AI IS A DOOR TO PRODCTIVITY GAINS, BUT DATA LITERACY HOLDS THE KEY

When it comes to overall productivity, the amount of meaningful output we achieve during that time, we are 26 percent less effective than the average worker in Germany.

Expert opinion is converging around the idea that technologies including Artificial Intelligence (AI) may hold the keys to solving Britain’s productivity puzzle. The UK government has put investment in AI and data at the core of recently published industrial strategy whitepapers.

As much as this approach seems sensible however, there is a danger that we focus too much on the technology itself and too little on what we actually want to do with it.

A report by PriceWaterhouse Coopers found that 69 percent of employers will demand data science and analytics skills from job candidates by the year 2021.

Yet according to a separate study only 17 per cent of UK workers can be classed as “data literate”, with a further 40 per cent feeling overwhelmed by data in the workplace.

Whilst there is significant investment taking place in the core technologies which underpin AI, the ability to turn the data it produces into valuable outputs is frequently siloed off as a specialist skill, held by a few highly qualified individuals.

Granted, certain aspects of AI and data science require specialised technical skills, but the reality is that almost every job function in every sector will be touched in some way by data. Everyone from the HR department through to the boardroom will need to be able to read, understand, and communicate data as information.

A significant part of the challenge facing government and businesses is to shatter the mystique around data and instil data literacy as a core competency across a far broader cross-section of the workforce.

The scale of this challenge is significant, requiring a top to bottom approach, beginning with the way we teach our children in schools. Changes to the curriculum must be implemented which reflect the increasing requirement to analyse and interpret complex data sets in the workplace.

Teaching of these skills should not be limited to STEM subjects, but embedded as a core competency across every subject. For as long as we have had schools, children have been encouraged to conduct analysis of source materials to build an argument. Those same principles apply today.

What has changed is that the complexity and the volume of the available sources has grown exponentially. Whether a child is studying physics or history, they will need both the mindset, understanding and skill to extract value from this data.

Change on this scale will not happen overnight and relying on the next generation to take the reins will leave us far behind any competitors that embrace data literacy now. Addressing the skills gap requires a more co-ordinated approach to open up the talent pool and improve data literacy among the current workforce.

According to a recent study we produced, 83 percent of UK employees say they are required to use data on a weekly basis as part of their role, yet 49 percent say they have never received any form of data literacy training.

Businesses are waking up to the need to offer training to the broader workforce. M&S recently announced the creation of its own data academy, while many others are investing in on the job training to help upskill employees.

For our own part, we have joined forces with digital transformation and leadership training specialist AVADO to develop a new range of interactive courses designed to help organisations and individuals upskill and become more data literate.

Part of this partnership has involved co-creating an apprenticeship programme for data analysts that will be accessible to businesses through the Apprenticeship Levy.

According to a recent government report demand for data analysts in the workforce is set to increase by 243 percent in the next five years. Over-reliance on universities to meet this demand is both impractical and likely to be prohibitively expensive for all but a very few organisations.

Investing in high quality apprenticeships has a vital role to play in easing the current strain on supply and ensuring organisations have access to a more diverse talent pool.

If further evidence of the value of this approach is required, take a look at Germany, where technical schools and apprenticeships hold equal prestige to university education.

The renowned computer scientist Yann LeCuf once said, “Our intelligence is what makes us human, and AI is an extension of that quality.”

AI and the data it produces form only part of the equation. For these technologies to have any meaningful impact on productivity, we must avoid the temptation to become fixated on the technology itself and make data literacy a priority for the workforce of today as well as the workforce of tomorrow.