A Guide To AI Readiness Assessment Frameworks

By 10Pearls editorial team

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Adopting artificial intelligence (AI) technologies has nearly limitless applications and benefits, but rushing into deployment is a surefire way to cause headaches down the road. It’s important to assess your organization’s AI readiness , or your ability (both technically and culturally) to successfully leverage and support AI technology.

This guide will discuss the importance of assessing AI readiness before buying or implementing an AI solution. It will also explain the two types of assessments and provide a list of example self-assessment questions before highlighting the benefits of engaging in an AI consulting session with an AI implementation partner.

AI consultant demonstrating an AI readiness assessment exercise
Blog contents

Understanding AI readiness levels

AI readiness can be broadly divided into the following categories:
  • Fully prepared: The organization has a well-defined strategy, robust computing and power infrastructure, AI-specific security policies and controls, a centralized and consistent data architecture, strong governance policies, internal expertise, and an AI-focused company culture.
  • Moderately prepared: The organization is well on its way to readiness, but lacks a few key components relating to staffing, infrastructure, or company buy-in.
  • Somewhat prepared: The organization has started implementing changes to support an AI deployment, but it does not have a clear strategy and has a lot of gaps in its architecture and policies.
  • Unprepared: The organization has just started exploring the possibility of AI technology for its use cases, but it hasn’t started implementing any changes yet.

An AI readiness assessment framework is designed to help organizations determine where they are in their AI journey and what gaps they need to fill to be fully prepared.

A guide to AI readiness assessment frameworks 

There are two basic types of AI readiness assessment frameworks: self-assessments conducted by internal resources and professional assessments conducted by external AI experts. There are pros and cons to each approach.

Self-assessments are inexpensive, and internal auditors have more institutional knowledge and context to help guide their answers. On the other hand, they may not have the specialized experience to know everything that an AI deployment entails and what the organization needs to do to prepare.

AI readiness assessments are performed by highly qualified experts who know exactly what questions to ask, what the answers mean, and how to fill any gaps. They are more expensive, however, and it can take some time for external auditors to get up to speed on an organization’s specific policies, practices, and infrastructure.

AI readiness self-assessment questions

Below are some example AI readiness categories and questions that you can use to guide the self-assessment process.

Strategy

A well-defined strategy is the necessary foundation for an organization’s AI readiness. An AI-ready organization will have an AI strategy that emphasizes clear ownership, measurable outcomes, and sustainable financial planning. 

  • Do you have an AI deployment strategy?
  • Has ownership of the AI strategy been clearly defined?
  • Are there mechanisms in place to measure the outcomes of the AI deployment?
  • Has the organization defined a sustainable funding strategy for AI deployment?

Infrastructure

AI deployments require powerful computing resources, scalable networks, and thoughtfully planned power architectures. An AI-ready organization has a robust infrastructure to support both current and future AI initiatives.

  • Is your current computing infrastructure flexible and scalable enough to adapt to the changing computational requirements of AI deployments?
  • Do you have robust computational resources (i.e., GPUs) configured and ready for AI workloads?
  • Does your organization have the ability to automatically allocate resources for AI workloads on demand?
  • Does your data center or cloud provider offer the low latency and high throughput needed for AI workloads?
  • Can your network adapt as the AI deployment’s data needs and complexity grow?
  • Do you have infrastructure in place to optimize your AI deployment’s power consumption?

Security

Protecting AI deployments from cyberthreats requires specific security controls and data governance policies. AI readiness is assessed based on the robustness of this security architecture. 

  • How would you assess your organization’s security awareness as it pertains to threats specific to AI systems?
  • Does your organization have security protocols in place to protect AI data in transit and at rest?
  • How would you rate your organization’s ability to detect and prevent adversarial attacks on AI systems?
  • Does your organization have the dynamic and granular access controls needed to secure AI systems and data?

Data

High quality data is the backbone of AI deployments. An AI-ready organization has sanitized, centralized datasets, as well as the tools and knowledge to use and integrate them effectively.

  • How centralized and consistent is your organization’s AI data?
  • Is your data processed and sanitized in preparation for the AI deployment?
  • Are there protocols for AI teams to seamlessly access and use data?
  • Are data processing, sanitization, and analytics tools well integrated with AI systems and data sources?
  • How would you rank your staff’s proficiency level with data and analytics tools?
  • Do you have quality and reliability checks in place to validate external data?
  • Does the organization have systems in place to ensure the accuracy of data used in AI deployments?

Governance

Ensuring transparency, privacy, and fairness is crucial to fostering ethical AI usage. A mature organization has policies and protocols in place to establish AI governance. 

  • How would you assess the organizational awareness of potential biases in AI datasets?
  • Do you have controls in place to detect biases in AI data?
  • What is your procedure for mitigating biases and a lack of fairness in AI datasets?
  • How transparent and explainable are the decisions made by your AI solution?
  • How would you rate your organization’s understanding of and adherence to global data privacy standards like GDPR and HIPAA?
  • Is your organization prepared to mitigate a potential data breach or privacy violation?

Talent

A successful AI deployment relies on qualified talent with the expertise to support and use it. An AI-ready organization has in-house staff who are proficient in chosen AI technologies as well as robust training protocols in place to upskill talent. 

  • Do you have enough in-house talent to successfully deploy AI systems and solutions?
  • How would you assess the proficiency of staff in using chosen AI technologies?
  • Has your organization invested in training programs to upskill new and existing employees in how to use and support AI technologies?

Culture

A successful AI deployment requires a complete cultural transformation across the organization. An AI-ready company culture prioritizes adaptability, speed, and accountability. 

  • How highly does your company prioritize AI deployment?
  • Have you received enthusiastic executive buy-in for all the changes required for AI deployment?
  • Have you received enthusiastic management and employee buy-in for all the changes required for AI deployment?
  • Are there robust change management practices in place to control the rapid changes involved in AI deployment?

Get a clear AI roadmap with a 10Pearls AI readiness assessment 

Knowing the right questions to ask is only part of the battle. Finding and interpreting accurate answers to these questions is a whole other challenge. If you lack the internal expertise to assess your AI readiness, working with a trusted AI consulting firm like 10Pearls is the best way to ensure the success of your deployment. Our AI experts will work closely with your organization to determine your current AI readiness and develop a clear roadmap to fill any gaps.

10Pearls uses the leading AI readiness assessment frameworks to guarantee the success of your AI project. Reach out today to schedule a risk-free consultation.

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