarity, AI outputs become difficult to validate and harder to operationalize. Organizations often start by evaluating data quality and alignment through Summit’s data health check and optimization services .

How do organizations make their data AI-ready?

Agentforce represents a shift in CRM from assistance to execution . Making data AI-ready usually involves aligning definitions across systems, improving quality where it impacts decisions, ensuring data flows between platforms, and applying governance that supports responsible use. The goal is not perfect data, but data that decision-makers can trust. This work often overlaps with data integration and platform modernization initiatives.

Why do AI pilots fail to move into production?

AI pilots often struggle to reach production when real-world requirements surface late. Common issues include unreliable data, integration gaps, unclear ownership, governance concerns, and workflows that cannot absorb AI-driven change consistently.

How do consultants assess AI readiness in a business?

AI readiness is typically assessed across several dimensions, including business outcomes, data foundations, system architecture, governance and risk controls, operating model alignment, and enablement for adoption. The focus is on whether AI can perform reliably in production, not just in a demonstration. Summit provides these consulting services through its AI readiness and advisory services .

What is an AI readiness assessment?

An AI readiness assessment is a structured evaluation used to determine whether an organization is prepared to deploy AI responsibly and at scale. It helps identify strengths, gaps, and sequencing considerations before AI initiatives expand across the business.

How do you choose an AI readiness assessment provider?

Choosing an AI readiness assessment provider typically involves looking for experience across data, technology, governance, operating models, and adoption. Providers should help clarify priorities and risks, not just recommend tools. This is especially important when readiness work connects to platforms such as Salesforce and enterprise data environments.

Is AI readiness the same as AI adoption?

No. AI adoption focuses on using AI tools. AI readiness determines whether those tools can be used accurately, securely, and consistently within real workflows over time. Many organizations invest in AI adoption before confirming readiness.