Work ItArtificial intelligence is the buzzword in town after China’s DeepSeek upstaged OpenAI recently. Many companies are also upskilling their employees with AI skills. But what types of AI skills do you need to do your job – and stay employed? Koo Sengmeng, head of LearnAI at AI Singapore breaks it down for Tiffany Ang and Gerald Tan.
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Hi, welcome back to the Work It podcast with Tiffany and Gerald. Now, not too long ago, someone asked me if my job can be easily replaced by artificial intelligence. If you asked me that question a year ago, I would say no because I didn't think AI can replicate my voice that perfectly or write a punchier introduction to the start of this episode. But these days, um I'm not so sure about that because I think AI might soon be able to write more creatively than I can.
But Gerald, do you use AI in your line of work? Yes, lots of it. In the process of guiding our clients with resume writing and job search processes, AI plays a really, really big part. It has made a lot of the painful parts of the process a lot more easy to live with. But I do also know that there are people who come up to me and also ask like, OK, now if I'm looking for a job, and then I'm looking at all these jobs that have AI requirements, right? So what do I need? How do I keep up to date?
With all these AI changes. Yeah, because I think for the average person, it looks like if you know how to use chat GPT just to shave off some time from writing an email or writing maybe a proposal, a deck, that should be enough, right? Yeah, I think that's the most obvious uses of AI, but I think today we want to go a bit deeper to understand how deep really AI can penetrate into different job roles and how we can keep up with that changes. So today I'm
Happy we have with us in studio, Ku Sing Ming, head of Learn AI at AI Singapore, to discuss more. Welcome Sing Ming. Hello, hi, thanks for inviting me. Singing, we've often heard that AI is reshaping our job roles and that it's not exactly going to be a niche thing if you have AI skills. In fact, it's going to be considered a core competency for many people, many jobs. So what exactly are these AI skills that companies want their work?
You're right that more and more companies are looking for their staff or future hires to have some form of AI skills, but then in itself, the AI skills can be a spectrum. It will largely depend on the type of roles, but I will kind of break it down into a non-technical requirement and a technical requirement. So for non-technical requirement, it focus less on
Your ability to code, your ability to actually create AI algorithm, but rather your ability to use AI tools that are quite relevant and useful to
The particular company's business area or the type of work and job functions that the company is looking for. For example, looking at tools to streamline workflows, to get things done better, faster, to even enhance creativity also. To your point, to talk about the opening intro itself, you definitely would have created own competency in creating punchy taglines, intros all that.
But it will be very useful for you to have an AI tool to help you to write up the draft and then you look at the draft and layering with your own tonality, your own personality that is very much your own. So AI will be seen more as a digital assistant. There are so many tools out there and many of them are actually free. So can the company leverage on this type of resources out there?
And they will be looking at people who are very effective and very creative in using those tools to achieve what the company wants and what the job requires. So that's the non-technical side. Then the technical side would be for the technical side itself, it is becoming more specialized. The requirements are also deeper. There is still requirement for certain types of companies, especially digital companies, to create a gorithm.
That will help to power their AI solution or digital solution, or they may have existing digital platform or digital solutions that will benefit very well from having autonomous AI agent operating inside. So companies will still be looking for people with coding proficiencies, for example, like in Python, they definitely is looking for people with data engineering skills.
Because today, how do you manage all the data sets that comes in and also the ability for you to, after you create an AI solution, how do you integrate it into your business back end? The term machine learning operations, the discipline of operating an AI model in a business environment.
Production environment. I think those would be very important requirement that companies will look for when they have technical requirements for such people. I think that's a very helpful breakdown. I see as like AI users and AI builders, the users are the ones who are using the benefit of the platform to augment their work to make things better, faster.
And then you've got the builders that they need to have deeper expertise to build the technology, build the algorithms, and then weave it into the business processes itself. So Sing Ming, for the majority of the industries out there, would you see that the demand is more for AI builders or AI users? I like the way you're describing it. Maybe I'll just contribute to a point. Singapore, we just released our new national AI strategy, version 2.0. We call it NAIS 2.0 for short.
We actually identify 3 types of AI talent archetype in Singapore. So, we have our AI users and what you call builders are actually AI practitioners, practitioners, right? And then the highest is AI creators. So 3 types.
AI users, AI practitioners, and AI creators. And this is a wonderful framework that not only guide a person, whether he or she wants to belong to each category, it also helps for organization.
To think about how many AI users do they want, how many AI practitioners should be part of the organization, and do I need the top AI creators also in my companies to help me to create new ways of solution, products and services.
Does that make me more competitive. Do you think most big companies need to have AI creators right at the top, at least giving the company a form of strategy to take the company forward? I believe so. You need to optimize it for your particular industry. For example,
If you look at a digital first industry, which means companies that operate on digital platform and a lot of their products and services depend on customer inputs or customer visiting their platform, for example, like Lazada, e-commerce platform itself.
Then these companies would definitely want to have more AI creators to create new and novel way of delivering their services. They would probably also want to have a lot of AI practitioners. So the ratio of AI creators, AI practitioners, and AI users could be evenly distributed across digital first industry.
Now, on the other hand, let's say Yakunon, Yaoon is in the business of serving quality breakfast. Do they need AI creators? Do they need they need AI builders maybe? Do they need AI users themselves? Yeah, could be as well, right? So then the ratio will be different, right? You definitely want to have your staff intelligently thinking about how can I do my job better? Was there an AI tool somewhere based on interaction with the customers, you can feedback to the company.
Can we have some kind of smart tools powered by AI to do certain things? So AI users will be one. Practitioners then would be probably the company having sort of a little development team or someone will actually know enough about technical details to work with either AI startups or AI solution providers. AI creators, to your point, maybe there isn't a need. They can just buy the model from somewhere else, right? You're right. So it's either which ROI serves you better.
So you perfectly encapsulate that ratio. Do you build or buy? Yeah, that's right. I think when we look at the AI practitioner, let's say at a practitioner level, in the different industries, what kind of job roles can we expect the practitioner to create? Let me give us some examples of industries or businesses so that we can visualize better. Some examples, it could be HR could be using the chat GPT.
Generative AI tools itself to look at generating certain types of JD that could be more targeted, that could be more specific. So, you could be generating more customized and more tailored one to screen out better applicants. Logistic companies are constantly interfacing with their customers, could be angry customers or the suppliers or that.
Could there be a form of automated email replies because several of the email transactions could be just updating of information or simple queries or that. So that could be one, which then also lend into customer facing functions across a variety of industries itself. This could be some of the broader areas which a lot of interaction can be automated away.
If it's more of simple reply, simple clarification. On a more deeper aspect of application and usage, right, you could be using GAI tools and more advanced AI algorithms to assist in your product planning. You could also be using it to be more creative.
So it's not about AI taking creative away from the industries, but rather enhancing creativity. So we can have companies that help in terms of looking at defect reduction. So we have a multinationals that was looking at manufacturing. So for them, manufacturing production you, defect you is very important. Can you build a machine learning algorithm or predictive system?
To help to predict which type of product lines would have a higher defect yield, finding out the cause, what causes that. So when you find out the cost and you can lower the defect rate, you can actually apply that to other product lines, makes for better product planning.
So, so even in the non-technical side, product planning itself, companies that are looking at future consumer demands or that could use AI tools to vastly integrate huge amount of information from the internet and consolidate them.
And provide either certain trend or analysis or even suggestion itself. For the creative industry itself, I came across this company called Mighty Bear. So Mighty Bear is a games company. They also help to look at providing some creative design for clients or that. And when they talk about generative AI Dale stable diffusion, all that, it is the opposite of, oh.
Clients now will be using Dale or stable diffusion and they don't want to engage us. In fact, it's actually the opposite because by being able to use those tools, they are actually generating more designs for the client to choose from. So in effect, the opposite has happened. They have become more creative, they have become more responsive to clients' needs.
And all in all, it actually enhance the client's experience itself. So if somebody says, OK, you know what, I've tried AI and I'm really not as good because this whole computer thing doesn't quite jive with me or I find it very hard to learn. So then what do you say to somebody like this who feels that they may not be able to pick up AI skills as quickly as the people around them. Hm.
The term AI skills can be quite broad. Many will interpret it as, oh, I need to learn coding, I need to understand what is machine learning, I need to understand what's deep learning, structured unstructured data, the technicalities of it, and
For someone, a working professional who has spent years in their own subject matter, honing their own skills itself, it could be quite a leap. For the average worker is I still love what I do. I'm being asked by the government, by the company to pick up AI skills.
Actually, what the company is looking at and what the person should be thinking about is what kind of AI tools can I use to make me become better. Yeah, I agree with what Ze Ming is saying here. I saw this report recently about social workers because a part of social workers, they have to do case notes and case notes takes a lot of time to record down the details to conceptualize about a client's background.
They found a way to use AI to create the case notes. So every conversation is transcribed. It comes out in bullet points and it's formed into a template for case notes and then wow, with the time savings, the social worker can spend more time with the families, spend more time talking, investigating a little bit more, and helping on the ground. So I thought that, wow, this is a really good example of how it can really augment and allow us to personalize a lot more.
If AI can help to take away the admin part of it, then it actually reduces in the long run that burn out as well because I think a lot of people who are in healthcare or in social work, they are also saying that we want to be in the field to do the work, but sometimes it's like the paperwork that really gets to us. And now if we equip ourselves with these skills that can make our jobs even easier, even more streamlined, then we can do the
thing that we signed up for the things that we really, really love. I think we've gone beyond the conversation of whether AI can replace our jobs. I think here is where we are asking how can AI really partner us to do our jobs better? How can we at least get baseline competent in the next 35, 10 years in our jobs. So thank you so much for coming on and sharing with us. Thank you for inviting me to speak.
Hi, we're back with our Ask Me Anything segment where we take a work-related question that you've said. So let's start. Today's question was sent in by Sandra. Sandra requested and submitted an application to work from home for 2.5 days under the new flexible working arrangement guidelines. Just to recap, this new policy kicked in last December and employees may submit a request.
For flexible working arrangements, but this is still subjected to the employer's approval. Now, Sandra is asking for this because she says her husband will undergo cataract surgery soon and she needs to be home during the day to care for him while fulfilling her work duties.
Sandra says that her request was rejected and her boss told her to apply for the 2.5 days, but this time of annual leave instead. The reason given, encourage employee to clear annual leave.
Yeah, I think the challenge here that Sandra faces is really what qualifies as leave and what qualifies as flexi work. With the new FWA kicking in, I'm sure we will have a lot more of these sorts of requests because it's becoming unclear to people when should we be asking for flexible work and when should we be taking leave. So I think for me, the difference here is really from an employee perspective, the difference.
Here are 3 things. One is our attention to our work. I'll be able to dedicate and devote our attention fully to our work. And also, the second thing is our availability to respond to contingencies to request on the job. And the third thing, of course, is the capacity to complete the work that we said we would do. So I think when we think about flexible work arrangements, we have to take these 3 things in mind.
So that we know whether it's, are we still able to perform, to cope, to pay attention to our work while we are away, let's say in Sandra's case away from the workplace. Yeah, so the three factors again just to recap, attention to work, availability to respond and capacity to complete. So these three factors need to be taken into account. Yes, because when you are working from home
Still at work, right? So you'll definitely need to be within reach from your team, from your bosses. You need to be able to pay attention to your work and you need to generate output, right? So in her case, I'm just wondering like why the company would recommend for her to take annual leave. It could be because they might find that they are not sure whether she needs to devote more of her time and attention to caregiving, whether she's available to respond when they need her to.
Correct. So on one hand, we can see as like they are rejecting her flexible work arrangement request, but on the other hand, they could really be just helping her to prioritize what's really important. Like if care for your husband is really important and you have to be there, then maybe it's better to devote yourself to the care, rather than try to split yourself both ways, right? But of course, for a lot of us, we feel like we can manage everything and that's why we want to do the flexible work arrangement. So if that's the case, then maybe Sandra really ought to just have a discussion with the HR to explain why.
Like why taking leave would be overkill, or be too much for her situation and how she's still able to cope with her work capacity, to respond on time, and that her attention would not be diluted too much if she's providing care for her husband. Flexible work arrangements should not be a decision, like a judgment, right, like or it's stamped already. I think it should be more of a discussion. Both sides need to engage in conversation to explain why certain things are done. Yeah. So on that point, if the flexible working arrangement is rejected.
Sandra could perhaps also still have a conversation with her superior and to say, you know what, could I maybe take some time off? Let's say my husband has to go for a follow-up checkup, can I take some time off on this day, and then I'll come back and work another 2 hours or 3 hours. I think like you say, it's always a discussion. They might actually be open to letting you be away from the keyboard for 2 or 3 hours and then come back and pick up the work. So the guy is there, but we need to learn how to communicate and converse properly. Employees really need to know.
How to put up a case and to explain how they can still be productive. At the same time, employers also need to start to realize that, hey, I'm not able to get 100% of an employee, right? Even if today someone goes to work sitting in front of the computer at the workplace, you may not be getting 100% attention from that person, right? So the employees also on the other hand, need to know that, OK, what's the bare minimum that I'm willing to accept, to say that if today you're out of sight, I still know that you're performing even though your attention might be divided. Yeah. So this is something that I think we will need to.
Figure it out along the way, right? There's going to be a lot of teething issues, I think surrounding the new flexible working arrangement guidelines and we're working on a longer podcast so that we can discuss this in greater detail. But Sandra, thank you for your question and we really hope that your husband will recover very, very soon. If like Sandra, you have a work-related question, do write to us. We are at CNA podcasts at Mediacorp.com.sg. You can also find us on Spotify, Apple Podcasts and YouTube.
The team behind the Work It podcast is Christina Robert, Joan Chan, Juani Johari and Saye Win. Sound mixing is by Carrie Lim, video by Reza Rahman and Hanida Amin. I'm Gerald and I'm Tiffany. Here's wishing you a good work week ahead.