OvalEdge AI Readiness
Assessment Results

Your organization’s AI strategy needs significant development. To broaden AI opportunities, begin by aligning AI initiatives with business goals, securing leadership support, and establishing high-priority use cases.

Your AI strategy is in its early stages, so remember to define priorities based on use cases, value, and feasibility. Leadership buy-in has a major impact during this planning stage.

Your AI strategy is progressing, but there might be gaps in use cases or operational processes. Improving these areas will strengthen your strategy to better support AI implementation.

Your AI strategy has defined priorities and leadership support, though minor refinements in use cases or processes could enhance alignment. A few adjustments will optimize your position for AI success.

Your organization is exceptionally prepared for AI, with leadership buy-in, clear priorities, and comprehensive use cases. With strong AI leaders and operational processes in place, your organization is embedding AI into the company’s fabric.

Your organization needs significant development to prepare its workforce for AI. Invest in comprehensive training, hire AI experts, and implement change management practices to build a company culture ready for AI adoption.

Your workforce is in the early stages of AI preparation. Workforce training, upskilling, hiring AI specialists, and change management are all time-intensive tasks, so be sure to factor this into your plans moving forward.

Your organization is making progress in preparing its workforce for AI. Strengthening workforce training and change management activities helps to better support AI initiatives and drive innovation.

Your workforce is prepared for AI through solid training and change management efforts. There may be additional opportunities to enhance AI expertise or engage more deeply in change management, but you are on track to empower your team effectively.

Your workforce is exceptionally prepared for AI with thorough training and change management efforts. Strong retraining and upskilling programs are in place, and your company culture supports AI innovation and experimentation.

Your organization’s data needs significant development for effective AI implementation. Address any gaps in data centralization, governance, metadata management, data quality, and classification to build a strong foundation for AI.

Your organization’s data is in the early stages of becoming AI-ready. To advance readiness, focus on centralizing data, defining governance roles, and enhancing metadata and quality management.

Your organization is making progress in data readiness for AI initiatives. Strengthening dataquality processes and classification practices will better support effective AI.

Your data readiness is strong, with implemented progress in centralizing data, defining roles and responsibilities, curating metadata, ensuring high-quality data, and classifying data. Further strengthening data quality processes and classification practices will better support effective AI.

Your data readiness is exceptionally prepared for AI, with well-centralized data sources, clearly defined governance roles, and comprehensive metadata management. High-quality data processes and effective bias prevention measures are in place, ensuring top-tier AI support.

Your organization needs significant development in technology and infrastructure to meet the strenuous demands of AI. Invest in essential hardware, software, and robust data systems to build a scalable foundation for supporting AI initiatives.

Your technology and infrastructure are not optimized for AI initiatives. To better support AI solutions and scalability, improve hardware, software, and data accessibility to accommodate AI’s stringent demands on tech.

Your progress in technology and infrastructure for AI is developing, but gaps in scalability or data accessibility may need attention. Address these areas to ensure your infrastructure supports effective scaling and delivery of AI solutions.

Your technology foundation for AI is strong, with essential hardware, software, and scalability in place. Consider opportunities for optimization or additional investment for scaling AI further.

Your organization’s technology and infrastructure are exceptionally equipped for AI. Your network, storage, and backup systems are well-established, and you are prepared to scale AI operations.

Each stage of AI readiness relies on the others to create comprehensive AI initiatives within the organization. If one stage is significantly behind in development, the entire AI implementation will lag. Focus efforts on bringing everything up to the same speed and progressing together. An AI readiness roadmap can significantly help by clearly laying out the necessary efforts for progress!