At the start of the year, I had a chat with Kevin, our head of the AI Advisory team here at AI Singapore (AISG®). We talked about our personal experiences with career transitions into AI. In this conversation, he shares more about his work at AISG helping companies, large and small, to chart out their own journeys with AI.
Below is a transcript of the conversation [*].
If you are keen to know more about the programmes mentioned (including the 100E), you can contact the AI Advisory team at firstname.lastname@example.org for further information.
Basil : Hi Kevin. Great to have you here again.
Kevin : Hi Basil. Good to be here again.
Basil : So, previously we talked about mid-career transitions for mature PMETs and today you find yourself leading the AI Advisory Team in AI Singapore. Tell us about your role and the mission of the team.
Kevin : Sure. So, currently I’m the head of AI Advisory in AI Singapore. The main responsibility of my team is, in a nutshell, to help Singapore companies, both large companies and small ones to adopt AI. As you know, AI is fast becoming critical to the competitiveness of businesses in many different industries. In some industries, AI is no longer a nice-to-have, but rather a critical tool that determines the survivability of the business. That’s why I think the Singapore government has invested heavily to help local companies, as well as Singaporeans, to upgrade themselves to be AI-ready, so that our economy can be competitive in the coming era. Therefore, our job is to catalyze this transformation. We run different digital transformation programmes for large corporates as well as SMEs, even start-ups, so that they can run faster in the adoption of AI technologies.
Basil : Yes, I think this is certainly an important component in the next stage of our nation’s development. So, as you mentioned, our economy has become more diversified since independence. Different organisations would therefore have different starting points on their journeys to adopt AI. Could you elaborate on how you address such a differing range of needs?
Kevin : Certainly. Yes, companies have very different maturities and readiness. They are at different stages along their digital transformation journeys. On the one end of the spectrum, you see companies that are interested in AI, but they don’t really know much beyond that. For these companies, our goal is to help them understand what is AI and how does AI help their business. Unfortunately, there are lots of confusion and misinformation out there. So for these companies that have just started on their digital transformation, it could be quite daunting. We try to help them with things like AI Clinics, which are workshops targeting specific industries. We invite people from that particularly industry to the AI Clinics. These participants are typically business owners, business unit heads, decision makers from a specific vertical industry. In that workshop, we share with them success stories and AI use cases pertaining to their industry. We go beyond theory. We focus on practical aspects of AI in business. And important to note that our team members comprise professionals who are technically trained in AI with many years of commercial experience. For example, I myself am a certified AI engineer, but I have also spent over twenty-five years managing businesses. Therefore, we are able to talk to business owners in languages that they can understand and also help translate the benefits of AI in a way that makes sense to them and through these AI Clinics, we hope to trigger their curiosity and create the interest in them to explore AI in their own companies. So, the objective is really to equip the participants with enough knowledge so that they can start the conversation within their organisations about AI.
If they get to a level of interest that they want to explore potential ideas, then at that time they can come back to us. When they do, we have another programme called the AI Discovery, which is a one-to-one consulting engagement to help companies to ideate and also to prioritise those ideas into actionable next steps. In the AI Discovery programme, companies will share with us their business priorities and their goals and then we will help them look at which ones of those are solvable by AI. As AI Discovery is often conducted under NDA (non-disclosure agreement), companies usually will share with us their actual data sets. With the data sets, we are able to help them look through, to see whether they have enough data and the data is in the right format and whether they are appropriate for the AI projects they want to embark on. At the end of the AI Discovery, the output is a consulting report with specific recommendations. These recommendations could be, let’s say, an AI project if they are ready to do that or just suggestions on the specifications and the project goals. But sometimes, we might also find that the companies do not have enough data to support the project and in those kind of cases we then will recommend to them what type of data they would need to collect and how to go about doing that. And then after that, for those companies that are ready to do an AI project, we will take one step further to recommend to them various ways of doing that. For example, the most obvious one is they could explore the 100 Experiments (100E) programme in AI Singapore. The 100E is a heavily subsidised programme for companies that are embarking on their first AI project and we focus on projects that require technologies that aren’t readily available in the market. Alternatively, they could also make use of something called Bricks. In AI Singapore, we develop reusable AI technology components which we license to local companies either at no cost or at very low cost so that we can help them speed up their AI project or to reduce their cost. Lastly, if we find that the best alternative is to make use of commercially available products or services, we would also advise our customers to do so. As AI Singapore isn’t a commercial entity, our end goal isn’t really about selling a service or a product to companies, but rather to give them the best advice on how they can go about doing their AI project. Therefore, we will try to help our customers in ways that are best for them.
Basil : I think the fact that AI Singapore isn’t so-called commission-based is a unique reason to engage us. Maybe let’s take a step back. What are the kinds of opportunities you see as impetus for companies to adopt AI?
Kevin : That’s a great question. Many companies do see that the current environment around them is fast changing and business owners whom we have spoken to told us consistently they’re looking for opportunities either to increase their sales or to reduce their cost, especially after the COVID pandemic. These are the two things that are at the top of the minds of business owners, whether they’re big companies or SMEs. These are the things that the bosses are most worried about. The ability to do so is critical to the survival of their business. They know that business-as-usual after COVID is not an option. So they want us to help them understand how they could leverage AI to achieve either or both of them. Therefore, I think scoping the opportunities of AI from the perspective of either increasing sales or reducing cost is the easiest way for business owners to understand.
Let me give you an example. AI is able to help companies understand their customers better, like which customers are likely to purchase what products from you in the future and which customers are potentially at risk of churn, meaning stop buying products from you in the future. So if you know that, then you can take appropriate interventions to either stop the churn or to sell more products. In the past, such knowledge might reside in the heads of very experienced employees or just within the sales organisation. The problem is, such knowledge is hard to retain. When the experienced employees leave, they take the knowledge away with them. It is also very difficult for companies to institutionalise and share such insights throughout the organisation even if they wanted to. By using AI, we can extract such insights out from historical data in a much more systematic and data-driven way. With the help of AI, companies could potentially find out more about their customers in a way that they couldn’t otherwise. There are a lot of times after doing the AI project they find things about their customers they didn’t know in the past. Therefore, such insights can then be shared broadly across their organisations helping decision makers to make better decisions, as well as more timely decisions. So, such things like demand forecasts, customer recommendations, sales prediction etc are very popular requests among companies in Singapore. AI can definitely help our companies to do these things more effectively than the traditional way and hence increase their sales opportunities. Likewise, there are many opportunities for cost reduction as well. You know, people talk about automation, that is obvious. That can be done by digitalisation, but AI can take that one step further. For example, AI can help businesses do better product quality checks through computer vision. AI can also process customer requests through NLP (natural language processing). NLP is a branch of machine learning that has improved tremendously over just the past few years. This technology is now able to understand human language, whether it is text or verbal. So with that, companies can actually automate many mundane tasks of responding to customers in a much quicker way, but at the same time reduce the cost of doing. These are some of the examples that we see in the market in terms of the potential of increasing sales or reducing cost.
Basil : What about at the individual level? What does it mean for the individual in such a AI-pervasive future?
Kevin : Yes, that is an important topic. We read a lot in the media and sometimes people worry about AI replacing jobs. Actually, I think that is a misconception that is unfortunately perpetuated by popular media. In reality, AI can help automate tasks but often not the entire job. There are some jobs that can be totally automated away, but that’s not very common. On the other hand, the tasks that AI can help to automate and do better are typically those that are mundane and repetitive. AI can actually make the job more interesting for humans by letting them focus on tasks that require creativity and human empathy, for example. So the reality is, AI will not totally replace humans, but rather those who learn how to use AI as a tool will become more competitive against those who don’t. Therefore, I think it is important for everyone to understand what AI really is and to learn how to make use of AI as a tool instead of fearing AI or thinking AI is some kind of a magical wand that can somehow solve all kinds of problems automatically. Not everyone needs to become an AI engineer, but it’s critical that everyone takes the initiative to pick up the skills to use AI tools. In the future, AI tools will become as common as using Excel or using online tools in our daily lives today to do our business. So for companies, I think the important next step is for senior management to internalise how digitalisation and AI are strategically important to them and then to start the transformation process for their companies. I think that’s the most important first step for companies to do. This transformation requires a big mindset change. A change from doing business solely through experience and intuition to one that leverages the power of data and AI. You know, as people say, AI is a foundational technology. That means it is something that transforms how businesses are done throughout the company. It cannot be viewed as something just for the IT department to worry about. The attitude cannot be, let’s provide some funding, let the technical department try out some AI projects and life goes on as usual. That definitely won’t work. Instead, work processes need to be redesigned in such a way that AI can be incorporated into all the appropriate areas within the organisation. Therefore, it has to start from the top.
Basil : Right, in any kind of change, especially at the organisational level, there will be resistance. Could you elaborate on how to overcome such roadblocks on the journey to AI readiness and adoption?
Kevin : Yes, I think the roadblock to adoption is really the resistance to change. Many companies, when you talked to them, they do recognise the need to change, but they fear the uncertainties that the change might bring. As I see it, some companies are hoping that they can somehow revamp their business or acquire new capabilities by doing things that they are already familiar with instead of embarking on things that are out of their comfort zone. So with regards to AI, I think that is due to the lack of proper understanding of what AI really is. Many view AI as something that is very technical and very complex. To some extent that might be true, but that shouldn’t be a roadblock. Let me take an example. Many businesses use machines that are very high tech and very complex too, and they probably don’t fully understand how these machines work under the hood, but that’s not a problem. What do they do? They retrain their employees to work with these machines, revamp the business processes to incorporate these high tech machines. Over time, the decision makers will also familiarise themselves. They acquire enough knowledge about these technologies to be effective. So, same thing with AI. In the beginning, it may look daunting, it may look complex, but it isn’t. It doesn’t need to be. It is nothing but a tool. Companies need to get started, start slow and learn how to make use of data and AI, and take their business to the next level. AI Singapore is here to help. We have programmes for both individuals as well as companies to help them along their digital transformation journey.
Basil : So the message is clear. Since being set up almost four years ago, AI Singapore has developed a whole suite of programmes and initiatives for both individuals and companies to integrate AI into their lives and operations. Well, thanks for sharing with us today, Kevin.
Kevin : Glad to be here again.[*] This conversation was transcribed using Speech Lab. The transcript has been edited for length and clarity.