How GenAI enhances employee productivity and learning

Generative Artificial Intelligence (GenAI) has made a great impact on employee productivity, enabling them to do their jobs better, from composing emails, preparing PowerPoint presentations, to improving service delivery.

But at the same time, GenAI also brings challenges: The fear that employees are losing their jobs or that their work are being taken over by AI. 

“It’s a matter of perspective whether you see GenAI as a partner or a competitor. Probably the best position we can give AI is as a digital companion to help us do our work better,” said VITAL’s Deputy Chief Executive, Yuen Sai Kuan.  

Yuen noted that AI is not at the stage where it would completely take over the jobs that humans do.

What we need to do now is put AI in the hands of individuals and then let them go as far as they can, he added.  

He was speaking on the Leveraging GenAI to Enhance Employee Engagement panel session at GovInsider’s Festival of Innovation in March. 

Other panellists included National University of Singapore (NUS)’s Chief Information Technology Officer Tan Shui-Min, Civil Service College (CSC)’s Assistant CEO for Digital Strategy, Patrick Lau Wei Peng, and SAP’s Regional Business Head, Varun Thamba. The panel was moderated by Air Selangor Malaysia’s Head of Organisational Change Management, Diana Jayasauri. 

The speakers discussed the opportunities and challenges of using GenAI to reshape employee engagement based on their experiences in their respective institutions. 

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Improving productivity with GenAI 

NUS’ Tan shared how GenAI has become a productivity booster in her organisation, taking the example of the AI solution in the NUS hostel enlistment system.

AI was used to help administrators process applications and decide who would be able to get the last few lots in the hostel, where applications at times reached upwards of 6,000. "With the help of AI, what took us weeks, with a lot of administrators involved, is now reduced to a day. 

"Does it take our colleagues out of work? No, it allows us to deploy them to do more meaningful work,” she said, adding that NUS had been developing its own AI productivity platform and tools before OpenAI launched ChatGPT. 

CSC’s Lau noted that as GenAI  helps employees to work faster and efficiently and organisation will have more “productive savings”. 

He urged organisations to be open to any opportunity to reexamine the work-life balance and reimagine what possibilities may exist. 

“Where before we could take weeks to prepare a presentation, it now takes just three seconds. There is a lot of time we saved. But then what do we channel that time to?” he questioned. 

SAP’s Thamba noted that  GenAI’s potential in improving the employee lifecycle, adding that the expected outcome of AI adoption is not only about driving business values, but also how it changes people’s lives. 

“GenAI will free employees from their mundane tasks and allow them to go home at four instead of six in the evening, for example, and let them do other activities with their invested time,” Thamba said. 

Personalised learning for employees 

When it comes to employee engagement, the panellists emphasised that GenAI can enable personalised learning for employees, even providing on-demand training. 

"GenAI allows us to match the competency and proficiency of employees with the type of training, where they can consume the training in the format they want," Lau noted.  

Currently, CSC is exploring a curriculum that will make learning highly engaging and customised to what employee's need at the time they want it.  

The challenge then is how to create a system that can integrate HR data across government agencies, including employee competency data, employee skills data and skills gap data, he added. 

Meanwhile, Tan added that organisations need to adopt a lifelong learning mindset to cope with rapidly evolving technologies. 

"Training is not a one stop destination. [We need to] invest in AI literacy, training employees to adopt AI, then employees will be ready to pivot and tandem with technological changes.” 

She added that NUS’ IT Division took the initiative to be an enabler in the learning process through the Digital Enablement programme that includes GenAI. 

"We have now trained more than 5,000 of our colleagues in dozens of digital tools, of which 1,000 trained just on GenAI alone," she noted. 

Ensuring accountability and transparency of AI 

At the end of the session, moderator Jayasauri asked panellist about the best methods to maintain transparency and accountability of AI-driven decisions.

Yuen responded by noting that humans must still play a central role in the decision-making process. 

He gave an example of an AI-powered recruitment system that makes it easier for staff to conduct the selection process but cannot guarantee that there is no bias in the selection process.  

"Please keep in mind that AI is not a final tool, but a decision-enabling process tool. So, it is important to keep training the AI to ensure it gives us the output we want," said Yuen. 

Thamba added that before we infuse AI into an application, it is important to include a human in the loop approach in it. This is important to ensure that there is trust in AI and remove ethical bias. 

You can find full FOI recording on the GenAI panel on-demand here.