Leadership expert says managers should test assumptions about older staff and pair generations as mentors
Organisations restructuring around artificial intelligence (AI) risk losing valuable institutional knowledge if senior workers are pushed out or left out of training, according to Dr Zsuzsanna Tungli, founder and managing partner of Developing Global Leaders Asia.
Tungli said senior employees are often among the most affected when companies go through transformations, particularly when they are offered early retirement or redundancy packages.
"This may be seen as cost saving for the organisation, but on the flip side, a tremendous amount of institutional and tacit knowledge can be lost," she told HRD.
Tungli's comments come as Singapore prepares to raise its statutory retirement age to 65 and its re-employment age to 70 on 1 January 2029, a year ahead of the original timeline, after the government accepted all six recommendations of the Tripartite Workgroup on Senior Employment.
Equal access to AI training
Tungli said inclusive leaders should give employees of all generations equal access to AI training, which she noted remains far from widespread. Aon's 2026 Human Capital Trends Study found that only 18% of organisations said most of their workforce had taken part in AI reskilling or upskilling programmes in the past year.
"Equal access to development opportunities can create a more level playing field for senior employees," she said.
"No coding or other IT experience is necessary to use many of today's AI tools. The fact that senior workers didn't grow up with social media is no disadvantage here, even if their limited exposure to earlier technologies may have previously excluded some of them."
Tungli also urged leaders to recognise and redefine people's strengths in the age of AI. She added that senior workers would be well placed to validate AI outputs because they "often know where the real risks, workarounds and client sensitivities are."
Testing assumptions
According to Tungli, managers commonly assume that older staff are not interested in technology, will be slower to learn, are winding down, or are not worth training so close to retirement.
She said a quiet senior worker who avoids new technology may simply not want to lose face by asking a basic question in front of younger colleagues.
"Ask people directly what they want to learn, in a safe environment where their needs can be addressed," she said.
Tungli also argued that training older employees can pay off because people are working longer.
"A 60-year-old may have close to 10 more working years ahead of them. The investment can certainly be worthwhile from the company's point of view," she said.
She urged managers to look at who is invited to AI pilots and training: "If it's always the same younger faces, that's a pattern worth checking."
Shaping AI adoption
Beyond providing equal access to AI training, Tungli said managers should actively make use of senior workers' experience. Her recommendations include:
- Ask them to spot what could go wrong. They know the exceptions, the customers and the history behind processes. They may recognise when data points are wrong or missing.
- Ask them to validate AI outputs. Does AI draw the right conclusions and suggest the best solutions? Senior employees are often well placed to pick up mistakes based on their experience and extensive knowledge.
- Create mentoring pairs between generations. Younger staff can help senior colleagues learn new tools, while senior staff can share their knowledge of the business context and how to validate AI outputs.
"As many entry-level positions may be impacted by AI, more emphasis should be placed on knowledge transfer between older and younger generations," she said.
On adjusting roles, she recommended one-to-one coaching conversations rather than managers deciding on employees' behalf.
"Don't assume what your senior employees want or don't want to do," she said.
Managers should ask employees what they enjoy, what they would like to learn and how their experience could best be used, then create a plan together with clear deadlines and accountabilities, she said.
Tungli also called for flexible working arrangements, including part-time and remote work, so companies can continue to benefit from senior workers' experience "without necessarily employing them full-time."
The role of HR
Tungli said HR should set policies on AI use, prepare managers for coaching conversations and support younger managers who lead older employees.
"Inclusive leadership means handling that respectfully, without avoiding difficult conversations or talking down to anyone," she said.
She said this can be particularly challenging in hierarchical cultures. A 2018 Randstad Workmonitor survey found that 83% of respondents in Asia preferred to work with a manager their own age or older.
She recommended practical training on working in multigenerational teams, including role-plays on giving feedback and having difficult conversations. She also suggested informal activities such as "meet a stranger" lunches, where employees are encouraged to talk with someone from a different generation.
HR should also review data on who receives training, promotions and new projects for patterns suggesting bias, and share the findings with managers, she said.
Tungli cautioned that senior workers are "not a homogeneous group," and that a 55-year-old engineer and a 65-year-old in operations have very different needs and goals.
"Make sure the 'AI champions' include senior people. Who leads the change sends a strong message about who belongs in the future," she said.
