Many organisations come from a strong position of digitalisation in the past two decades. However, identifying areas to tackle with AI is tough. There is a gap between the promise of AI on popular media and the reality of what engineers can realistically deliver in a short amount of time. With limited budgets and pressure from competitors, surgical precision in what use cases are tackled first is a priority.

Organisation have interest in embracing AI, but there is confusion about what datasets are necessary, what is feasible, how much it will cost, and where autonomous intelligence fits within legacy systems, and an organisation's future IT strategy. We have experience in multiple sectors in the economy, and we know innovation. You know your business, and we embrace transparency, and share our designs to deploy machine learning solutions tailored to your organisation.

Much of today’s advance is in AI is what is often referred to as “narrow AI” – where machine-learning techniques are being developed to solve specific problems, for example, in computer vision or natural language processing, as opposed to a more general form of intelligence. As more progress is underway, organisations need to grow flexibility to ride the crest of a wave of change that is only gaining steam.

Lastly, AI can only live up to its promise if the public gives it a vote of confidence, which can easily crumble as a result of privacy violations, bias, or malicious use, or if much of the world comes to blame it for exacerbating inequality, as entire economies are navigating through uncharted territories.