AI Maturity Model Survey

แบบประเมินศักยภาพด้านปัญญาประดิษฐ์ เพื่อวัดระดับความพร้อมและการนำ AI มาใช้ในมิติต่าง ๆ ขององค์กร ครอบคลุมตั้งแต่กลยุทธ์ โครงสร้าง ข้อมูล บุคลากร เทคโนโลยี และวัฒนธรรม

Part 1: ข้อมูลส่วนตัว

Full Name / ชื่อ-นามสกุล

Gender / เพศ

Job Position / ตำแหน่งงาน

Part 2: การรับรู้และทัศนคติต่อ AI

I. General Perception of AI

1. What is your level of familiarity with Artificial Intelligence (AI) technology and its related software/platforms?

Highly Familiar – Actively study and experiment with AI in-depth.

Somewhat Familiar – Understand the fundamental concepts and some of its use cases.

Moderately Familiar – Have heard of AI but possess limited knowledge about it.

Unfamiliar – Uncertain about what AI is or how it functions.

Completely Unfamiliar – Have not previously heard of or been introduced to AI.

2. What is your attitude towards the adoption of new AI technologies?

Enthusiastic – Eager to try new technologies as soon as they become available.

Receptive – Willing to adopt if their value is demonstrated.

Neutral – May adopt if it becomes a common practice.

Hesitant – Prefer to adhere to conventional methods.

Resistant – Avoid AI unless it is absolutely necessary.

II. AI Experimentation

3. Have you ever used any AI tools or platforms (e.g., chatbots, predictive analytics, AI-powered software)?

Yes, frequently – I frequently experiment with new AI tools.

Yes, some – I have tried some tools based on recommendations.

Occasionally – Only when required for a specific task.

No, never – I have not used any AI tools.

4. Which of the following AI tools or platforms have you used previously? (Select all that apply)

ChatGPT

Gemini (Google)

Microsoft CoPilot

Claude (Anthropic)

Midjourney

DALL-E

GitHub Copilot

DeepMind / Grok

Other:

III. Applications of Artificial Intelligence

5. How do you typically approach learning about new technologies such as AI?

Proactive Research – I actively seek information, attend workshops, and engage in self-directed experimentation.

Guidance-based Learning – I rely on recommendations and support from peers or mentors.

Cautious Adoption – I wait until the technology is well-established and widely adopted before learning about it.

Necessity-driven Learning – I avoid learning about new technologies unless it is required.

6. What is the primary motivating factor for you to adopt AI technology?

Intrinsic Motivation – I am personally driven by a desire to experiment with innovation and explore new opportunities.

Evidence-based Adoption – I will adopt AI upon clear evidence of its tangible benefits.

Social Influence – I am influenced to adopt AI by peer pressure or observing its use by others.

Extrinsic Requirement – I will adopt AI only when it is a necessity or a directive.

7. What is your perspective on the ethical risks and concerns associated with AI (e.g., bias, privacy, job displacement)?

Aware and Proactive – I acknowledge these concerns and am actively engaged in mitigating them.

Cautiously Optimistic – I am mindful of the concerns but remain open to AI adoption.

Skeptical and Risk-Averse – I am highly skeptical and prefer to avoid AI unless its safety is rigorously proven.

Dismissive due to Concerns – These concerns lead me to avoid AI entirely.

8. To what extent do you believe artificial intelligence technology poses a personal or professional risk to you?

No Impact – I do not perceive any direct impact.

Risk of Displacement – AI technology is likely to replace my current role.

Risk with Adaptability – I perceive a risk, but I am confident in my ability to adapt and work alongside AI.

No Long-Term Risk – AI adoption may be transient and is unlikely to impact my career in the long term.

No Risk, Potential for Enhancement – AI technology poses no risk and will serve to augment my capabilities.

1. Strategy

กลยุทธ์และทิศทางการนำ AI มาใช้ในองค์กร ครอบคลุมวิสัยทัศน์ การผูกพันของผู้นำ และการจัดสรรทรัพยากร

1. Vision & Alignment

Level 1Initial

No clear AI vision; scattered, informal activities.

Level 2Emerging

AI mentioned in some planning, not a core focus.

Level 3Integrated

Explicit AI vision aligned with institutional strategy.

Level 4Optimized

Regularly updated AI vision guiding strategic initiatives.

Level 5Transformational

Vision drives sector innovation; alignment at all university levels.

2. Leadership Commitment

Level 1Initial

Minimal leadership engagement or sponsorship.

Level 2Emerging

Occasional leadership attention; no formal role.

Level 3Integrated

Dedicated leadership assigned (e.g., AI committee/lead); visible sponsorship.

Level 4Optimized

Executive champions AI; leadership incentivizes progress.

Level 5Transformational

Leadership is nationally/internationally recognized for AI thought leadership.

3. AI Investment and Prioritization

Level 1Initial

No defined resources for AI.

Level 2Emerging

Ad-hoc or opportunistic funding.

Level 3Integrated

Initial budget allocations and resource prioritization.

Level 4Optimized

Substantial, recurring investment aligned with roadmap.

Level 5Transformational

Strategic investment, external partnerships for continuous AI innovation.

2. Structure

โครงสร้างองค์กร การกำกับดูแล บทบาทหน้าที่ และการประสานงานข้ามสายงานเพื่อรองรับการใช้ AI

4. Governance & Policy

Level 1Initial

Informal governance; no policies.

Level 2Emerging

Drafting of some policies.

Level 3Integrated

Formal AI policies and governance structures in place.

Level 4Optimized

Policy reviewed for efficacy; proactive risk management.

Level 5Transformational

Adaptive, benchmark-setting governance influencing sector norms.

5. Roles & Accountability

Level 1Initial

Unclear roles for AI.

Level 2Emerging

Some roles identified, but inconsistent.

Level 3Integrated

Designated roles and responsibilities in main units.

Level 4Optimized

Clear, institution-wide roles; dedicated AI offices/teams.

Level 5Transformational

Integrated roles across all levels; clear accountability network.

6. Cross-functional Coordination

Level 1Initial

Coordination absent.

Level 2Emerging

Initial taskforces; limited collaboration.

Level 3Integrated

Routine interactions in select projects.

Level 4Optimized

Systematic, cross-campus collaboration through committees/platforms.

Level 5Transformational

Highly agile cross-functional teams; model shared externally.

3. Data

การบูรณาการข้อมูล คุณภาพ จริยธรรม และการเข้าถึงข้อมูลเพื่อสนับสนุนการใช้ AI อย่างมีประสิทธิภาพ

7. Data Integration

Level 1Initial

Data in silos; little sharing.

Level 2Emerging

Partial systems integration.

Level 3Integrated

Institution-wide unified data platform.

Level 4Optimized

Real-time integration, broad interoperability.

Level 5Transformational

External partnerships use seamless, secure data integration.

8. Data Quality & Ethics

Level 1Initial

Quality unmanaged; inconsistent ethics.

Level 2Emerging

Initial quality/ethics standards being considered.

Level 3Integrated

Defined data quality and ethical frameworks implemented.

Level 4Optimized

Proactive audits, continuous improvement, strong ethical oversight.

Level 5Transformational

Organization sets sector benchmarks, participates in regulatory co-creation.

9. Data Accessibility

Level 1Initial

Limited or no access.

Level 2Emerging

Restricted access for few users.

Level 3Integrated

Broader access with permissions and monitoring.

Level 4Optimized

User-driven customization; easy, secure self-service.

Level 5Transformational

Open, responsible data ecosystem supporting internal/external innovation.

4. Organization

ทักษะ AI ของบุคลากร การทำงานร่วมข้ามสาขา และการบริหารการเปลี่ยนแปลงองค์กร

10. AI Skills & Training

Level 1Initial

No formal programs.

Level 2Emerging

Occasional workshops; few staff trained.

Level 3Integrated

Coordinated skills programs for staff/faculty/students.

Level 4Optimized

Mandatory training; targeted development plans.

Level 5Transformational

AI literacy embedded; advanced skills are a competitive edge.

11. Interdisciplinary Collaboration

Level 1Initial

Rare/none.

Level 2Emerging

Pilot cross-unit projects exist.

Level 3Integrated

Regular interdisciplinary initiatives in teaching/research.

Level 4Optimized

Strategic, supported collaborations; incentives provided.

Level 5Transformational

University is recognized for ecosystem-wide, boundaryless collaboration.

12. Change Management

Level 1Initial

No formal process.

Level 2Emerging

Some buy-in, isolated champions.

Level 3Integrated

Coordinated plans and communication for AI changes.

Level 4Optimized

Institution-wide engagement, effective feedback loops.

Level 5Transformational

Deliberate, cultural change embraced and led by all stakeholders.

5. Technology & Infrastructure

ทรัพยากรการประมวลผล เครื่องมือ AI และความปลอดภัยทางไซเบอร์ที่รองรับการพัฒนา AI ขององค์กร

13. Computing Resources

Level 1Initial

Basic IT infrastructure only.

Level 2Emerging

Limited cloud/AI resources.

Level 3Integrated

Scalable computing for priority programs.

Level 4Optimized

Advanced, secure, institution-wide cloud/HPC infrastructures.

Level 5Transformational

Dynamic, cutting-edge resources; supports global AI research/collaboration.

14. AI Tools & Platforms

Level 1Initial

None or ad hoc freeware.

Level 2Emerging

Some pilot systems/platforms tested.

Level 3Integrated

Licensed, supported platforms for core uses.

Level 4Optimized

Multiple, integrated AI platforms supporting diverse needs.

Level 5Transformational

University-developed/customized tools and platforms; external influence.

15. Cybersecurity & Privacy

Level 1Initial

Basic controls, mostly reactive.

Level 2Emerging

Initial risk identification.

Level 3Integrated

Formal policies and proactive risk management.

Level 4Optimized

Mature, pre-emptive controls; continual monitoring.

Level 5Transformational

Recognized as a secure "trusted hub," leader in privacy-by-design.

6. Culture & Ethics

การรู้เท่าทัน AI วัฒนธรรมองค์กร จริยธรรม และความเปิดรับนวัตกรรมในระดับสถาบัน

16. AI Literacy & Mindset

Level 1Initial

Limited awareness.

Level 2Emerging

Pockets of interest; optional awareness efforts.

Level 3Integrated

Regular literacy campaigns and dialogue.

Level 4Optimized

AI recognized as transformative; learning is ongoing.

Level 5Transformational

AI fluency expected; fosters thought leadership and external championing.

17. Ethical AI Use

Level 1Initial

Not discussed or enforced.

Level 2Emerging

Initial awareness; discussions started.

Level 3Integrated

Ethics codes adopted, monitored in use cases.

Level 4Optimized

Embedded in practices and curricula; recurring audits.

Level 5Transformational

Sets/raises sectoral standards; influences AI policy at national/global level.

18. Openness to Innovation

Level 1Initial

Resistance to change.

Level 2Emerging

Select groups open to pilot projects.

Level 3Integrated

Broader acceptance; innovation rewarded.

Level 4Optimized

Institutionalized innovation (labs, funds, hackathons).

Level 5Transformational

Innovation is cultural DNA — university seen as a model of digital/AI transformation.

พร้อมส่งแบบประเมินแล้ว

กรุณาตรวจสอบคำตอบทั้งหมดก่อนกดส่ง

ขอบคุณสำหรับข้อมูล!

เราได้บันทึกคำตอบของคุณเรียบร้อยแล้ว ขอบคุณที่ร่วมประเมินศักยภาพ AI