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The conversation around AI is just beginning to shift, from futuristic, sci-fi ideologies to tangible actions and impacts. Kubrick Managing Partner Simon Walker joined the panel at Eversheds Sutherland’s 6th Annual Digital Financial Services & Fintech Conference to discuss all things Artificial Intelligence, where they shared their insights into reframing its perceived risks and accessing the rewards of its implementation. Whilst the financial services have led the early adoption of AI, the panel highlighted some of the many cultural and intellectual barriers still left to overcome, and their expert advice should be applied by organisations across all industries who are exploring the field.

Demystifying AI

Despite increased familiarity of ‘AI’ as an acronym outside of the technology community in the last decade, the panel quickly identified the primary blocker for most organisations: the black box nature of Artificial Intelligence. The dangerous preconceptions of AI are damaging to its reputation and experts are searching for a platform to demonstrate the truth of what’s inside when the black box is opened. In practice, Machine Learning is simply an evolution of algorithms and methodologies which have long been used in areas such as financial modelling and predictions.

Recent developments in AI are not a run-away train to a dystopian future, as often depicted in the media, but a path to stability and heightened safeguarding for the models and practices which govern decision-making in financial services. The techniques and technologies behind AI are, in fact, much easier to oversee and control than human actions – and certainly less prone to error. Moreover, its power to identify and mitigate against risks in other systems and processes should earn AI widespread approval as an organisational safety-net, rather than warrant assumptions that it is a risk of itself. Instead, data scientists continue to lament the barriers of jargon and fear-mongering misinterpretations of machine learning capabilities which leave businesses vulnerable to falling behind in the technological revolution.

Laying the Groundwork

Alongside instigating attitudinal change, there are some practical actions that organisations should take to ensure the implementation of AI is most effective. Significantly, the growing skills gap will hinder many businesses’ ability to harness AI even when culturally ready to do so. The alarming reality is that the UK is especially susceptible to failure in this aspect of digital transformation, as reported by Microsoft in August 2020. Businesses who are starting to explore implementing machine learning capabilities should simultaneously prepare to augment their workforce with the right skills to see their efforts come to fruition in a timely and effective manner.

The companies which will benefit the most from integrating AI capabilities are those who are looking beyond the data science team. Embedding data-literacy throughout the business will not only ease the cultural shift to utilising data and IT, but a stronger understanding of its benefits and capabilities will also help to ensure regulation is upheld.

Equally, leaders must recognise diversity as a priority when taking stock of their workforce. A diverse and inclusive data team is able to remove biases which harm data functionality with skewed, inaccurate information; what used to be a pleasant but disposable statistic in a corporate report is now moving up the agenda as a commercial requirement. Moreover, in the talent war which is soon to be waged over the growing skills gap, young people are favouring workplaces with active diversity and inclusion initiatives when choosing their employers. Organisations which push diversity to the fore gain both improved data capabilities and the top talent to utilise it.

Simon reflected on the conclusions of the panel:

The widespread adoption of AI is just around the corner. Leaders in transformation and change need to prioritise the addition of data skills across the business in order to implement AI and machine learning technology as well as accelerate cultural change. At Kubrick Group, we ensure that diversity is at the heart of the future data workforce to protect data use, remove biases, and create an inclusive environment in which young professional can thrive.

To learn more about Kubrick Group, our Machine Learning engineers and their capabilities, and our diversity initiatives, please get in touch:

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