Rating Scale/Point System:
1 Pts. (Strongly Disagree): Inadequate understanding and significant gaps in the
specified area.
2 Pts. (Disagree): Some awareness and initial efforts made, but substantial
improvements are needed.
3 Pts(Neutral): A reasonable level of awareness and preparation, with identified
opportunities for enhancement.
4 Pts(Agree): Strong awareness and well-established practices in the specified
area.
5 Pts(Strongly Agree): Outstanding performance, best practices, and continuous
improvement in the specified area.
5 (High) – 1 (Low)
| 1 | 2 | 3 | 4 | 5 | |
| Data Governance | |||||
|---|---|---|---|---|---|
| 1.We have well-defined and communicated data governance policies and procedures, ensuring alignment with regulatory requirements and organisational objectives | |||||
| 2.We have embedded and strong data ownership, accountability, and stewardship roles clearly established and enforced across the organisation. | |||||
| 3. Our data governance policies are reviewed and updated in a regular cadence to adapt to evolving compliance standards and business needs. | |||||
| 4. We have established mechanisms for resolving data governance disputes and ensuring consistent adherence to policies. | |||||
| 5.We have strategies in place to communicate the importance of data governance throughout the organisation, fostering a culture of responsibility | |||||
| 6.We ensure that data governance practices are integrated into our project management and decision- making processes. | |||||
| Total Score: |
/30 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| Data Security | |||||
|---|---|---|---|---|---|
| 1.We have robust data security measures, encompassing encryption, access controls, and regular audits, to safeguard against unauthorised access and data breaches. | |||||
| 2.We have proactive steps to assess and mitigate security risks associated with AI applications, particularly those involving sensitive or personal data. | |||||
| 3. We frequently provide security training to staff to ensure awareness and compliance with data security protocols. | |||||
| 4.In the event of a security incident, we respond and recover quickly. We have measures in place for continuous improvement. | |||||
| 5.We ensure that third-party vendors and partners adhere to the same rigorous data security standards as our organisation. | |||||
| Total Score: |
/25 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| Data Storage | |||||
|---|---|---|---|---|---|
| 1.Our current data storage and infrastructure is scalable and resilient, ensuring it can accommodate the increasing demands associated with AI initiatives. | |||||
| 2.Our data storage capacity is monitored and optimised to avoid unnecessary costs while ensuring accessibility and performance. | |||||
| 3.We have redundancy measures in place to mitigate the risk of data loss or disruption, and they are frequently tested. | |||||
| 4.We prioritise data archiving and retrieval, and align these with regulatory requirements and business priorities. | |||||
| 5.We balance the utilisation of on-premises and cloud- based storage solutions to optimise cost and performance. | |||||
| Total Score: |
/25 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| Data Quality | |||||
|---|---|---|---|---|---|
| 1.We have a rigorous approach to ensuring data accuracy, completeness, and consistency, particularly in the datasets utilised for AI training and decision-making. | |||||
| 2.We have tools and processes in place to detect and rectify data quality issues. These are integrated into our broader data management strategy. | |||||
| 3.We involve end-users and data stakeholders in the data quality assurance process to capture diverse perspectives. | |||||
| 4.We ensure the ongoing alignment of data quality standards with evolving business needs, industry best practices, and technological advancements. | |||||
| 5.We have measures in place to address biases and ensure fairness in our data quality assessment processes. | |||||
| Total Score: |
/25 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| Data Architecture | |||||
|---|---|---|---|---|---|
| 1.We have well-defined data architecture, considering factors like data lakes, warehouses, and integration points, to support the scalability and flexibility required for AI initiatives. | |||||
| 2.Our data architecture is designed to facilitate seamless integration between various data sources, ensuring a comprehensive view for analytical purposes. | |||||
| 3.We regularly review and update data architecture to accommodate evolving business requirements and technological advancements. | |||||
| 4.We have measures in place to ensure that our data architecture aligns with industry standards and emerging best practices in the field. | |||||
| 5. We ensure that data architecture decisions are communicated effectively across the organisation, fostering collaboration and understanding. | |||||
| 6.We have internal reviews of privacy and data protection laws when designing and updating our data architecture. | |||||
| Total Score: |
/30 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| Data Analysis | |||||
|---|---|---|---|---|---|
| 1.We are well equipped with the necessary tools and technologies for advanced data analysis and AI model development. | |||||
| 2.We have a skilled workforce capable of leveraging data analysis techniques for extracting meaningful insights and supporting AI initiatives. | |||||
| 3.We integrate data analysis into decision-making processes, ensuring a data-driven culture throughout the organisation. | |||||
| 4.We have mechanisms in place to assess the effectiveness and impact of our data analysis efforts in contributing to overall business objectives. | |||||
| 5.We foster innovation and continuous improvement in data analysis capabilities to stay ahead of industry trends and emerging technologies. | |||||
| 6.We ensure data analysis results are communicated in an understandable and actionable manner. | |||||
| Total Score: |
/30 |
||||
| 1 | 2 | 3 | 4 | 5 | |
| AI Ethics | |||||
|---|---|---|---|---|---|
| 1.We ensure ethical considerations are embedded in our AI development and deployment processes, avoiding biases and promoting fairness. | |||||
| 2.Our AI algorithms are transparent and explainable, allowing stakeholders to understand and trust the decision-making process. | |||||
| 3.We have mechanisms in place to regularly audit and monitor AI systems for ethical compliance and adherence to established principles. | |||||
| 4.We involve diverse stakeholders, including ethicists and representatives from impacted communities, in shaping our AI policies and practices. | |||||
| 5.We communicate our commitment to AI ethics both internally and externally, fostering trust among employees, customers, and the broader community. | |||||
| 6.We ensure ongoing training and awareness programs for employees regarding ethical considerations in AI development and usage. | |||||
| 7.We have measures in place to address ethical challenges that may arise in the integration of AI into various business processes and decision-making. | |||||
| Total Score: |
/35 |
||||
| Assessment Scoring | |
|---|---|
| Category | Score Summary |
| 1.Data Governance | / 30 |
| 2.Data Security | / 25 |
| 3.Data Storage | / 25 |
| 4.Data Quality | / 25 |
| 5.Data Architecture | / 30 |
| 6.Data Analysis | / 30 |
| 7.AI Ethics | / 35 |
| Final Score |
|
Calculate the total score across all categories.
| Points Earned | What This Means |
| Less than 50 | Immediate attention and substantial improvements required |
| 51 - 99 | Basic foundation, indicating a need for comprehensive AI readiness enhancements |
| 100 - 150 | Minimum Readiness established with high-risk areas identified and clear opportunities for optimisation. |
| 151 - 200 | AI readiness established, demonstrating strong alignment with best practices in data governance, security, storage, quality, architecture, analysis, and ethics |
Need some help nudging the scores into the green before unleashing an AI strategy? The demand for
'AI
Readiness' roadmaps, strategy and remediation implementation has skyrocketed since mid-2023.
We
are working across a diverse set of industries to ensure our client's data strategy and future
roadmap
checks the boxes for what we like to call
"The MVP of being AI ready".
Need some support? Connect with us
today!
info@intelligengroup.com
02 9188 3911