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AI Maturity Assessment

Discover your organisation's AI readiness in just 10 minutes. Complete this brief assessment to receive a personalised AI maturity report delivered straight to your inbox, giving you actionable insights to accelerate your AI journey.

Tell us about you

Strategy and Leadership

To what extent is AI integrated into your organisation's overall business strategy?
No AI strategy exists
AI is mentioned in strategy but not clearly defined
AI strategy exists but is not fully aligned with business goals
AI strategy is well-defined and mostly aligned with business goals
AI strategy is fully integrated and central to business strategy
How involved is senior leadership in AI initiatives?
No involvement from senior leadership
Limited awareness of AI initiatives
Occasional involvement in major AI decisions
Regular involvement and support for AI initiatives
AI championed by senior leadership, driving organisational change
How well-defined is your AI investment strategy?
No specific AI investment strategy
Ad-hoc investments in AI projects
Basic investment plan for AI, not tied to ROI
Structured investment plan with some ROI considerations
Comprehensive AI investment strategy with clear ROI metrics

Data Infrastructure and Management

How would you rate the quality and accessibility of your organisation's data?
Poor data quality, siloed and inaccessible
Inconsistent data quality, limited accessibility
Moderate data quality, partially accessible
Good data quality, mostly accessible
High-quality data, easily accessible across the organisation
To what extent does your organisation have a unified data architecture?
No unified architecture, completely siloed systems
Limited integration between some systems
Partial unified architecture, some systems still isolated
Mostly unified architecture with a few exceptions
Fully unified data architecture across the organisation
How advanced is your organisation's data governance framework?
No formal data governance
Basic data policies in place, not consistently enforced
Data governance framework exists, partially implemented
Comprehensive framework, mostly adhered to
Mature data governance with continuous improvement processes

Technology and Tools

What types of AI infrastructure does your organisation currently use?
No AI-specific infrastructure
On-premises infrastructure, limited AI capabilities
Mix of on-premises and cloud infrastructure for AI
Primarily cloud-based AI infrastructure with some specialised hardware
Advanced hybrid or multi-cloud infrastructure with specialised AI hardware (e.g., GPUs, TPUs)
Which AI tools and platforms has your organisation adopted?
No AI tools adopted
Basic analytics tools, considering AI-specific solutions
Some mainstream AI tools (e.g., ChatGPT, basic machine learning libraries)
Wide range of AI tools including large language models (e.g., GPT, BERT) and specialised AI software
Comprehensive suite of cutting-edge AI tools, including custom solutions and early access to advanced models
Which AI technologies or tools is your organisation planning to adopt in the near future?
No plans for AI tool adoption
Considering basic AI tools or services
Planning to adopt mainstream AI platforms or services
Evaluating advanced AI tools and developing adoption roadmap
Proactively identifying and planning to adopt or develop cutting-edge AI technologies
How advanced are the AI and machine learning tools used in your organisation?
No AI tools in use
Basic analytics tools, no specific AI capabilities
Some AI-specific tools, primarily off-the-shelf solutions
Advanced AI tools, mix of custom and off-the-shelf solutions
Cutting-edge AI tools, including custom-developed solutions
To what extent is your AI infrastructure scalable and flexible?
No AI-specific infrastructure
Limited, non-scalable AI infrastructure
Moderately scalable infrastructure, some flexibility
Scalable infrastructure, good flexibility for most AI needs
Highly scalable, cloud-native infrastructure adaptable to all AI needs
How well integrated are AI tools with existing business systems?
No integration of AI tools
Limited, manual integration of AI outputs
Partial integration with some automated processes
Good integration across most business systems
Seamless integration, AI embedded in all relevant business processes
How does your organisation approach AI tool evaluation and adoption?
No formal evaluation process
Ad-hoc evaluation based on immediate needs
Basic evaluation framework focused on technical capabilities
Comprehensive evaluation considering business impact and user adoption
Platform-neutral, needs-based approach with continuous assessment

Talent and Skills

How would you rate your organisation's AI and data science talent pool?
No in-house AI or data science talent
Limited talent, mostly self-taught or non-specialists
Small team of AI specialists, some skill gaps
Strong AI team covering most required skills
World-class AI talent across all relevant disciplines
How effective is your AI-related training and development program?
No AI-related training available
Ad-hoc, limited AI training opportunities
Structured training program for technical staff only
Comprehensive AI training for technical and non-technical staff
Continuous learning culture with personalised AI development paths
How well does your organisation attract and retain AI talent?
No specific focus on AI talent acquisition or retention
Basic recruitment efforts, high turnover of AI talent
Targeted AI recruitment, moderate retention rates
Strong employer brand for AI, good retention rates
Recognised as a top employer for AI talent, excellent retention

Ethics and Governance

How comprehensive is your AI ethics framework?
No AI ethics framework in place
Basic awareness of AI ethics issues, no formal policies
Formal AI ethics policy exists but not fully implemented
Comprehensive ethics framework, mostly adhered to
Industry-leading AI ethics framework with continuous improvement
To what extent does your organisation consider bias and fairness in AI systems?
No consideration of AI bias or fairness
Basic awareness, no formal processes
Some processes to check for obvious biases
Comprehensive bias detection and mitigation processes
Advanced fairness-aware AI development with ongoing monitoring
How robust is your AI governance structure?
No AI-specific governance
Basic governance policies, not consistently applied
AI governance framework exists, partially implemented
Comprehensive AI governance, mostly adhered to
Mature AI governance with continuous auditing and improvement

AI Implementation and Use Cases

How mature are your organisation's AI use cases?
No AI use cases implemented
Experimental AI projects, not in production
Few production AI use cases, limited impact
Multiple AI use cases deployed with measurable impact
AI widely deployed across organisation with transformative impact
How effective is your AI project management and deployment process?
No formal AI project management process
Basic project management, frequent delays or failures
Structured process, moderate success rate
Efficient process with good success rate and timely deployment
Optimised AI project lifecycle with continuous delivery and improvement
How well does your organisation measure and communicate the impact of AI initiatives?
No measurement of AI impact
Basic metrics, not tied to business outcomes
Some impact measurement, limited communication
Comprehensive impact measurement, regular communication
Advanced impact analysis driving decision-making, transparent communication

Organisational Culture and Change Management

How would you characterise your organisation's mindset toward AI adoption?
Fear-based resistance to AI adoption
Skepticism with pockets of interest
Cautious optimism but concerns about disruption
Positive outlook with willingness to experiment
Growth mindset seeing AI as a strategic advantage
How effective is your change management approach for AI initiatives?
No change management for AI initiatives
Ad-hoc change management, often reactive
Basic change management processes in place
Comprehensive change management strategy for AI
Proactive, data-driven change management optimising AI adoption
How well does your organisation manage the workforce impact of AI adoption?
No consideration of AI's impact on workforce
Basic awareness, no formal planning
Some planning for AI-driven changes, limited execution
Comprehensive workforce planning and re-skilling initiatives
Proactive workforce evolution, seamlessly integrating humans and AI

AI Learning and Education Culture

How would you rate your organisation's approach to AI education and learning?
No formal AI education or learning initiatives
Ad-hoc learning, primarily self-directed
Some structured AI learning for technical teams only
Organisation wide AI education program with different tracks
Comprehensive AI learning ecosystem with continuous education paths
How does your organisation approach knowledge sharing around AI?
No AI knowledge sharing mechanisms
Informal sharing within specialised teams
Some formal knowledge sharing within departments
Cross-functional knowledge sharing with regular sessions
Advanced knowledge ecosystem with mentorship and communities of practice
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