How to build AI capability locally, before it’s too late

• Commonly, Asia teams are told they must wait for centralised direction from HQ.

Yes, but waiting carries its own cost. Asian competitors are moving fast to experiment with AI.

• By the time HQ ships a solution, the use cases and tech stack may miss the mark in the local market.

What Asia CEOs are doing: Below are ways MNCs in Asia are pressing ahead while staying within company-mandated compliance and governance frameworks.

• The Asia region has a deep, technically savvy AI ecosystem. Western MNCs operating here can take advantage of the best of both worlds.

1. Build AI literacy team-wide

Several CEOs admitted they did not fully understand AI themselves. Instead, they focused on exposing teams to the technology and creating space for experimentation.

• A leading global tech firm made AI training mandatory for everyone, setting a common baseline across the company.

Three years ago, our entire company went through a global AI training — it was like a day-to-day AI course. Everyone had to do it, regardless of their position or knowledge. It was so good I wanted my kids to take it.

But most consumer and industrial firms have been slower to develop global AI training programs.

Asia CEOs know their job is to motivate their teams. But where to start?

• The Asia CEO of a food wholesaler and retailer turned to a software vendor for assistance in running an off-site AI workshop for her team.

I often joke with IT that I am a dinosaur. I know I don’t have the answers, but I wanted to inspire our team. We asked our software supplier, Microsoft, to organise a one-day workshop to show our people what is possible with AI. This spurred a lot of conversations. If we don’t have a goal, then we have to go out and find it. Too often, we are internally focused.

Workshops can be a useful way to bring functions together and cross-pollinate ideas. Silos block digital transformation; the same goes for AI.

• But a one-off event fades without reporting lines and incentives behind it. Inertia returns unless change management is deliberate.
• For the Asia CEO of a luxury brand, post-workshop leadership requires adjusting the org chart and KPIs.

I agree it is very difficult to know where to start as a CEO without a technical background. We also held a one-day workshop to motivate people to start with AI. We ensured people came from different functions. But this was just the beginning. There needs to be constant focus and revised reporting lines to keep an initiative going.

Inculcating a growth mindset is more essential than ever in these turbulent times. AI does not stand still. Neither does customer innovation.

• In many cases, AI adoption is more of a change-management and people problem than a technology one.

I encourage a growth mindset in our company. If you don’t have a growth mindset, then people close themselves off and nothing changes.

We are a very dynamic organisation. Our advantage is that we are central to our customers’ business. Either we adapt, or we’re out. We are very project-driven, always opening new locations or changing our networks. The work is constantly changing. It is not like a bank where the office is the same, and you replicate it. This has made us quite open to AI. (Logistics)

2. Create AI champions

While AI literacy matters, enterprise-wide mandates rarely inspire the passion and drive to make big changes.

• A tech CEO found it effective to start with a small AI-savvy team to develop edge cases.

About six years ago, I set up a small data team of nine people that became the genesis of our AI learning in the region. This team must work within our company’s data compliance policies, and we partner with IT for funding. But they report directly to me, not to IT. The best ideas are not always centralised; they come from the edge. It takes a flexible organisation that empowers people to be innovative.

Another firm gave AI access to its most eager volunteers first, regardless of title or seniority.

• Those volunteers are set to become AI ambassadors and change agents for their teams.

When we launched Copilot, instead of meting out licenses to leaders, we asked for AI volunteers. In my region, Asia, we had about 200 licenses for 900 people. We can see the most active users are young, move more quickly than the rest, and are highly motivated to figure things out for themselves. We asked how we can push this group further. So we decided to make the most active users AI ambassadors and leverage their passion.

3. Identify your use cases

Two themes emerged on where to start with use cases. First, target the workflows where staff spend the most time.

• The largest surface area is where AI delivers the best ROI. It may be that the most high-impact AI opportunities are hidden within processes executives thought were already automated.

Second, let the people accountable for business results drive the work.

• IT should not own AI transformations, but it can be essential in supporting them.

The Asia CEO of a hardware firm shared how they used focus groups to surface new ideas.

We start by narrowing down to one or two areas that can bring the most efficiency and used internal focus groups to get more people involved. We looked at where employees spend most of their time. Admin paperwork turned out to be massive, which was expected.

More surprising was how much time sales spent preparing quotes for customers. We had thought that was already quite automated by IT. We walked through the process and found so many steps were repeatable across customers.

The focus groups were entirely driven by frontline sales. By listening to them, we targeted the biggest time-wasters and developed better systems for sales, which ultimately led to a better experience for customers.

4. Plug into the local AI ecosystem

Increasingly, Asia’s innovation ecosystems provide expertise, partners, and funding that regional leaders can tap into independently while keeping an eye on corporate governance alignment.

AI capability does not have to come solely from inside the company.

• One Asia CEO shared their success with a ‘call for proposals’ approach.

I have found when tackling new, or especially complex problems, that organising a ‘call for ideas’ can be very helpful. There is a vibrant community working on AI-driven solutions here. You can give 30 to 90 days for pitches to be submitted and have a team, perhaps led by IT, to curate the best ones. You may not find a single, magical solution. It is more likely you will get slices of very credible options that you can fund and scale.

Government funding for AI projects is growing in select sectors.

• Another Asia CEO hopes to leverage local grants to build the case for more HQ support.

I am seeking funding from the Singapore Economic Development Board, which has numerous programs. I have found that they are quite eager to provide funding as long as you can show progress or results. With that funding, I may be able to use it to make a case with our CEO to fund a global centre of excellence in Singapore.

The upshot: The broader lesson is that AI adoption need not begin with a global mandate.

• Several Asia CEOs found that local pilots, external partnerships, and early wins were enough to build momentum—and, eventually, secure greater support from HQ.

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✅ Asia CEO Checklist: Five ways to leverage local AI resources

Many regional CEOs face the same dilemma. How to get started on AI when the direction is not yet clear.

• Asia CEOs in our discussions seek low-risk ways to build organisational confidence before making larger investments.
• Tapping external partners, research institutes, and government-backed programmes can accelerate AI adoption at low cost.
• Singapore is the example explored below, but similar ecosystems exist elsewhere in Asia. (Prompt idea: copy and paste the checklist below into your preferred chatbot, then ask for a similar list of AI resources for MNCs in the city of your choice: Hong Kong, Bangalore, etc.)
• The principle is the same: MNCs do not need to build every capability themselves.

1. Need fresh AI ideas? Check out IMDA Open Innovation Platform (OIP).

• Singapore’s national crowdsourcing platform connects companies with a network of startups, researchers, and technology firms to solve business problems.

How MNCs use it: Rather than issuing a traditional RFP, companies define an operational challenge—such as predictive maintenance, quality inspection, customer service, or inventory optimisation—and invite external AI specialists to propose solutions.

The benefit: Access a broad pool of vetted AI expertise without needing an in-house innovation team.

2. Need technical AI expertise? Check out AI Singapore (AISG).

• AI Singapore is the country’s national AI programme, connecting businesses with researchers, engineers and universities.

How MNCs use it: Partner on applied AI projects, access engineering talent, explore apprenticeship programmes or work with researchers to validate use cases before committing major investment.

The benefit: A practical way to augment internal capability when local teams lack deep AI expertise.

3. Need to pilot industrial AI? Check out the Advanced Remanufacturing and Technology Centre (ARTC).

• Operated by A*STAR, ARTC brings manufacturers, technology providers and researchers together to solve operational challenges using AI, robotics and advanced manufacturing technologies.

How MNCs use it: Participate in collaborative projects focused on computer vision, predictive maintenance, robotics and digital manufacturing.

The benefit: Test AI in realistic industrial environments before committing to large-scale implementation.

4. Need help turning an AI pilot into a business case? Check out the Enterprise Compute Initiative

• Launched in 2025, the Enterprise Compute Initiative helps eligible companies develop AI applications by providing access to cloud computing resources, technical expertise, and implementation support.

How MNCs use it: Work with approved partners to develop a proof of concept or a minimum viable product, receiving support for technical implementation and organisational change.

The benefit: Reduces both the technical and financial barriers to moving beyond experimentation.

5. Need executive support and a roadmap? Check out GenAI x Digital Leaders Programme.

• Designed for digitally mature enterprises, the programme helps organisations identify and scale high-value AI opportunities.

How MNCs use it: Regional leadership teams work with experienced implementation partners to prioritise use cases, develop an AI roadmap, and build the internal capability needed for broader transformation.

The benefit: Useful for regional headquarters looking to demonstrate measurable business value before seeking larger investment from global HQ.