AI (Artificial Intelligence), High-trust leadership
The rise of Gen AI promises to revolutionize the workplace. Here鈥檚 why the best workplaces are focused on improving human performance, rather than replacing it with machines.
Are your employees open and excited to use AI at work?
Surveys show that a lack of trust threatens to impede adoption of new technology all over the world. Employees are concerned about how AI will change, or even replace their jobs 鈥� but their minds can be changed.
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How leaders talk with employees about AI and the change it will create is paramount. 鈥淲e have to make sure that people understand that they鈥檙e uniquely qualified to do things that nothing else can do,鈥� Bond explains. 鈥淪o, how do we build trust around this new teammate that we have that can augment our ability to do our jobs?鈥�
All the leaders believed that the rise of AI presented opportunities for people willing to seek new skills.
鈥淚鈥檓 very positive that we will need a lot of humans going forward in all sectors,鈥� says Trine Str酶msnes, managing director, Cisco Norway. 鈥淏ut we need to really come with [AI] competence. Competence needs to be part of everything we do.鈥�
Compelling use cases
What does it look like when companies introduce AI tools in an employee-centric way?
Aviva, Teleperformance, and Cisco all see AI as a way to eliminate repetitive tasks and increase productivity. 鈥淚f we can automate repetitive tasks, that is a good way of using gen AI, but it鈥檚 also freeing up resources for more strategic and creative activities,鈥� Str酶msnes says.
More exciting applications are starting to be explored around hiring and talent management.
Bond gives an example of a sales team that can use AI to practice their pitch or hone their selling skills. 鈥淚t can almost be like a sparring partner,鈥� he says.
Other use cases include employee retention, using AI tools to monitor employee data for risk factors. 鈥淲e know through experience there are certain signs,鈥� says Winters. 鈥淪o we use this tool to pull all that data, and arm our retention specialists to do proactive outreach to find out what is going on and help solve a problem before it becomes a problem.鈥�
Where can things go wrong? Using AI to scan r茅sum茅s from potential applicants, for example.
On the one hand, AI tools dramatically lower the cost of sifting through thousands of applications. 鈥淎re you going to staff a recruiting team for one role with 5,000 applicants?鈥� says Winters. 鈥淭hat鈥檚 a hard question, right? It鈥檚 expensive.鈥�
On the other hand, when you think about the experience of a candidate going through your hiring process, AI tools can create a bad experience for someone you hope will join your company.
There鈥檚 also the potential for bias. 鈥淲e don't know enough yet about the bias that exists in the system, which worries me greatly,鈥� says Harmer.
鈥淚f you鈥檙e looking to hire diverse talents, then the data the AI models are trained on is really important,鈥� Str酶msnes agrees. 鈥淚 would never take out the human element in that loop.鈥�
Changing what work looks like
How employees build a career will look very different thanks to AI advances.
People will always be needed, but the work they do will be very different. Harmer points to the typewriter and fax machine as historical examples. These machines used to be at the heart of entry-level jobs in the workplace, and now they don鈥檛 exist.
Expect the trend to continue, Harmer says. 鈥淩esearch skills aren鈥檛 going to be as important,鈥� she gives as an example. 鈥淲e may not be able to think immediately of all its capabilities 鈥� but we are building it and also bringing people into the workforce and educating them.鈥�
But companies will always need people.
鈥淧eople will always go to where they want to be served,鈥� Winter says. 鈥淚 don鈥檛 believe that we鈥檒l get to a point where the human aspect will ever be 100% replaced.鈥�
