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    AI Readiness Assessment

    Evaluate your organization's preparedness to implement and scale AI initiatives across go-to-market operations, identify foundational gaps and opportunities, and establish a phased AI enablement road map.

    Category 1: Use Case Definition and Prioritization

    Define where and why AI should be deployed.

    1 Are high-impact use cases identified (e.g., lead scoring, forecasting)?
    Rate your organization:
    Not at all Fully implemented
    2 Do AI projects tie to core strategic initiatives of KPIs?
    Rate your organization:
    Not at all Fully implemented
    3 Are pilots or prototypes already running or planned?
    Rate your organization:
    Not at all Fully implemented
    4 Is there alignment on success criteria for AI initiatives?
    Rate your organization:
    Not at all Fully implemented

    Category 2: Data Infrastructure and Accessibility

    Ensure AI-ready data structure and availability.

    1 Is data centralized across CRM, marketing, finance, and support?
    Rate your organization:
    Not at all Fully implemented
    2 Are key fields structured and consistently populated?
    Rate your organization:
    Not at all Fully implemented
    3 How frequently is data cleansed or de-duplicated?
    Rate your organization:
    Not at all Fully implemented
    4 Is the current schema normalized and scalable?
    Rate your organization:
    Not at all Fully implemented
    5 Are integrations feeding real-time or near real-time updates?
    Rate your organization:
    Not at all Fully implemented

    Category 3: Technology Ecosystem and Integration

    Confirm platform compatibility and system flexibility for AI deployment.

    1 Are core systems API-accessible and integrated?
    Rate your organization:
    Not at all Fully implemented
    2 Are AI-powered tools (e.g., ChatSpot, Einstein, Gong) already in use?
    Rate your organization:
    Not at all Fully implemented
    3 Is there middleware to orchestrate data flows (Zapier, Workato, etc.)?
    Rate your organization:
    Not at all Fully implemented
    4 Can data be exported to BI, ML, or cloud tools (e.g., BigQuery Azure)?
    Rate your organization:
    Not at all Fully implemented
    5 Are workflows modular and automation-friendly?
    Rate your organization:
    Not at all Fully implemented

    Category 4: Team Readiness and Enablement

    Equip the team with knowledge and confidence to adopt AI tools.

    1 Has AI training or enablement been offered to GTM teams?
    Rate your organization:
    Not at all Fully implemented
    2 Are roles defined for managing AI tools and outcomes?
    Rate your organization:
    Not at all Fully implemented
    3 Is there openness to adopting data-driven or AI-supported workflows?
    Rate your organization:
    Not at all Fully implemented
    4 Are end users (sales, CS, marketing) aware of how AI will enhance vs. replace?
    Rate your organization:
    Not at all Fully implemented

    Category 5: Change Management and Culture

    Foster an adaptable environment that supports transformation.

    1 Is leadership communicating a clear AI vision or mandate?
    Rate your organization:
    Not at all Fully implemented
    2 Are there change management plans tied to AI adoption?
    Rate your organization:
    Not at all Fully implemented
    3 Do teams have experience adopting automation or major workflow changes?
    Rate your organization:
    Not at all Fully implemented
    4 Are there designated champions or early adopters?
    Rate your organization:
    Not at all Fully implemented

    Category 6: Governance, Risk, and Compliance

    Maintain control over ethical, legal, and responsible AI use.

    1 Are there data governance and AI use policies in place?
    Rate your organization:
    Not at all Fully implemented
    2 Is compliance with privacy regulations (GPSR, HIPAA) ensured?
    Rate your organization:
    Not at all Fully implemented
    3 Are model outputs documented and auditable?
    Rate your organization:
    Not at all Fully implemented
    4 Are safeguards in place for human-in-the-loop decisions?
    Rate your organization:
    Not at all Fully implemented

    Category 7: Measurement and Iteration

    Track AI performance and continuously optimize.

    1 Are there defined metrics to measure AI success?
    Rate your organization:
    Not at all Fully implemented
    2 Is performance benchmarking included in pilot programs?
    Rate your organization:
    Not at all Fully implemented
    3 Is feedback collected from users for model tuning or workflow improvements?
    Rate your organization:
    Not at all Fully implemented
    4 Are unsuccessful experiments analyzed and iterated upon?
    Rate your organization:
    Not at all Fully implemented

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