Machine Learning is getting more and more prevalent in many industries. But with all the excitement (and also anxiety) about AI replacing our jobs, is our current knowledge in this field sufficient enough to digitalise our industries?

Before we get ahead ourselves, we talk to Theng Hui, the Head of Artificial Intelligence in PLUS Malaysia, as we understand how Machine Learning has become a key component in the company, and learn tips and insights as to how you too, can incorporate it into your business seamlessly. 

  • Data is key. 

In order to build AI models, data is very crucial. Without the basis of data collected and analysed, there is no chance of building an AI platform. 

Just like all data-related projects, we also need to identify the problem statement from our stakeholders before we venture into the Machine Learning models we build. 

Only when your company has sufficient data collected, you can look into incorporating Machine Learning into your processes. 

  • Focus on Quick Wins. 

There is a term called quick wins – for management, this means its something you invest in, and you are able to get the returns very quickly; for business owners, this defines something that can solve your pain points very quickly. 

For example, for our customer service department, one of our quick wins was when we built and implemented a chatbot that can resolve customer’s non-urgent matters. This would straightaway reduce the number of calls they receive per day, which will definitely increase the efficiency of the department. 

If you are starting out on digitalising your processes with Machine Learning, focusing on quick-win projects can help you get the momentum going. 

  • Globalisation is catalysing AI growth. 

With the borderless access of the internet, we are able to gain knowledge and industry insights from just a click away. Even if we are slightly slower than in other countries, we are still able to obtain information as long as there is a hunger for knowledge. 

So if you are looking to explore AI or Machine Learning in your business, there is no excuses in regards to the lack of information. Everything is very accessible now, and as long as you have some basic technical background, or if you have a data science team, you are definitely able to look into the use of AI in your business processes. 

  • Focus on building “Real AI” instead of “Fake AI”. 

What we define as “Fake AI” are models that are very rule-based, mostly set by If/Else statements. These models are not as comprehensive as it would be quite impossible to write out every possible If/Else Statements. 

So when building your own AI, it would be best if you invest the time and budget into building something that has a more intelligent system where it can handle exceptions in cases. 

This will ensure your machine is able to learn on its own and able to perform a more comprehensive task to help improve your processes effectively.

  • Determine the suitable phase of your business to invest in AI. 

For smaller companies, there is always 2 perspective in deciding if its time to incorporate AI in their business, one which is data-driven, and one that is business-driven. 

A data-driven decision is when you don’t really have a business problem you need to solve, but you believe from the trends or patterns from your data, you want to explore deeper insights, you can decide to look into AI. 

If you are seeing it as a business-driven decision, it would be when you have a specific business problem in which you need AI to help you solved, that is when you need to adopt AI as part of your processes. 

So there are two ways to look at it, either from the top-down approach or from the bottom-up approach; both which are good reasons to explore Machine Learning in your business.

  • Always plan a roadmap for the digital transformation. 

So for corporate companies, especially in enterprises, they have a huge user base. So when you are implementing something new, it can be quite challenging if you go in without a proper planned roadmap. 

So a roadmap can give you a step by step process, what you need to achieve first before proceeding to the next steps. 

Its important to look at the feasibility and the adaptability of your company’s employees as you plan out the roadmap. 

If your company practice agility amongst the team, it would be much easier to incorporate these initiatives as they would be more open to explore new processes.

Catch Theng Hui’s presentation in D/M Summit: Journey Towards A.I and Analytics

  • Determine the resources you need. 

If you are looking to kickstart incorporating Machine Learning in your business, another factor you need to look into is the resources you need. 

Budget aside, you will need to determine the talents you need to hire in your team. How you can determine the size of your team would depend highly on the business problem you are trying to tackle. 

It is always wise to build a game plan so you know to what scale you are planning your digitalisation, and then it would be more apparent to you as to how many people you need in your team, and the expertise needed. 

  • Invest time in your team’s adoption rate. 

When introducing digitalisation of your company’s processes, there will always be resistance, especially from your employees themselves. 

This is because they have been doing the same old processes for more than 10 years, and are already in their comfort zone. When there is a change in the process, even from manual to automation, there will be some time needed for the adoption to take place. 

Often times, the resistance is higher if your employees do not understand the digitalised solution, or how it can add value to their processes. So we need to spend more time on education, be it for the business user or the end user. 

Ultimately, we want them to understand that we are trying to help them improve the processes so that their time and effort can be spent on more higher-value tasks.


Machine Learning and AI are crucial parts in the digital transformation of businesses to create more efficient processes and automate mundane tasks to free up your employees to do higher-value tasks, which in exchange can further bring growth to your company. 

If you are someone who is looking to venture into AI applications, it is very important for you to build a strong foundation in your technical skills before going into real life applications. If you are a business owner, it takes a lot of planning and strategising before you can kick off a digitalisation initiative in your company, especially if you have a larger size business. 

Theng Hui has been working on Machine Learning for years and he has so many interesting insights to share, especially on how corporate companies optimise their business with AI. If you would like to learn more from him and other industry experts, be sure to sign up for the all-access pass and tune in to the D/M Summit with the latest official recordings now!