“How Ready Is Your Business for Scalable Enterprise AI?”

Take the AI Maturity Assessment Now

AI Maturity Assessment Framework

Take our quick, 5–10 minute AI Assessment to uncover actionable insights on your organization’s current AI maturity, key gaps, and opportunities. You’ll also understand the next steps to accelerate your AI journey — and how to align it with your business priorities.

AI Assessment

Step 1 of 5

20%

Name(Required)

First

Email(Required)

Designation(Required)

Vision, Strategy & Leadership

Understand the level of strategic alignment, vision, and executive buy-in.

1. Does your organization have a clear vision for AI adoption?(Required)

Not Started

In-progress

In-review

Completed

2. Is there a formal strategy in place to integrate AI into core business operations?(Required)

In-progress

In-review

Completed

3. Have senior stakeholders and sponsors been identified to champion AI initiatives?(Required)

Partially identified

Ongoing

Fully identified

4. Have specific, measurable outcomes for AI initiatives been defined?(Required)

In-progress

In-review

Completed

Roadmap, Prioritization & Use Cases

Evaluate your ability to identify, prioritize, and implement meaningful AI use cases.

5. Has your organization developed a comprehensive roadmap for AI implementation?(Required)

Partially developed

Ongoing

Fully developed

6. Are AI use cases prioritized based on impact, feasibility, and business value?(Required)

Partially done

Ongoing

Fully done

7. Do you have established timelines, milestones, and resources for AI implementation?(Required)

Partially done

Ongoing

Complete

8. What is your current focus area for AI implementation? (You can select multiple options using CTRL)(Required)

i. Developer productivity (e.g., code generation, test automation)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

ii. Internal automation (e.g., HR, finance, legal)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iii. Operational excellence & Business productivity (e.g., service elevation, forecasting, process optimization)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iv. Customer experience (e.g., chatbots, agents, assistants, sentiment analysis)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

v. Analytics & decision support (e.g., dashboards, reports, anomalies)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

Data, Infrastructure & Governance

Understand foundational readiness to support responsible, scalable AI.

9. Is your data infrastructure (e.g., data lakes, pipelines) AI-ready and scalable?(Required)

Partially done

Ongoing

Complete

10. Do you have robust data governance, security, and compliance controls in place?(Required)

Partially done

Ongoing

Yes

11. Are ethical AI practices (e.g., fairness, transparency, explainability) embedded into your initiatives?(Required)

Partially done

Ongoing

Yes

Execution, Scaling & Continuous Improvement

Assess the degree of hands-on implementation, ROI, and model lifecycle maturity.

12. Have you piloted AI/ML use cases or scaled them in production environments?(Required)

No pilots yet

Early-stage pilots only

Limited production deployments

Nearing enterprise-wide deployment

13. What types of AI technologies are in active use? (You can select multiple options using CTRL)(Required)

i. Traditional ML (classification, regression, clustering)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

ii. Predictive analytics(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iii. Generative AI (text, image, code generation)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iv. NLP or Conversational AI(Required)

Not Started

Early Stages

In Progress

Fully Implemented

v. Automation (RPA, AIOps, cognitive services)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

14. Are you measuring tangible outcomes (cost savings, speed, accuracy, revenue impact)?(Required)

Partially done

Ongoing

Yes

15. Do you have a continuous improvement loop (e.g., MLOps, retraining, feedback loops)?(Required)

Partially done

Ongoing

Yes

Step 1 of 5

20%

Name(Required)

First

Email(Required)

Designation(Required)

Vision, Strategy & Leadership

Understand the level of strategic alignment, vision, and executive buy-in.

1. Does your organization have a clear vision for AI adoption?(Required)

Not Started

In-progress

In-review

Completed

2. Is there a formal strategy in place to integrate AI into core business operations?(Required)

In-progress

In-review

Completed

3. Have senior stakeholders and sponsors been identified to champion AI initiatives?(Required)

Partially identified

Ongoing

Fully identified

4. Have specific, measurable outcomes for AI initiatives been defined?(Required)

In-progress

In-review

Completed

Roadmap, Prioritization & Use Cases

Evaluate your ability to identify, prioritize, and implement meaningful AI use cases.

5. Has your organization developed a comprehensive roadmap for AI implementation?(Required)

Partially developed

Ongoing

Fully developed

6. Are AI use cases prioritized based on impact, feasibility, and business value?(Required)

Partially done

Ongoing

Fully done

7. Do you have established timelines, milestones, and resources for AI implementation?(Required)

Partially done

Ongoing

Complete

8. What is your current focus area for AI implementation? (You can select multiple options using CTRL)(Required)

i. Developer productivity (e.g., code generation, test automation)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

ii. Internal automation (e.g., HR, finance, legal)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iii. Operational excellence & Business productivity (e.g., service elevation, forecasting, process optimization)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iv. Customer experience (e.g., chatbots, agents, assistants, sentiment analysis)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

v. Analytics & decision support (e.g., dashboards, reports, anomalies)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

Data, Infrastructure & Governance

Understand foundational readiness to support responsible, scalable AI.

9. Is your data infrastructure (e.g., data lakes, pipelines) AI-ready and scalable?(Required)

Partially done

Ongoing

Complete

10. Do you have robust data governance, security, and compliance controls in place?(Required)

Partially done

Ongoing

Yes

11. Are ethical AI practices (e.g., fairness, transparency, explainability) embedded into your initiatives?(Required)

Partially done

Ongoing

Yes

Execution, Scaling & Continuous Improvement

Assess the degree of hands-on implementation, ROI, and model lifecycle maturity.

12. Have you piloted AI/ML use cases or scaled them in production environments?(Required)

No pilots yet

Early-stage pilots only

Limited production deployments

Nearing enterprise-wide deployment

13. What types of AI technologies are in active use? (You can select multiple options using CTRL)(Required)

i. Traditional ML (classification, regression, clustering)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

ii. Predictive analytics(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iii. Generative AI (text, image, code generation)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

iv. NLP or Conversational AI(Required)

Not Started

Early Stages

In Progress

Fully Implemented

v. Automation (RPA, AIOps, cognitive services)(Required)

Not Started

Early Stages

In Progress

Fully Implemented

14. Are you measuring tangible outcomes (cost savings, speed, accuracy, revenue impact)?(Required)

Partially done

Ongoing

Yes

15. Do you have a continuous improvement loop (e.g., MLOps, retraining, feedback loops)?(Required)

Partially done

Ongoing

Yes