Is the tech skills gap a barrier to AI adoption?

• Read original article here

The government is actively pursuing a strategy which places the UK at the ‘forefront of the artificial intelligence and data revolution’, however, the £45 million to be allocated for 200 extra PhDs in AI and related disciplines will barely make a dent in this omnipresent issue. In order to progress towards an AI future, we need to value the human role in this process and ensure the right skills are in place to develop the best tech.

By better preparing a shift towards data skills, companies can build an army of citizen data scientists’ capable of better reacting and leading in a data-led world. Through empowering every member of the business to use and leverage analytics to amplify their abilities companies can develop existing talent to understand the data in a business context without investing in consultants to do relatively easy data tasks.

Without the right workforce, organisations simply cannot proceed to tackle the technical challenges existing in a data-driven industry. This can help to reverse the inconsistencies and set-backs with data-led AI projects. With the right analytics platform, data capabilities can be put in the hands of the business experts who not only have the context of the questions to solve but the data sources needed to deliver insights at speed. Trained data scientists will still be required, but the shortage of them does not mean all activity, or some level of a project, can’t be tested and iterated and progressed.

Existing employees should be still able to perform some levels of data tasks despite not being experts. They are in the line-of-business, close to the questions, the data, and the leaders who need insight. Linking up data insight for people with the vital business knowledge is paramount to making the most of data analytics and fuel business progress. What’s more, getting data in the hands of the people is crucial in order to democratise AI and make advanced analytics more accessible to everyone, rather than locked away by a ‘priestly caste’ of data scientists. Empowering citizen data scientists with the right support and self-service tools is crucial to help speed up adoption and share the benefits.

Historically, analytics has required skills like coding in R or other specialised languages in order to build out predictive models, skills that the average individual doesn’t traditionally possess. Modern zero code (or ‘code-free’) platforms are helping to make the democratisation of AI a reality. They act as a gateway into the analytical world whereby every employee can collaborate to transform data into actionable insights, not just a few where insights are taking months to deliver in the old model.

Demand for data democratisation has created a wealth of self-service solutions. The necessity of analytics platforms to tie together the data, workflows, tools and best practices needed for a diverse set of data scientists, engineers, compliance officers, and everyday business analysts just trying to do their jobs has driven this trend. Now individuals across every department can interact with their own and external data with the help of these technologies. In turn, businesses and recruiters can look at a broader range of applicants to fulfil data-driven roles than only certified statistical grads and expert data scientists who are in such short supply. And whilst those experts are needed, they are not needed to do every data task, investigation, and project to the exclusion of other skill sets and the functional knowledge that those within the line of business apply to problems using their own data.

With the ability to process and analyse data, the citizen data scientist is able to engage in an increasingly AI and data analytics-driven world, speaking the language of the new paradigm and contributing to their own success as well as their business by using the tools of the future to best effect.

Solving challenges with data is fun. There’s a genuine thrill to making smarter, faster discoveries that can alter the course of business, a market, or a career. And what was once painful, slow, expensive, hard to implement and just for the elite few, is becoming open, self-serve, ‘click, drag and drop’. Just as tech caused a boom in elite IT skills with complex technologies, it’s also gone on to open up the field with simplified ones too. Analytics has matured, and now a mass-market is open for those able to think in terms of data. While AI and automation may be becoming the popular dream of data analytics, companies that focus on empowering the next generation of citizen data scientists will not only gain better insights faster, but also realise the full potential of a technology workforce that can only multiply as AI increasingly comes into a well-prepared culture ready to make the best use of data science in new and exciting ways.

Nick Jewell, Director – Product Management at Alteryx. My passion is building communities of fiercely-enthusiastic individuals who become more than the sum of their parts. I love how technology can bridge the gaps in large, siloed organisations in unexpected ways. I thrive on the network effect and my role in making change happen.