Reaping the benefits of automation and artificial intelligence

Picture this: You are cruising along Uhuru Highway and all of a sudden, your car comes to an abrupt halt, exactly two metres from the car in front of you, without you having hit the brakes. After 30 minutes on the roads, you arrive at the main entrance of your place of work, at the exact time the car informed you when the journey started.

You disembark and make your way to your office just in time to see the car finish parking itself as you peer through the window to confirm that it is still in one piece. As you settle in at your desk, you get a prompt that the automated bank reconciliation system has successfully completed its work on 30 different bank accounts—all while as you were sleeping through the night.

You walk into your first meeting well-rested and well-prepared. This scenario may sound like one taken straight out of a sci-fi film but it is a reality that will confront us very soon and thanks to the power of artificial intelligence.

According to a study done by PwC, ‘Sizing the prize’ (2017), it is estimated that up to 14 percent of global GDP will be attributable to smart automation by 2030, an equivalent of $15 trillion in today’s economy.

On the flip-side, the landscape of the labour force is set to drastically change as automation takes over people’s jobs, leading to increased unemployment and redundancies.

With that in mind, the responsibility falls upon us as human beings to maximize on the positives and minimise on the negatives that this drastic change will most certainly bring. According to research conducted by PwC economists, building on that done by Frey and Osborne (Oxford University, 2013), automation of jobs in the years leading to the 2030s will occur in three successive waves namely the algorithm wave, the augmentation wave and the autonomy wave.

Each wave will have varying impacts on different occupations, industries and demographics.The first wave, which is already upon us and is estimated to come to maturity in the early 2020s, involves the automation of both regular computational tasks and the analysis of structured data.

Its impact will be felt most in occupations and industries that are data-driven such as the financial sector. The second wave, augmentation, is predicted to mature in the late 2020s and entails the automation of tasks that can be repeated such as arranging files and upgrades to the algorithm wave such as unstructured data analysis in a partially-controlled environment.

By design, the augmentation wave is likely to affect most the jobs of clerical workers. The third wave, autonomy, could come to maturity in the mid-2030s and could put at risk physical labour such as transport and factory work when machines adapt to performing routine tasks and problem-solving in real-world situations.

Effective public policy can help us to avoid a double tragedy where jobs are being lost without being replaced and the advantages of automation are not being exploited. One of the key drivers of automation risk is task composition and specifically tasks that are manual, routine, computational, managed, social or literal.

Another risk is education and the specific skills, focus areas or training options that will prepare the workforce for automation such as a focus on STEM subjects (Science, Technology, Engineering and Mathematics) or training in creativity, flexibility and value addition.

Musembi is an Associate with PwC Kenya’s Assurance practice, Thuo is a Manager with PwC Kenya’s Assurance practice.