Examples of AI Readiness Report, Business Case for AI Adoption, and Data Quality & Infrastructure Assessment

When implementing AI in retail, documentation and structured analysis are key to ensuring success. Below are example templates for each essential document:

1. AI Readiness Report (Example Template)

Purpose: This report evaluates the retailer’s current technological capabilities, data quality, and business alignment for AI adoption.

Retailer AI Readiness Report

Company Name: [Retailer Name]
Date: [Date]
Prepared By: [AI Consultant / IT Team]

Executive Summary

• Overview of AI readiness assessment

• Key findings and AI maturity level

• Recommendations for next steps

Current AI Maturity Assessment

Key Barriers to AI Adoption

• Data inconsistency across different sales channels

• Lack of AI-skilled personnel to manage model training and insights

• Limited integration with cloud-based AI services

AI Readiness Score & Recommendations

• AI Readiness Score: 65/100 (Medium Readiness)

• Short-Term Focus: Data standardization and workforce training

• Long-Term Focus: Full AI integration for personalization and automation

2. Business Case for AI Adoption (Example Template)

Purpose: This document outlines the rationale for AI investment, potential ROI, and strategic impact.

Business Case for AI Adoption

Company Name: [Retailer Name]
Date: [Date]
Prepared By: [AI Consultant / IT Team]

Executive Summary

• AI adoption will enhance customer experience, operational efficiency, and profitability

• Estimated ROI: 20% cost savings in supply chain, 15% revenue increase from personalization

Problem Statement

• Current Challenges:

  • Low inventory turnover due to poor demand forecasting

  • High cart abandonment rates due to lack of personalized recommendations

  • Inefficient workforce scheduling leading to high labor costs

AI Solution Proposal

Implementation Plan

• Phase 1: AI Readiness Assessment (1-2 months)

• Phase 2: Pilot AI in high-impact areas (3-6 months)

• Phase 3: Scale AI across operations (6-12 months)

Financial Justification & ROI Analysis

• Projected AI investment: $550,000 over 12 months

• Expected annual savings & revenue growth: $1.2M

• ROI Projection: \>2x return within 18 months

Next Steps & Recommendations

• Finalize AI vendor selection

• Define AI governance policies

• Conduct pilot program in key areas (e.g., demand forecasting and personalization)

3. Data Quality and Infrastructure Assessment (Example Template)

Purpose: This assessment evaluates whether the retailer’s data is suitable for AI and identifies any gaps in infrastructure.

Data Quality & Infrastructure Assessment

Company Name: [Retailer Name]
Date: [Date]
Prepared By: [IT/Data Team]

1. Data Quality Assessment

2. Infrastructure Assessment

3. Data Governance & Security

• Data Privacy Compliance: GDPR and CCPA alignment required for AI personalization

• Access Control: Need role-based data access policies

• Data Integration Needs: API-based connectivity with third-party AI services

4. Recommendations

• Short-Term Fixes:

  • Clean CRM data to remove duplicates and standardize fields

  • Implement automated inventory tracking to reduce manual errors

• Long-Term Strategy:

  • Upgrade to cloud-based AI infrastructure for faster model training

  • Establish a real-time data pipeline to enhance AI-driven decision-making

Conclusion: Preparing for AI in Retail

AI adoption in retail requires a strong foundation in data quality, technology infrastructure, and business alignment. Before launching AI-driven personalization, automation, or analytics, retailers must:

• Assess AI readiness to determine current capabilities and gaps

• Build a business case that quantifies ROI and aligns AI with business goals

• Improve data quality to ensure AI models generate reliable insights

---

At Valere, we help retailers evaluate AI readiness, optimize data infrastructure, and implement AI strategies that drive real business impact. If you're ready to take the next step, visit valere.io for expert guidance on AI adoption in retail.