The AI Qualification Framework serves as a roadmap to guide organisations in identifying, evaluating, and qualifying AI opportunities. The framework focuses on a holistic approach, ensuring that both technical and organisational aspects are considered.

Artificial Intelligence (AI) and, more specifically, Generative AI are transforming the way businesses operate. However, as with all transformative technologies, the implementation of AI is not without its challenges. Selecting the right AI opportunities and ensuring that they align with organisational goals and capabilities is crucial. Without a proper framework, organisations may risk capital, resources, and even their reputation.

While the allure of AI is undeniable, not every AI project is suitable for every organisation. The rush to harness the power of AI has led many organisations to dive headfirst into projects without a clear understanding of the prerequisites, potential outcomes, or inherent risks. Misaligned AI projects can lead to wasted resources, skewed decision-making, and in some cases, unintended harmful consequences. Thus, there is a pressing need for a systematic approach to evaluate, qualify, and implement AI opportunities that align with the organisation's strategic objectives and capabilities.

By deploying the AI Qualification framework, a company can expect to reduce costs, reduce risk and celebrate higher product acceptance. 

• Cost Reduction – by ensuring the opportunity qualification is done properly, the success ratio of the project is high, and resources are saved.

• Risk Reduction – a thorough and informed assessment mitigates reputational risk, as well as project risks, legal and technical risks.

• Higher product acceptance – a targeted AI solution that meets the needs of staff and consumers will lead to higher acceptance and better business.

The challenge is that while the term "AI" sounds promising, it's abstract and lacks the tangibility of something like "cloud computing." The crux of the issue is understanding and demystifying what AI is, its capabilities, and its potential applications in a given industry.

To address this, the AI Qualification Framework is segmented into 3 phases, which seek to do the following: 

• Seek a sound understanding of the current state of business.

• Provide tailored use cases to solve clearly identified problems.

• Ensure proposed use cases are aligned with business strategy.

• Focused experimentation for best use of resources.

• Focused solutioning proportional to risk appetite.

• Identify risks and solution for risk mitigation.

• Propose a high-level change management strategy. 

• Perform a high-level impact assessment for people and processes.

• Formulate a strategy that minimises disruption to BAU.

• Assess existing data and data quality. 

• Ensure the solution is regulation compliant and ethical.

• Identify skills and resources needed for implementation.