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Effective ways to introduce, transform, and enhance ways of working in organisations.
AI can be transformative for organisations. However, taking the wrong approach in implementing it can result in very costly failures.
A responsible AI project does not just consider its social impact, but it’s business impact as well. It is focused in what the organisation expects of it, critically considering a good use case. It is realistic in what investment is required for it to succeed, and ethical to those who are affected by it.
In this publication, we share our learnings from implementing responsible AI solutions at our customers, where thoughtful strategies meet real world impact.
To build an AI system, you need to consider the context of the problem you are solving.
Understanding how the issue can be approached within this technology will ensure you’re answering the real problem, not merely addressing the symptoms.
A good use case starts as a business problem and can include metrics such as potential revenue growth, reduction in operational costs, improvement in efficiency, and gaining a competitive advantage.
Your AI project is unlikely to succeed without embracing a Research and Development nature. This can be fortified with an AI culture and strategy to promote the value of good quality data, encourage a learning mindset, and cut through the AI hype.
The rapid rise of AI has sparked numerous ethical concerns, ranging from the potential embedding of biases within AI systems to the threat of human rights.
Get a deeper understanding of the current landscape of AI ethics and legislation, and what to consider when implementing an ethical solution.
The rapid advancements in technology has resulted in a plethora of new themes for technology leaders to engage in, and presents an interesting case for the workforce.