Is your business unit really ready for artificial intelligence?

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ARTICLE | November 02, 2025

Artificial intelligence adoption is a competitive necessity. According to RSM’s Middle Market AI Survey 2025: U.S. and Canada, 91% of organizations use generative AI in some part of their business. Yet many leaders remain stuck in pilot purgatory, testing AI use cases without knowing how to scale, govern or measure business impact.

Our downloadable AI readiness checklist is designed to help you cut through the uncertainty. By evaluating your organization across eight essential dimensions—business and strategy readiness, process readiness, technical architecture, data readiness, talent and skills, governance and policies, security and risk, organizational alignment—you’ll see where your business unit stands and where action is needed.

AI readiness drives AI success

AI is transforming how organizations operate. The question isn’t if you should act—it’s whether your organization is ready to act with confidence.

Checklist of key questions

1. Business and strategy readiness

  • Do we have a clear strategy for where AI will create measurable business value, and is leadership aligned on the roadmap?
  • Have we identified relevant AI use cases for our industry and business unit?
  • Do we have a formal intake process to evaluate and prioritize AI ideas?
  • Have we conducted an ROI analysis to forecast value and gain leadership buy-in?
  • Can we tie AI opportunities to measurable productivity gains or revenue impact?
  • Do we have a roadmap that aligns AI adoption with our overall business strategy?

2. Process readiness

  • Are our core processes documented, standardized and understood well enough to automate tasks and augment with AI?
  • Have we mapped and documented key processes?
  • Are these processes standardized, repeatable and consistent across the business unit?
  • Have we identified pain points and inefficiencies at the root cause?
  • Do we understand the complexity of the decisions and the intelligence needs of these processes?
  • Have we assessed the data dependency and availability needed for AI enablement?

3. Technical architecture

  • Can our current technology support scalable, integrated AI solutions without major disruption?
  • Do we have an up-to-date system inventory and landscape?
  • Are integration capabilities in place (e.g., ETL tools, APIs, data lake)?
  • Are we operating in the cloud or on premises with sufficient computing power and storage?
  • Can our infrastructure support scalable AI solutions?
  • Do we have monitoring and maintenance processes in place for AI systems?

4. Data readiness

  • Is our data accurate, trusted and accessible enough to fuel AI models that drive real decisions?
  • Is there a clear data model and schema that aligns with AI needs?
  • Have we mapped data flows, lineage and dependencies?
  • Do we maintain a single source of truth across systems?
  • Are metadata and master data management frameworks in place?
  • Are we addressing data quality, availability and accessibility for AI?

5.Talent and skills

  • Do we have the right mix of people to build, manage and use AI effectively across the business?
  • Do we have internal staff with the required technical AI skill sets?
  • Are business unit leaders trained to recognize and evaluate AI opportunities?
  • Do we have training or upskilling programs in place for employees?
  • Have we considered managed services or outsourcing where skills are lacking?
  • Are roles and responsibilities clear for building, maintaining and using AI?

6. Governance and policies

  • Do we have clear guardrails and accountability for AI use covering ethics, compliance and change management?
  • Have we established an AI and automation governance policy?
  • Do we have an AI oversight committee (including IT, human resources and compliance)?
  • Have we updated security and privacy policies for AI risks?
  • Is there a change management and communication plan in place for AI adoption?
  • Have we created ethical use guidelines to address bias, fairness and transparency?

7. Security and risk

  • Are we prepared to manage the new risks AI introduces, from cybersecurity to regulatory exposure?
  • Are our cybersecurity frameworks updated for AI-related risks?
  • Do we assess and monitor risks around data leakage and model integrity?
  • Are compliance requirements (i.e., industry, regional, global) addressed?
  • Do we have plans for AI incident response and recovery?
  • Are vendor and third-party AI usage properly evaluated and secured?

8. Organizational alignment

  • Is there broad sponsorship and cultural readiness across business units to adopt AI in a way that augments people and aligns with enterprise priorities?
  • Have we secured leadership sponsorship for AI initiatives?
  • Are stakeholders across business units aligned on AI goals?
  • Do we communicate clearly about AI’s role in augmenting—not replacing—jobs?
  • Have we built a culture of experimentation and innovation around AI?
  • Do we link AI initiatives to enterprise priorities (e.g., run, grow, protect the enterprise)?

Frequently asked questions

What is an AI readiness checklist?

An AI readiness checklist is a structured framework that helps your business assess your preparedness for adopting AI. It evaluates key factors such as strategy, data, governance, talent and risk to determine whether your organization is ready to scale AI initiatives.

Why is AI readiness important?

AI readiness is critical because many organizations remain stuck in pilot projects without seeing measurable ROI. By assessing readiness, you can identify gaps, secure leadership alignment and build an adoption roadmap that encourages scalable and responsible AI implementation.

How can this AI readiness checklist help my business?

This 48-point AI adoption assessment provides actionable insights into your strengths and weaknesses across eight dimensions. It helps you move beyond pilots, reduce risk, improve governance and unlock the full value of AI for productivity, growth and innovation.

Who should use an AI readiness checklist?

Executives, technology leaders and business unit managers who are evaluating AI opportunities should use an AI readiness checklist. It’s especially useful for aligning stakeholders and helping AI adoption support the broader business strategy.

What are the next steps after completing the checklist?

Once you have a clear view of where your organization stands, the next step is to build a roadmap for adoption—prioritizing areas that deliver measurable business impact while addressing governance, compliance and risk management.

Please connect with your advisor if you have any questions about this article.

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Source: RSM US LLP.
Reprinted with permission from RSM US LLP.
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