AI Maturity Test
QED.pl » AI Maturity Test
Business maturity concerning AI can be viewed as a progression through which a business evolves from having little to no AI capability to fully integrating AI into its core operations and strategy.
Check below what stage your company is at:
Level | Characteristics | Outcome | Offer |
---|---|---|---|
1. AI Naive | Little to no awareness of AI’s potential.
No AI-specific capabilities or resources.
| The business operates traditionally without leveraging AI. | |
2. AI Aware | Some awareness of AI’s potential benefits.
Limited in-house AI expertise. Reliance on external vendors for AI tools or solutions. | Initial exploration of AI possibilities, mostly through external consultations or adopting off-the-shelf solutions.
| |
3. AI Experimental | Investments in AI pilots or proof-of-concepts (PoC).
Hiring or training for specific AI roles (like data scientists). Limited AI-driven decision-making. | Some AI-driven projects or initiatives but not yet consistently delivering value. | |
4. AI Functional
| AI projects are systematically delivering value.
Increased budget allocation for AI. More robust in-house AI capabilities. AI begins to influence strategic decisions. | Regular deployment of AI solutions in specific functional areas, such as marketing, finance, or operations.
| |
5. AI Integrated
| AI is embedded in multiple functions and processes.
AI-driven strategy in at least one major area of the business. Ongoing commitment to AI research and development. | AI consistently drives value across various facets of the business, leading to noticeable improvements in performance. | |
6. AI Driven | AI is central to the company’s strategy and operations.
Continuous innovation using AI. Comprehensive in-house AI capabilities and infrastructure. Ethical AI considerations and governance structures are in place. | The business is reimagined around AI, leading to new business models, products, or services. |
As your business progresses through these phases, it’s crucial for you to ensure that your AI implementations are not just technically sound but are also ethically responsible, culturally compatible, and strategically aligned with their overall vision and mission.
Little to no awareness of AI’s potential.
No AI-specific capabilities or resources.
Some awareness of AI’s potential benefits.
Limited in-house AI expertise.
Reliance on external vendors for AI tools or solutions.
Investments in AI pilots or proof-of-concepts (PoC).
Hiring or training for specific AI roles (like data scientists).
Limited AI-driven decision-making.
AI projects are systematically delivering value.
Increased budget allocation for AI.
More robust in-house AI capabilities.
AI begins to influence strategic decisions.
AI is embedded in multiple functions and processes.
AI-driven strategy in at least one major area of the business.
Ongoing commitment to AI research and development.
AI is central to the company’s strategy and operations.
Continuous innovation using AI.
Comprehensive in-house AI capabilities and infrastructure.
Ethical AI considerations and governance structures are in place.
AI Naive
AI Aware
AI Experimental
AI Functional
AI Integrated
AI Driven
The business operates traditionally without leveraging AI.
Initial exploration of AI possibilities, mostly through external consultations or adopting off-the-shelf solutions.
Some AI-driven projects or initiatives but not yet consistently delivering value.
Regular deployment of AI solutions in specific functional areas, such as marketing, finance, or operations.
AI consistently drives value across various facets of the business, leading to noticeable improvements in performance.
The business is reimagined around AI, leading to new business models, products, or services.
As your business progresses through these phases, it’s crucial for you to ensure that your AI implementations are not just technically sound but are also ethically responsible, culturally compatible, and strategically aligned with their overall vision and mission.
Little to no awareness of AI’s potential.
No AI-specific capabilities or resources.
Some awareness of AI’s potential benefits.
Limited in-house AI expertise.
Reliance on external vendors for AI tools or solutions.
Investments in AI pilots or proof-of-concepts (PoC).
Hiring or training for specific AI roles (like data scientists).
Limited AI-driven decision-making.
AI Naive
AI Aware
AI Experimental
The business operates traditionally without leveraging AI.
Initial exploration of AI possibilities, mostly through external consultations or adopting off-the-shelf solutions.
Some AI-driven projects or initiatives but not yet consistently delivering value.
AI projects are systematically delivering value.
Increased budget allocation for AI.
More robust in-house AI capabilities.
AI begins to influence strategic decisions.
AI is embedded in multiple functions and processes.
AI-driven strategy in at least one major area of the business.
Ongoing commitment to AI research and development.
AI is central to the company’s strategy and operations.
Continuous innovation using AI.
Comprehensive in-house AI capabilities and infrastructure.
Ethical AI considerations and governance structures are in place.
AI Functional
AI Integrated
AI Driven
Regular deployment of AI solutions in specific functional areas, such as marketing, finance, or operations.
AI consistently drives value across various facets of the business, leading to noticeable improvements in performance.
The business is reimagined around AI, leading to new business models, products, or services.
- AI Solutions
- AI Due Diligence
- AI Solutions
- AI Due Diligence
As your business progresses through these phases, it’s crucial for you to ensure that your AI implementations are not just technically sound but are also ethically responsible, culturally compatible, and strategically aligned with their overall vision and mission.