Sarah Gilchriest is Chief People Officer at Workforce Learning, the group that encompasses QA, Circus Street and Cloud Academy. Sarah is passionate about creating a business that is thriving creatively, financially, and culturally. Sarah’s priority is driving the businesses exponential growth and global expansion without sacrificing the people-focused, award-winning culture of which the business is exceptionally proud. Previously, Sarah was President of Circus Street, joining the company in 2016.
THERE HAS BEEN PLENTY OF TALK IN THE MEDIA IN RECENT MONTHS ABOUT THE LONG TERM IMPACT OF AI, PARTICULARLY WITH THE MUCH HYPED INTRODUCTION OF CHATGPT.
Some of the focus of this has been around the way in which the automation of business functions could lead to mass redundancies.
One recent report from Goldman Sachs put the figure at 300 million jobs in Europe and the US alone, and BT has announced it would cut 55,000 jobs over the next seven years and replace them with 10,000 new roles in AI.
Whilst this may cause concern, it is important to remember that, firstly, this is going to be a drawn out process and we remain a long way from AI being capable of taking on lots of skilled jobs. Companies that do make use of it will also require comprehensive human oversight. Secondly, this expected technology driven revolution is by no means the first time we have seen such change – work roles have constantly evolved since the industrial revolution, with some becoming obsolete while entirely new careers take their place. According to economist David Autor, 60% of workers are in occupations that did not exist in 1940.
Change in the workplace may be scary, but it is also inevitable, and it requires an ability to adapt.
The key to thriving in this new era as a business and as an individual lies in the ability to recognise the opportunity that AI offers to increase productivity and remove a lot of the mundane workday tasks, and to grow with it. As an employee, you should be looking to take steps to future proof your career and ensure that as AI, or indeed any new major technology advancement, changes working practices you are in the best possible position to respond.
The same is true for businesses. Used correctly by businesses and it will manifestly improve working conditions while at the same time spurring innovation, efficiency and ultimately, profitability. But there is a well documented global skills gap in technology which is particularly acute in data-related fields. As AI advances this gap is only going to increase and push the cost of hiring data-skilled workers higher. Using AI effectively within a business requires widespread data skills which are best acquired by upskilling existing teams.
Where should you start when looking to upskill or retrain to future proof your career, or to implement a program for your team? First off, it is important to understand that there is no one size fits all approach. Every person will have different career ambitions, potential exposure to AI and expertise required in their role. Reskilling is often a long term process, and for most people quitting their current job and dedicating time to retrain in a new field is impractical and undesirable. It is also highly likely to be completely unnecessary. The reality is that you do not need to become a data scientist, analyst or engineer to always be employable. Every new technology is divided between those who develop, implement and maintain a solution and those that know how to best use, manage and innovate with it. The vast majority of professionals will fall into the latter category with AI.
Therefore, for most people your starting point should be determining how you can best use data, and by extension, AI, in your existing role. This has the added advantage of being an attractive strategy to most employers – they want you to be more effective in your current position – and as a result, may lend a lot of support to your upskilling.
At QA Workforce Learning, we have found that the most popular skill to learn in the first instance in the past year is basic data knowledge. Understanding how AI works and the foundations of data analysis will help you to ascertain how you can better apply data today while also getting to grips with the potential long term impact of AI on your profession.
From there you can begin to plot out how you can build on these skills and evolve your career.
With a multitude of ways available to learn skills these days, from online to in person, to professional development courses to ad hoc targeted skill acquisition, everyone should be able to find a format that suits your mentality and lifestyle the best. You should look to engage with your employer on your training journey to make sure you have the opportunity to put what you are learning into practice at the earliest opportunity. Many businesses do offer upskilling programs, those that don’t should be willing to help you with your independent learning if you make a good commercial case. If you don’t shy away from the opportunities that are offered by the development of AI, and commit to supporting your professional growth through upskilling, you can ensure that you are best placed to thrive in this exciting new era of technology.
