Get 360° clarity on your company’s AI readiness with our AI maturity assessment tool

Discover how prepared your company is to leverage AI for business growth. Get tailored recommendations for your next steps - strategy, data, infrastructure, skills, and governance.

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How this tool can aid your company's growth

Informed decisions

Get a clear picture of your AI readiness to make smarter investment choices and avoid misaligned initiatives.

Team alignment

Use this tool as a discussion starter for your team to align on goals, priorities, and the best path forward for your software’s future.

Gap identification

Easily spot capability gaps across strategy, data, infrastructure, and skills to focus your resources where they matter most.

Risk mitigation

Assess governance and ethical readiness to minimize risks, ensure compliance, and build trustworthy AI solutions.

Strategic focus

Translate AI ambitions into actionable steps with tailored recommendations specific to your maturity level.

Growth acceleration

Lay a solid foundation for scalable AI adoption that drives efficiency, innovation, and business growth.

About the tool: A comprehensive assessment for AI readiness

This self-assessment tool provides a structured framework to help your team evaluate your organization's readiness to implement AI-driven solutions effectively.

Designed for CTOs, CIOs, and IT decision-makers in SMBs, this tool guides you through key areas like strategic alignment, data maturity, technical capacity, and governance practices, offering a clear view of your AI enablement potential.

Assessment questions
Maturity radar
Tailored recommendations

Take the first step towards AI-driven growth

Download our free AI Capability Maturity Self-Assessment Tool and gain clarity on where your company stands in its AI journey. Identify strengths, uncover gaps, and get expert-backed recommendations to move from potential to implementation.

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Key dimensions when assessing your AI capability maturity

When determining how prepared your organization is to implement AI, it’s crucial to evaluate readiness from multiple perspectives. Reviewing your capabilities across these dimensions ensures your AI initiatives are aligned with business goals, resources, and operational needs.
Below are five critical areas to consider:

Ensuring AI initiatives are driven by clear business goals and supported by leadership
What to consider

Assess if AI is part of your strategic priorities, with executive sponsorship, defined KPIs, and allocated resources for AI-driven innovation.

Why it matters

Without leadership buy-in and a clear strategy, AI projects often lack direction, leading to wasted efforts and missed opportunities.

Example insight

If AI is seen as an IT experiment rather than a business enabler, aligning leadership and defining business-driven AI goals is a crucial first step.

Ensuring your data is clean, accessible, and governed to support AI initiatives
What to consider

Evaluate the quality, availability, and integration of your data, as well as governance policies for privacy, security, and compliance.

Why it matters

AI success depends on data quality. Poor data readiness can stall projects, introduce bias, and limit the effectiveness of AI solutions.

Example insight

If key data is siloed across systems or lacks proper governance, prioritizing data infrastructure improvements is essential for AI adoption.

Assessing if your IT environment can support AI workloads and scalability
What to consider

Review your cloud adoption, compute resources, and system architectures to ensure they are flexible and scalable for AI deployments.

Why it matters

An underprepared infrastructure can slow down AI initiatives, inflate costs, and hinder real-time processing capabilities.

Example insight

If your systems are legacy-bound or lack cloud-native capabilities, adopting Azure services can accelerate AI deployment and scalability.

Ensuring you have the right expertise and capacity to execute AI projects
What to consider

Identify internal AI/ML skills, upskilling initiatives, and availability of external partners to support AI initiatives effectively.

Why it matters

Without the right skills, even well-planned AI projects can fail to deliver. Building or accessing expertise is key to successful implementation.

Example insight

If your team lacks AI experience, starting with pre-built AI services and external AI enablement consulting can bridge the gap while internal skills are developed.

Evaluating policies, risk management, and ethical considerations for AI use
What to consider

Assess the presence of AI governance frameworks, risk assessments, and ethical AI guidelines to ensure responsible adoption.

Why it matters

Proper governance reduces risks of bias, non-compliance, and reputational damage, ensuring AI adds value responsibly and sustainably.

Example insight

If AI initiatives are being implemented without formal governance, introducing oversight processes is critical to scale AI safely.

Tool limitations: When expert AI consulting is required

While this self-assessment tool offers a comprehensive starting point to evaluate your AI readiness, it is designed to spark informed discussions, not to replace expert guidance. AI initiatives often involve complex decisions that go beyond assessing maturity. Defining the right strategy, building custom solutions, and managing AI governance at scale require specialized expertise.

This tool helps you gain clarity, but consulting with AI professionals ensures your approach is aligned with business goals, resources, and technical realities.

Schedule a free 30-minute consultation with our AI consulting team to discuss your specific needs and map out the most effective next steps.

When AI opportunities are identified, but require validation through feasibility studies, ROI projections, and stakeholder alignment.

Why it’s critical:
AI without a clear business case risks becoming a costly experiment. Experts help prioritize use cases that deliver measurable value.

Expert benefit:
Consultants bring structured methodologies to align AI initiatives with strategic business outcomes.
When data is fragmented, unstructured, or lacks governance, making it difficult to build reliable AI models.

Why it’s critical:
Data quality directly impacts AI effectiveness. Experts assess your data landscape and recommend actionable improvements.

Expert benefit:
Specialists design scalable data architectures and ensure governance for AI-readiness.
When pilot projects succeed, but scaling AI solutions organization-wide becomes a challenge.

Why it’s critical:
Scaling requires robust infrastructure, change management, and continuous monitoring to maintain AI performance and ROI.

Expert benefit:
Consultants guide the transition from isolated pilots to enterprise-wide AI adoption strategies.
When AI projects raise concerns about ethics, bias, regulatory compliance, or risk management.

Why it’s critical:
Without governance, AI can introduce risks to brand reputation, legal compliance, and decision-making transparency.

Expert benefit:
Advisors help establish AI governance frameworks aligned with industry standards and best practices.
When off-the-shelf AI services fall short of addressing specific business challenges or innovation goals.

Why it’s critical:
Custom AI development requires deep technical expertise to ensure scalability, maintainability, and integration with existing systems.

Expert benefit:
Consulting teams design and implement bespoke AI solutions tailored to unique business needs.

Understanding AI implementation approaches

Data-driven AI

AI models trained on your company's own data to generate predictions, automate insights, or personalize experiences. Typical examples include demand forecasting, churn prediction, or recommendation engines.

Key features:
Leverages your proprietary data for competitive advantage. Highly contextualized and relevant to your business operations. Improves accuracy as more internal data is collected.

Ideal for:
Companies with well-structured, quality datasets. Businesses aiming for predictive analytics or operational optimization. Organizations seeking data-driven decision support.

Limitations:
Requires data readiness (clean, structured, accessible data). Needs expertise in data science and machine learning. Longer implementation cycles compared to plug-and-play services.

Pre-built AI services

Ready-to-use AI capabilities provided as APIs or cloud services, such as Azure Cognitive Services (vision, speech, text analysis, chatbots).

Key features:
Quick deployment with minimal coding required. Covers common AI functions: image recognition, language processing, document analysis, etc. Scalable and maintained by cloud providers.

Ideal for:
SMBs starting with AI and seeking quick wins. Companies needing AI-powered features without full-scale AI teams. Use cases with standard AI tasks (e.g., automated support, document scanning).

Limitations:
Limited customization for unique business needs. Dependent on third-party providers’ service offerings. May not provide deep competitive differentiation.

Custom AI solutions

Tailor-made AI applications designed to address specific business challenges, workflows, or innovation initiatives unique to your organization.

Key features:
Fully customized to fit your processes and goals. Supports complex, industry-specific AI use cases. Provides long-term strategic advantage through differentiation.

Ideal for:
Organizations with advanced AI maturity. Businesses pursuing AI-driven innovation or new product development. Companies with unique operational challenges not solved by off-the-shelf solutions.

Limitations:
Higher development costs and longer time-to-market. Requires close collaboration with AI experts and development teams. Involves ongoing maintenance and iterative improvements.

Next steps: A practical AI enablement path

This tool helps your team evaluate your organization's AI readiness from multiple perspectives. Review each question, understand how your current capabilities align with AI best practices, and use the results to guide your next steps. If the outcomes are unclear or advanced expertise is needed, consult our specialists for tailored AI strategies.

Complete the assessment

Evaluate your AI readiness by answering targeted questions across strategy, data, infrastructure, skills, and governance dimensions.

Review results

Analyze your maturity scores to identify strengths, gaps, and priority areas for AI-driven improvements.

Align with your team

Use the assessment outcomes to foster team discussions, align AI goals with business priorities, and build a shared vision.

Consult AI experts

For complex AI initiatives, scaling strategies, or custom solution design, book a consultation with our AI enablement team for expert guidance.

Intuitive to complete. Easy to interpret & act upon.

Why consult CIGen

At CIGen, our commitment is clear: we prioritize our clients, maintain open communication, embrace cutting-edge technology, and foster strong partnerships. This approach ensures we deliver exceptional value and drive mutual success.

Client-centric approach

Your vision is our mission. We prioritize your needs and work closely with your team to ensure our solutions propel your business forward.

Transparency and communication

We believe in open, honest communication throughout the project lifecycle. You'll have full visibility into progress, challenges, and decisions at every step.

Cutting-edge technology

As Azure Cloud experts, we utilize the latest technologies and methodologies to deliver solutions that are not just effective but also future-proof.

Partnership and collaboration

We see ourselves as an extension of your team. Our collaborative approach ensures we're working together towards your success, every step of the way.

Get AI capability maturity self-assessment tool
Download our free AI Capability Maturity Assessment Tool and schedule a 30-minute no-obligation consultation with our AI enablement team.

Together, we’ll create a tailored roadmap to enhance your AI readiness, align with your business goals, and maximize ROI.
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