AI Readiness Survey - co-entrepreneur.net

AI Readiness Assessment Survey

Evaluate your organization’s preparedness for AI integration and adoption

According to McKinsey

63%

of organizations report revenue increases from AI adoption

Gartner predicts

85%

of AI projects will deliver erroneous outcomes due to bias by 2024

Deloitte found

76%

of executives expect AI to substantially transform their business within 3 years

This comprehensive assessment will provide a clear picture of your organization’s AI readiness across five critical dimensions. The results will help identify areas of strength and opportunities for strategic improvement in your AI journey.

Strategy & Leadership

Strategy forms the backbone of AI readiness, emphasizing a well-defined approach, clear ownership, and sustainable financial planning.

1. Do you have a strategy to deploy AI-powered solutions in your organization?

Yes — we have a well-defined AI strategy

No — we are currently in the process of developing an AI strategy

No — we have not yet started to develop an AI strategy

Unsure

2. Is it clear who/what team is leading the AI strategy for your company?

There is clear leadership/ownership of our organization’s AI strategy

More organic and decentralized

No defined leadership structure for AI

Unsure

3. Do you have a process in place to measure the impact of AI deployments?

Yes, we have a process and clearly defined metrics

Yes, we have a process but are still working on actual metrics

No, but we are likely to have this in the next 12 months

No, and we are unlikely to have this in the next 12 months

4. Has your company established a financial strategy to ensure sustainable funding for AI initiatives?

Yes — A short and long-term financial strategy is in place

Yes — Only a short-term financial strategy is in place

No — But we are currently developing a financial strategy

No — We have no plans presently to develop a financial strategy

People & Culture

Success with AI requires organizational openness to change, proper talent development, and a culture that embraces innovation.

1. How open is your organization to change, especially when it comes to adopting AI?

Highly Receptive

Moderately Receptive

Neutral

Reluctant

Highly Resistant

2. How much of your organization is already using company-approved AI in their daily operations?

Less than 25%

25% to 49%

50% to 74%

75% to 99%

100%

3. How well resourced is your company with the right level of in-house talent necessary for successful AI deployment?

Very well resourced

Moderately well resourced

Moderately under resourced

Significantly under resourced

Unsure

4. Do you have a plan to train your team so that your organization can effectively adopt AI?

Comprehensive Change Management Strategy

Partial Change Management Strategy

Limited Change Management Strategy

Exploring Change Management Strategies

No Change Management Strategy

Process & Governance

Governance in AI demands a rigorous commitment to data privacy, sovereignty, fairness, and ethical considerations.

1. Have you identified the main business goals you want to achieve with AI?

Clearly Defined Objectives

Partially Defined Objectives

Limited Objectives

Exploring Objectives

No Identified Objectives

2. What is the level of awareness across your organization regarding potential biases and fairness in AI?

High awareness: regular training sessions and active discussions

Moderate awareness: occasional training or awareness programs

Limited awareness: sporadic discussions but no formal understanding

Not aware: haven’t considered biases in our data

3. How does your organization ensure transparency in AI decision-making processes?

Highly transparent: can trace most decisions back to specific factors

Moderately transparent: essential decision factors are known

Limited transparency: some understanding but lacks depth

Completely black box: no understanding of decision mechanisms

4. What is your organization’s understanding of global data privacy standards (like GDPR, CCPA) in AI projects?

High understanding: strict adherence with regular audits and reviews

Moderate understanding: have protocols in place, but occasional lapses

Basic understanding, but no systematic adherence

Unaware of global privacy standards

5. Have you established guardrails for which data AI can access and which tasks require human oversight?

Thoroughly Evaluated and Implemented

Moderately Evaluated

Limited Evaluation

Just Beginning Evaluation

Haven’t Evaluated

Technology & Infrastructure

AI readiness heavily depends on a solid infrastructure, including computing resources, networks, and security systems that can scale.

1. How would you rate your organization’s current IT infrastructure in terms of scalability for AI?

Fully adaptable: can instantly accommodate any AI computational needs

Highly scalable: designed with growth and future AI demands in mind

Moderately scalable: can handle current projects but need enhancements

Limited scalability: might need significant updates for AI projects

Not scalable at all

2. Does your organization have dedicated GPU resources available for AI workloads?

Robust GPU infrastructure available for current and future AI workloads

Just enough GPU resources to cater to ongoing projects

Limited GPU resources for experimental purposes only

No, we don’t have dedicated GPU resources available currently

3. How would you assess your organization’s cybersecurity readiness for AI systems?

High awareness: comprehensive understanding and regular security updates

Moderate awareness: aware and have taken preliminary precautions

Limited awareness: basic understanding but no specific measures

Unaware of security threats specific to AI workloads

4. Is your technology architecture aligned with best practices for AI implementation?

Fully optimized and aligned with best practices

Small handful of customizations, but shouldn’t be limiting

A few issues or customizations that might limit us

Significant technical debt that’ll create major barriers

Data Quality & Management

Quality data is the cornerstone of AI, with an emphasis on centralized, cleaned datasets and reliable governance.

1. How centralized is your organization’s data for AI initiatives?

Fully centralized: data is consistently managed and readily accessible

Moderately centralized: majority in unified databases, some silos remain

Partially fragmented: some central databases, many department-specific silos

Highly fragmented: data is scattered across different silos

2. To what extent is your data pre-processed, cleaned, and ready for AI projects?

Consistently pre-processed: our data strategy ensures data is always AI-ready

Mostly pre-processed: most of our data is primed for AI use

Occasionally pre-processed: some datasets are AI-ready, many require work

Rarely pre-processed: significant cleaning needed before AI use

3. Do you have a data governance framework for AI implementation?

Robust Governance Framework

Moderate Governance Framework

Limited Measures in Place

Exploring Governance Options

No Governance

4. How would you rate your staff’s proficiency in leveraging data analytics tools for AI?

Proficient: staff are adept at leveraging tool capabilities to their fullest

Moderate: most staff can handle regular AI analytics tasks efficiently

Intermediate: staff can use tools but need guidance for advanced functions

Beginner: significant training is required

AI Tools & Technology Awareness

Understanding the available AI technologies and tools is crucial for effective implementation and adoption.

1. Which of these AI platforms and services are you familiar with? (Select all that apply)

ChatGPT (OpenAI)

Gemini (Google)

Claude (Anthropic)

Copilot (Microsoft)

DALL-E (OpenAI)

Midjourney

Azure AI (Microsoft)

AWS AI Services (Amazon)

IBM Watson

Salesforce Einstein

2. Which of these AI concepts are you familiar with? (Select all that apply)

Large Language Models (LLMs)

Generative AI

Retrieval Augmented Generation (RAG)

Agentic AI

Neural Networks

Machine Learning Operations (MLOps)

Computer Vision

Natural Language Processing (NLP)

AI Alignment and Safety

Prompt Engineering

3. Which domain-specific AI tools are you familiar with? (Select all that apply)

Productivity & Collaboration

Notion AI

Jasper

Otter.ai

Cursor

Fireflies.ai

Windsurf

Sales & Marketing

Gong.io

Drift

HubSpot AI

Crew AI

Lavender.ai

Relevance AI

Content Creation

Synthesia

Runway

Descript

Canva AI

Adobe Firefly

Pictory

Other Industry-Specific AI Tools

Legal: Harvey AI, Casetext

HR: Pymetrics, HireVue

Finance: Vic.ai, Ramp AI

Customer Service: Ada, Intercom AI

Healthcare: Atomwise, Tempus

Manufacturing: Noodle.ai, Augury

Challenges & Opportunities

Identify specific challenges and opportunities in your AI adoption journey.

1. What are your biggest concerns about adopting AI in your business? (Select up to 3)

Cost of implementation

Lack of technical knowledge

Data privacy/security

Regulatory compliance

Integration with existing systems

Staff resistance or fear

Unclear return on investment

Ethical considerations

2. What benefits do you hope to achieve through AI adoption? (Select up to 3)

Increased productivity

Cost reduction

Better customer experience

Innovation and new offerings

Competitive advantage

Improved decision making

Enhanced employee experience

Risk mitigation

3. What would help your organization adopt AI more effectively? (Select up to 3)

Executive education

Staff training

Clear implementation roadmap

Expert guidance

Case studies relevant to your industry

Trial periods for various AI tools

Financial resources/budget

Technical infrastructure improvements

Additional Insights

Share your specific thoughts and questions about AI in your business.

1. How do you personally stay informed about developments in AI?

2. What specific AI use cases are you most interested in exploring for your business?

3. What questions do you have about implementing AI in your organization?

Contact Information (Optional)

Provide your details if you’d like to receive a personalized assessment and recommendations.

Name

Job Title

Company

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