Artificial Intelligence is still a sci-fi concept to many but there’s no doubt it will change how we live and work – and soon. AI has become an inescapable buzzword and plenty of start-ups and scale-ups are pivoting to jump on the bandwagon. However, AI seems to mean lots of things to different people. So, what does the reality look like, and what’s next?
At our AI: Transforming Business breakfast briefing, we turned to three leaders from AI firms Magic Pony, BenevolentAI, and Babylon Health. Reaching an agreement on what artificial intelligence actually means isn’t necessarily straightforward, however our panel reached a clear consensus. They view AI as a shift away from traditional rules-based programming towards a process of learning (or “machine learning”), often structured in a similar way to the neural networks in our brains.
While the public are most likely to encounter artificial intelligence through AI assistants such as Amazon’s Alexa, the applications are wide-ranging. AI makes the automation of a huge number of tasks currently carried out by humans possible. Its other key strength is interrogating data to solve problems.
More data will be created in 2017 than in the past 5,000 years of human history. The potential outcomes of how that data is used range from the mundane to the spectacular. However, if even a fraction of this data could be placed into machine learning, the outcomes could, theoretically, drive change at a societal level.
Currently, the likes of Google, IBM, Microsoft and Apple are competing to offer AI services to enterprise clients, while AI startups offer bespoke services for companies with specific AI needs. Sectors such as financial services, healthcare, and marketing are already investing heavily in the space.
The next step is Generalised AI, where we take artificial intelligence from narrow, domain-specific applications (like preparing an insurance quote) to broader applications that can do almost anything you ask it to. While AI will undoubtedly present new challenges – for example, job losses and skills gaps – our panel was universally optimistic about its longer-term prospects. We will soon see the day when AI is as indispensable to a business as electricity.
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