SINGAPORE: Many Singapore employees and businesses are still trying to work out what to do with AI– and what AI will do to us. So when the conversation starts turning to quantum computin g and the next generation of technological capabilities, it can feel overwhelming.

In our conversations with SGTech members, AI adoption has already outpaced organisational readiness. Employees are independently experimenting with AI, but companies are struggling with structured, organisation-wide adoption, and decision uncertainty with many tools out there.

Helping businesses and workers adopt AI remains an urgent priority. The gains are already tangible, from strengthening fraud detection in financial institutions to automating tasks for small and medium-sized enterprises with little manpower to spare.

Singapore’s economic success has always depended on doing both things well at the same time: Adopting technologies with immediate, practical value, and investing in those that could shape our competitiveness a decade or more from now.

This is the central thrust of the Economic Strategy Review (ESR), which calls on Singapore to deepen leadership in areas where we already have advantages while continuing to make bold investments in emerging fields that can drive the next phase of growth. Singapore’s challenge is not deciding between one or the other.

It is ensuring we are prepared for both. WAITING FOR TECH TO MATURE IS NOT AN OPTION That technologies such as quantum computing have yet to reach widespread commercial use is precisely why Singapore needs to start thinking of them now.

semiconductor industry biomedical sciences sector and fintech ecosystem did not emerge overnight. Each was built through long-term investments made before commercial outcomes were certain.

Take semiconductors. In 1968, National Semiconductor established Singapore’s first semiconductor manufacturing facility, at a time when Singapore was still building its industrial base. The following year, Texas Instruments opened its first plant here.

The early focus was on building manufacturing capabilities, infrastructure and a skilled workforce, rather than waiting for a fully developed local semiconductor ecosystem to appear first. Now, the country has an ecosystem spanning much of the semiconductor value chain, and continues to attract new investments as demand grows for chips. The same approach is needed today.

New technologies could eventually address problems beyond the reach of even the most powerful classical computers – or create new problems. Some implications already require action today and preparation cannot wait for the technology to mature.

Cybersecurity provides a clear example. Organisations that manage sensitive data with long life cycles must prepare for a future in which quantum computers may be capable of breaking some current encryption standards Organisations have to start transitioning to cryptography designed to withstand those future attacks. It becomes part of long-term risk management, not a distant research exercise.

NOT A CHOICE BETWEEN AI OR QUANTUM It helps if we do not mistake AI and quantum technology as separate tracks. Their greatest value is likely to come from how they complement each other.

AI excels at recognising patterns, processing large volumes of data and generating insights. Quantum computing, if it achieves its potential, could dramatically accelerate certain forms of optimisation and simulation.

For example, global supply chains are getting more complex as tariffs and emphasis on economic security reshape trade. As that complexity grows for our maritime and logistics sector, so will the need for technology that can analyse vast operational data sets, and even solve optimisation problems like the routes goods take, the way cargo space is allocated and when ships are scheduled in port.

This puts a premium on professionals with interdisciplinary expertise and those who can bridge deep technical knowledge with industry application.

Today, much attention is rightly focused on helping workers become more confident and effective users of AI. Digital literacy, prompt engineering, data interpretation and AI governance will become valuable across almost every profession, but so is knowing how to apply it with purpose and discernment.

Software engineers should have exposure to quantum software frameworks. Cybersecurity professionals should understand post-quantum cryptography. Business leaders should understand where these technologies might create commercial value.

Skills development cannot be treated as a one-time intervention, but a continuous process that evolves alongside technology itself.

WHAT PREPARING FOR THE NEXT WAVE REQUIRES Singapore must prepare for the next – and the next – wave of technology. But that does not mean every business needs to start investing in quantum computing while it is still figuring out AI. If there is an ecosystem, companies will not need to build every capability on its own.

Building one requires contributions from industry, government, academia and investors to tackle different parts of the puzzles based on their strengths. Government agencies play an important role in developing national capabilities and creating platforms for experimentation. Research institutions contribute scientific expertise and breakthrough discoveries.

More resourced or innovative businesses can provide real-world use cases. Investors can help scale promising innovations. Trade associations can help bridge the gaps.

Such an ecosystem makes sense given what businesses tell us they need: Not another standalone AI tool, but clearer pathways from experimentation to implementation, trusted recommendations, practical resources and access to partners that can help them solve specific business problems.

That ecosystem must also extend beyond our shores. International collaboration can help Singapore remain connected to leading-edge developments while providing local companies with access to larger markets and talent.

The ESR's call to build global leadership in areas of strength while taking bold bets on emerging technologies reflects the strategic instinct that has served Singapore well for decades. In the next era of innovation, that means being early to build the capabilities, standards and trust that allow new technologies to be used safely and at scale.

Gavin Chua is Chairman of SGTech. Gunasekharan Chellappan is former Chairman of SGTech’s AI, Cloud and Data Chapter.