Artificial intelligence is flavour of the month at the moment and the world is full of predictions about how it is going to revolutionise our lives. But alongside this is a shortage of people with the skills needed to make AI work.
So just what is needed for working with AI? Who are the people on the front line of this digital revolution? AI isn’t about just one set of skills, in fact, it needs a combination of knowledge, ensuring that people with the right attributes are in high demand.
At the heart of AI is machine learning, an understanding of this is fundamental to a career in the field. Mathematical knowledge is important too, the best AI candidates will have a solid grasp of facts such as statistical probability and algebra, to allow them to develop or adapt algorithms.
Programming skills are important too, but while older languages like C++ and Java are employed in this field, the big demand is for specialist skills including Python and Prolog. Increasingly there is also demand for skills in platforms such as TensorFlow that offer AI capability.
Experience in search technology is needed too, as are skills in data handling – particularly unstructured data and ‘big data’ as these are areas where AI is increasingly being applied. There’s also a need for expertise in fields that aren’t always directly programming related. For example, natural language processing or text analytics.
Of course, AI doesn’t stand on its own. It needs to be integrated into other enterprise systems, this means a need for skills related to the platforms and APIs needed to tie AI into other applications. Security is important too, not only to protect AI systems but also because security systems themselves are increasingly turning to AI in order to provide improved detection of malware and cyber attacks.
Beyond the technical
In addition to technical skills, working in AI also needs abilities in areas including decision making, deductive logic, and understanding concepts. The ideal candidate will also have strong team working skills and be able to build effective business relationships. They need to be able to integrate their work with parts of the project created by other teams too.
Because AI is a relatively new field, the skills it requires often don’t chime with the traditional teaching of STEM and IT subjects. In the past, the focus has been on the nuts and bolts of coding, but with AI there needs to be more emphasis on the creative side of the activity. The process of building AI applications can be an exciting one and education and training needs to reflect that.
At project manager level, the ability to be able to assess performance and evaluate the success of projects is important too. Plus of course, skills in performance evaluation and testing are essential before projects are signed off.
It should be obvious from the above that AI encompasses a whole range of skills and that its practitioners can come from a variety of different backgrounds.
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