How to Conduct an AI Readiness Assessment for Your Business

CEOs widely recognize leveraging AI to help businesses grow and become more profitable as a well-known strategy. According to recent research by Kearney, 89% of CEOs acknowledge the strategic importance of leveraging AI for business transformation. However, just one in four feel fully prepared to integrate it across their organizations.

AI readiness extends far beyond just buying software. It requires a strategic review across multiple dimensions of your business, including technology infrastructure, data maturity, tool utilization, people and processes, and governance and security.

When conducting an AI technology readiness assessment, consider leveraging these five pillars of AI readiness:

1. Connectivity & Infrastructure

Evaluate your network for bandwidth and uptime. AI workloads require reliable, high-speed connections to process large datasets and perform data analysis in real-time. Test your network by simulating increased data loads to identify weaknesses.

Evaluate your current servers, networking equipment, and storage capabilities to ensure they can handle the data throughput and demands that various AI tools require. Review your company’s use of cloud resources and data centers to determine if they meet your current needs. Determine how these resources can scale as you implement AI across business functions and demands increase over time.

After you conduct a thorough review of your organization’s connectivity and infrastructure, compare your findings to industry standards so you can identify gaps and understand where you need additional improvements. With this information, create a project roadmap to address all additional requirements before you fully integrate AI into your business.

2. Data Maturity

When assessing data maturity throughout your organization for AI technology, you need to go beyond the traditional “fit-for-use” assessment, as many organizations have built systems that operate independently of each other and may not meet the same requirements as AI systems.

Consider leveraging a data maturity model that enables analysis of data, breaking it down into maturity levels from siloed and unmanaged to fully integrated, fully managed, and high quality. Cover dimensions such as governance, accessibility, and integration into current systems. This type of assessment will enable you to identify weaknesses and gaps so you can develop a remediation plan to prepare for full AI technology integration.

Data that reaches sufficient maturity for AI technology should have the following characteristics:

Accessible, available, and used as a trusted source throughout the organization
Accurate, timely, and represents “the single version of the truth”
Governed with clear ownership of management, sourcing, and cleansing

AI technology requires high data maturity to learn, train, and perform—especially when generating actionable insights and advanced analytics.

3. Tool Landscape

A critical component of an AI technology readiness assessment ensures that any candidate tools you select can integrate with existing systems. If they don’t, you’ll need to identify gaps and plan remediation activities. Ideally, your organization’s tool landscape should support both current and future AI initiatives.

Steps to evaluate your tool landscape:

Inventory existing tools and infrastructure, including SaaS capabilities, cloud platforms, hardware, software, data management systems, and any AI-adjacent tools
Understand the current state architecture, including process and data flows, to identify integration points
Define both business and technical requirements by engaging with stakeholders from across the business
Research available AI tools based on use cases. Evaluate each using consistent criteria: integration, scalability, usability, functionality, and security

Any candidate tool should align with the business strategy and scale to meet future growth.

4. People and Process

When you deploy AI technology within your organization, your team’s skills and abilities, along with your current processes, will play a crucial role. A team equipped with the right skills and knowledge will ensure reliable and effective integration. Additionally, clearly defined processes will highlight areas where AI can enhance or transform your business.

Realistically, not everyone will reach the same skill or knowledge level when you deploy AI technology. Determine your organization’s training needs so that employees know how to effectively use AI in their specific roles and daily workflows. Consider training beyond daily routines, including prompting, agentic approaches, and automation awareness.

Support change by developing a communications plan that informs employees about what’s coming and how it could affect them.

You should also document processes well, and governance, compliance, and risk controls should account for the specific challenges and responsibilities AI will bring.

5. Governance and Security

The final pillar of AI readiness ensures your governance structures and security controls can support AI deployment.

Many organizations establish a governance committee to oversee implementation and monitor the outputs of AI tools used throughout the organization. Leadership typically tasks these committees to carry out the AI strategy and provide regular updates.

Governance should include published policies that address fairness, explainability, and security. Some companies create their own internal standards, while others adopt frameworks such as the OECD AI Principles or Microsoft’s Responsible AI Standard. You should review policies regularly to reflect the evolving capabilities and risks of AI.

Security considerations include:

Data: Assess integrity from ingestion through output
Infrastructure: Confirm that you have updated and securely configured systems
Architecture: Evaluate vulnerabilities and consider zero-trust approaches
Access controls: Enforce authentication and monitor unusual access behavior
Incident response: Have protocols in place for detection, containment, and recovery

Accelerate Your AI Journey with Expert Guidance

To help business leaders assess their AI readiness and accelerate adoption at scale, consider engaging a strategic partner like Cox Business to evaluate your infrastructure and chart a clear path forward.

Schedule Your Strategy Session Today →

Frequently Asked Questions (FAQs)

1. What is an AI readiness assessment for business?

An AI readiness assessment provides a detailed evaluation of your company’s infrastructure, data, tools, workforce, and governance to determine if you’re prepared to adopt, implement, and scale AI technologies effectively.

2. Why is data maturity critical for AI adoption?

AI systems rely on accurate and well-managed data to serve your business needs properly. Mature data allows AI to produce useful, reliable insights and prevent poor outcomes that low-quality or fragmented information causes.

3. How does infrastructure impact AI readiness?

AI workloads require robust, high-speed networks, reliable uptime, and scalable cloud infrastructure. Without these, AI processes can bottleneck or fail to perform in real time.

4. What tools should you review during an AI readiness assessment?

Your assessment should include a full inventory of SaaS platforms, cloud services, analytics systems, and integration tools. Evaluate how well they support interoperability, scalability, and data governance.

5. How do you prepare employees to use AI technology?

Provide AI upskill training based on employee job functions. Focus on the practical use of AI tools, automation awareness, prompting, and responsible AI use. Clear communication and documentation will also support adoption.

6. What governance and security practices do you need for AI?

Strong governance should include oversight committees, documented policies, and regular audits. Security protocols should address access controls, zero-trust architecture, and incident response plans for AI-specific risks.

7. How do I get started with AI readiness planning?

Begin by evaluating your organization using the five readiness pillars. Then build a roadmap to close gaps—ideally with help from a trusted partner like Cox Business who can support infrastructure, strategy, and implementation.

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Martin Jones

Martin Jones is a Senior Manager and Editor for CoxBLUE at Cox Business covering business technology, tech trends, news, and related interests including enterprise, small business, healthcare, hospitality, education and more.