Amit Suxena, GVP and Head of NetSuite Asia
Ask a typical AI assistant a question and it answers. Amit Suxena thinks that is already yesterday’s AI.
“You don’t need AI where I ask a question and get an answer. I think that’s already passed,” says the GVP and Head of NetSuite Asia, who oversees Southeast Asia, the Indian subcontinent and Greater China for Oracle’s cloud ERP business. “I want AI to give me suggestions before I ask.”
His example is deliberately mundane. An AI notices that a distributor’s average inventory cycle is 22 days, works out that a tweak could bring it down to 17, and tells the owner what those five days are worth in cash. The owner, happy with 22 days because customers tolerate 30, would never have thought to ask.
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That pitch, proactive and boring in the best sense, sits at the heart of how NetSuite is trying to sell AI to the region’s growing businesses. It also builds on the argument Suxena and NetSuite founder Evan Goldberg made to e27 at SuiteWorld in August: context, not automation, is the real prize.
Thailand, the surprise package
Asked which markets have surprised him, Suxena does not reach for the obvious. Singapore leads, he concedes, largely because labour is expensive and AI lets a small team do more. China has been among the fastest adopters, though he says widespread adoption there has been “up and down”.
The real surprise is Thailand. “Thailand actually stands out as a country where the founders and organisations have been ahead,” he says.
His explanation is supply chains. Thailand hosts a dense cluster of multinationals, many of them Japanese manufacturers, and the SMEs that supply them are pushed to adopt the latest tools to keep up. The country is also courting AI more deliberately, from an OpenAI-backed startup accelerator to a US$80 billion semiconductor push.
Malaysia and Indonesia, he says, still have catching up to do. Indonesia is the bigger prize: a sprawling archipelago of SMEs and mid-market firms operating under different regional rules. Vietnam, meanwhile, still leans heavily on traditional workforces to deliver output. “Big potential,” he says, diplomatically.
Fear, not cost, held SMEs back
So what has slowed the laggards? Suxena’s answer is fear of implementation more than data privacy. The small business owner’s reflex, he says, is: “I have a small business. Can I actually implement AI? It’s too complicated.”
NetSuite’s response is speed. Suxena points to its accelerated implementation programme, which he says can get a company live in a matter of weeks, along with prebuilt industry dashboards and AI that answers questions in plain language. “Suddenly the fear is taken away,” he says.
The deeper problem, he argues, is fragmentation. SMEs buy best-of-breed tools for each job: one for supply chain, another for finance, a third for CRM. Bolt a third-party AI onto that patchwork and it works blind.
He sketches a leather manufacturer shipping to a US customer who expects delivery in 18 days. An AI optimising logistics alone would rush the order. It would not know the customer pays late, or that another buyer who pays reliably deserves priority, even at an extra four per cent discount. “Everything that AI does is out of context,” he says.
It is a self-serving argument for a vendor selling an all-in-one suite. It is also one e27 keeps hearing: Southeast Asia’s SMEs have a record problem, not an AI problem, and even in Singapore, messy data keeps AI pilots stuck.
No one asks AI what business to be in
Practical AI has become every vendor’s favourite phrase, so what have customers asked for that was not practical? Suxena insists the requests have been grounded. “Nobody has asked us what business should I get into, or should I leave this business,” he says.
Instead, they ask about cash flow. One recurring question is what a new market or product line would do to the books. Another is whether a marketing agency’s sales forecast matched reality; NetSuite’s dashboards now compare the prediction with the outcome.
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Currency volatility is the region’s chronic headache. Suxena is careful not to overclaim. NetSuite is not a currency trading platform, and “it’s impossible for anyone to predict where currencies are going,” he says. “The only certainty is that the uncertainty is there to stay.”
What the software offers instead is historical correlation: what a firm bought from country A, how long it took to arrive, and how currencies moved across markets C and D. The newer twist is that the AI surfaces those patterns before anyone asks.
What ASEAN can borrow from China
Suxena, who stresses he is not a China expert, sees one transferable lesson in how Chinese firms expand. Many run a two-tier ERP model: a heavy enterprise system at headquarters, and a lighter, multi-currency, multi-jurisdiction system such as NetSuite for overseas subsidiaries.
The point, he says, is that Chinese companies were not constrained by their domestic software when they went abroad. For Southeast Asian founders eyeing regional expansion, the lesson is to pick tools for the markets you are entering, not the one you started in.
Compliance and the hallucination problem
India’s DPDP Act, Indonesia’s PDP law and China’s data export rules all restrict where business data can travel. Suxena’s answer on compliance is reassuring in tone but thin on detail. NetSuite has a product team tracking regulatory changes in each country, he says, and customers are “also expected” to check what they are using is compliant.
His stronger card is that NetSuite’s AI is built in and runs on Oracle’s own cloud infrastructure, so analysis stays inside the customer’s context rather than being handed to someone else. Founders connecting external models through NetSuite’s newer AI connectors may want a sharper answer than that, given how Singapore firms fear data sovereignty failures but remain underprepared.
On hallucinations, particularly agents that go rogue with payments, his mantra is human control. Users decide which tasks an agent can execute alone and which need a yes or no.
He offers a telling example. An AI’s idea of a “bad paying customer” may differ from the owner’s, so before automated payment reminders go out, the owner can review the list. “Being in control is the mantra,” he says. That is sensible, but it also places the burden of catching errors back on the customer.
Rivals, and the car with a free engine
NetSuite is hardly alone. Zoho, Kingdee and a crowd of regional accounting and ERP players are adding AI to cheaper suites, while SAP Business One and Microsoft Dynamics 365 Business Central chase the same mid-market. Suxena declined to discuss specific competitors.
Instead, he set out three tests. First, does the AI see the whole business or just one function? Second, does the vendor own its infrastructure as well as its software? Third, how fast can it be deployed? “You want something which works for you today,” he says, “not something which takes a year to implement.”
The infrastructure test is the shakiest. Microsoft, for one, pairs Dynamics with its own Azure cloud, so Oracle is not unique there.
On price, Suxena is emphatic that AI is not a back door to higher licence fees. Everything Goldberg announced in the keynote a day earlier, he says, is included in the existing subscription. He borrows Goldberg’s line: “When you buy a car, you don’t expect to pay separately for the engine.” NetSuite is also offering a startup version that, he says, costs nothing at the outset, betting customers will scale with it, as some have from under US$100,000 in revenue to multi-billion-dollar businesses.
The junior accountant question
Finance back-office work is a major employer in the Philippines and India. What happens to the junior accountant when AI handles reconciliation and exceptions?
Suxena reaches back to NetSuite’s early days as one of the first cloud companies, when customers feared the cloud would hamper them. Those early adopters, he says, are now far ahead and probably did not cut staff. Junior accountants, he argues, will shed repetitive data-entry work and reskill into more proactive roles.
It is the industry’s standard reassurance, and it sidesteps the harder question of who pays for that reskilling. e27 has argued that agentic AI should worry the people it replaces, and the evidence from shared-services hubs is not yet in.
How the boss uses it
Suxena’s own favourite use is telling. He asked NetSuite’s dashboard which country in his region was most productive and profitable, and where he should add headcount. The AI weighed staff numbers, sales, renewals (“extremely important” for a software company), local regulations and more.
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The answer surprised him. He would not name the country. “I would have never thought that particular country is the one where I should be investing,” he says.
What has he stopped doing? Digging through forecasts line by line. He now simply asks what the six-month forecast looks like and what risks it carries.
For Southeast Asia’s founders, that may be the most practical lesson of all: the value is less in AI that answers, and more in AI that notices what you never thought to ask, provided the data underneath is in order.
Quotes have been lightly edited for clarity and length.
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