Opening Address by SMS Tan Kiat How at Tech Talent AssemBly (TTAB) Appreciation Night on 26 Aug 2026

Good evening. It is a real pleasure to be able to join you this evening.

It is a very important milestone year for TTAB - the 10th year of founding TTAB. In the last decade, TTAB has grown from strength to strength and created many more communities in Singapore. You can see many more partners in the room. So please give yourself a round of applause.

Firstly, let me thank all of you here today for what you have contributed to Singapore's tech community in both your personal and professional capacities. You are representing organisations and many of you dedicate personal time and effort to the important work that TTAB is doing.

I would like to thank all of you for your dedication and contribution to Singapore's tech community.

I am very happy that we are having an appreciation night for all of you today and it is very well deserved. But it comes at a time when many in our community are asking difficult questions about the future.

AI is changing technology work quickly - software engineering, data analysis, cybersecurity, product development, and many more. The pace can feel relentless.

Many in our industry are asking: Will my skills still be relevant?

Employers are asking: How do I harness AI fast enough to remain competitive - without leaving my people behind?

These are real concerns. We hear them in the community, work places, and increasingly in schools from young people before they graduate.

I can relate to some of that uncertainty. I started my own career in technology shortly after the dot-com bubble burst. It was not exactly the most reassuring time to enter the sector.

All of us here in the technology space know that every generation of technology professionals has lived through different sets of disruption.

But AI is moving unusually quickly. And none of us can predict exactly how every role will change.

So rather than trying to predict which jobs will disappear, I think there is a more useful question to ask ourselves: As AI changes what we can do, what will make each of us more valuable?

AI is already making some things easier. It can write code. Generate prototypes. Analyse data. Move us from an idea to something that works much faster.

But fast is not the same as good. And a prototype is not the same as a production system. A system still has to be secure. Reliable. Integrated into real workflows. Able to handle exceptions. And accountable when something goes wrong.

That is why strong technical foundations do not become less important in the AI era. They become more important. Software engineering. Systems design. Cybersecurity. Data architecture. These foundations allow us to understand what AI produces, test it, challenge it, and turn it into dependable systems.

But technical depth alone will not be enough.

Recently, I met employers, deans of computing schools from our institutes of higher learning and policymakers to discuss how technology careers are changing.

One observation stayed with me. Many young people today are already comfortable with AI. Increasingly, AI fluency will become a hygiene factor.

The differentiator is how you apply it. Do you understand the business? The customer? The industry?

Can you identify the problem that actually matters? Can you exercise judgement when AI gets it wrong? Can you turn technology into something people will trust and use?

We have also heard that one gap among younger talent is often not their unfamiliarity with AI. They lack something. That is domain experience. That distinction matters.

The future tech professional will not simply be a person who knows the latest model. It will be someone who combines technical depth, AI fluency, domain knowledge, and human judgement. That combination will remain valuable even as technology changes.

There is another reason I remain optimistic about technology careers. Technology is no longer simply an industry. It is a capability that every industry needs.

Healthcare needs technology professionals. So does manufacturing. Financial services. Transport. Government.

Almost every organisation is asking how AI will change the way it operates. So, the opportunities for tech professionals are becoming broader too.

In one recent discussion, an employer told me that they were about hiring "builders" even in functions such as HR - people who can bring technology into domains that were not traditionally considered technology roles.

I think that is an important signal. So, your career does not have to be defined by whether you work in a technology company.

Increasingly, your value will come from the problems you can solve with technology, wherever those problems are found.

But opportunities do not automatically become careers. We also need clearer career pathways. Better internships and apprenticeships. And stronger signals about where employers are hiring and what skills they value.

That brings me to what I hope we can do together.

So, I have three asks tonight. First, to our tech professionals: keep building your craft. Use AI. Experiment with it. Learn what to delegate to it - and how to validate what comes back.

But do not outsource your fundamentals to AI. Keep learning how systems work. Keep building your judgement. And get closer to real problems.

Understand your customer. Understand the business. Understand the domain. Because as AI makes some forms of technical execution easier, your value must increasingly come from what you can do beyond execution.

So, my challenge to our tech professionals is simple: Do not just become better at using AI. Become better at using AI to solve problems that matter.

Second, to employers: redesign work with your people in mind. Do not simply bolt AI onto today's processes. And do not treat workforce development as an afterthought, or something that happens after the technology has been deployed.

Bring your people - your colleagues, staff, employees - into the redesign. Ask what AI should take on. What should remain human. How roles can become more valuable. And how junior professionals will develop the experience and judgement that senior professionals have today.

I would like to place extra emphasis on this last question as it deserves more attention. AI can make work more efficient. But expertise and judgement are built through practice. Judgement comes from making decisions, encountering exceptions, getting things wrong, and learning why.

So, there may be moments when the right approach is not simply human in the loop. But what I call AI in the loop.

We should decide deliberately when AI should assist - and when people need to learn by doing for themselves.

Efficiency matters. But if optimise for efficiency entirely, you are not optimising the building of expertise, experience, and judgement in our people. And those are two different equations to optimise.

Sometimes, not all frictions are meaningless and wasteful. There are some frictions that are required for formative training experience for our people, so we need judgement to decide.

We should not optimise today's work so aggressively that we stop developing the tomorrow's experts. Automate tasks, but do not automate the learning.

So, my ask to employers is: Use AI to raise productivity. But redesign work in a way that raises the value of your people too.

Third, to TTAB and your partners: turn uncertainty into action.

This is where TTAB can play an important role. Not simply by bringing the community together. But by helping people navigate what is changing.

Share what is working. Surface emerging roles and skills. Connect professionals with employers. Create opportunities to gain real experience - not simply another credential. And help companies, especially SMEs, learn from those that are further ahead.

I commend TTAB and its partners on the Tech Start-up Community Playbook that we launched last year, with an AI companion to be released in September.

This offers a practical resource for start-ups and employers to build resilient teams while navigating an increasingly AI-driven business environment.

That is why the partnerships being formalised tonight matter. The MOUs being signed today with AI Singapore, NUS SCALE, SBACC and *SCAPE Singapore, together with the establishment of the TTAB AI Council, create an opportunity to turn conversations about AI into practical value for your members.

So, I encourage TTAB to use these partnerships boldly. Bring employers and professionals together around real problems. Create opportunities to experiment. Show people where jobs and new roles are emerging. Help companies understand how to adopt AI responsibly. And help professionals understand what they need to learn next.

Singapore has an advantage here. We are small and connected. Employers, educators, industry associations and Government can respond quickly when skills and jobs change.

Look around the room. We have representatives from different domains and sectors. And our DNA is to work together towards a common cause.

But that advantage only matters if we act on it.

Let me conclude. AI will continue to improve. Some tasks will become easier. Some roles will change. New ones will emerge. There will be uncertainty.

Our goal cannot be to preserve every job exactly as it exists today. It must be to help our people remain relevant - and become more valuable, not less - as technology changes.

For tech professionals: Deepen your craft. Get closer to real problems.

For employers: Redesign work with your people, not around them.

For TTAB: Help this community see change early, learn quickly and act together.

If we do these things well, the future of tech work in Singapore need not be a story of people struggling to keep up with AI.

It will be a story of people using AI to solve harder problems. To do more meaningful work. And to create opportunities that did not exist before.

AI will change what machines can do. Our task is to make sure our people continue to matter more.

Thank you.