How Is AI Shaping The Workplace?
In our recent research, the eighth edition of the Beamery Talent Index, we asked employees across the UK, US and Australia about their attitudes to work, workplaces and working life. One key finding was that skills are being left on the table – and learning, progression, and mobility opportunities could be useful levers in talent retention.
We also found that there was a disparity between the appetite and personal usage of new technologies, and the support provided by employers to help people get the most from these innovations.
The rise of generative AI ✨
There have been massive advancements in Artificial Intelligence recently, and naturally people are asking what it means for them. The incredibly fast rise of generative AI tools like ChatGPT have raised a host of interesting questions about the possibilities and risks opening up to the whole world.
Around half of those we surveyed in the Talent Index said they were planning to quit their jobs in the next 12 months – and 59% of those who are currently looking for a new role said that they had noticed Artificial Intelligence (AI) being used during recruitment processes. 50% said they had used it themselves as job seekers.
But numbers start to dip when we look at the official, sanctioned use of AI. 44% of respondents said that they had noticed an increase in the use of AI technology in their organizations (unsurprisingly this number was higher in the Technology sector) – but very few people are actually using it themselves, as part of their jobs. Just 15% said they using it in their role because it was provided by their employer.
The number of men using AI at work (47%) was higher than the number of women (31%), whilst 62% of those aged 18 to 24 are embracing AI within their current role. Given how AI is often used in conversations of fairness, and democratizing access to opportunities, it seems certain demographics are getting more from it than others.
Where is the training? 🎓
There is also a paradox when it comes to enthusiasm from employees vs training support from employers. 57% of our respondents said they were in some way open towards using AI-driven tools (21% said “welcomed” while 36% said they were open to using it but had some concerns), but just 16% are currently being trained in the use of AI for their current role. Only 35% of our respondents said they were very or somewhat confident that they were receiving the right training on developments of AI.
Allaying fears 😱
Of course, there are many apprehensions about AI – particularly its potential impact on employment and autonomy, as well as security fears. This could be holding some employers back from offering tools and training to their employees, and stopping some employees from being more vocal about getting these (often time-saving, bias-reducing and productivity-enhancing) tools into their organizations and teams.
The biggest concern was that it would take jobs – 37% are concerned it will reduce the human workforce. 33% say they are concerned it could stop people from thinking for themselves.
Employers looking to implement AI should of course ensure they keep humans “in the loop”, and emphasize to staff how AI can take on the more repetitive parts of certain roles, and free people up to focus on creativity, empathy and connection.
Tech can help 🔌
At Beamery, we believe AI can play a big and important role in improving talent experiences, for workers, leaders and HR teams alike. Technology can help you get more from your existing workforce, in numerous ways, if it is applied correctly – and as long as the training and communication is appropriate to staff, who often feel confused and concerned at the pace of change.
To take advantage of upskilling, reskilling and talent mobility as ways to boost retention and productivity, you need a better understanding of the skills you have and need, and you need to connect skills with the way you design and structure jobs at your organization. AI can be really helpful here, to give you rich, contextual Skills Intelligence that forms the basis of better talent-related decision making.