I am unapologetically pro-AI and pro-automation. Not because they’re buzzwords, but because I’ve lived what they unlock. With the right systems and AI twins in place, I run multiple ventures lean, move faster than bigger teams, and focus my energy where it matters most: Growth.

But there’s a caveat. Automation is leverage — it multiplies what you already have. Multiply zero by anything and you still get zero. Multiply revenue and relationships, and you get scale. The art is knowing what to automate now, what to automate later, and what to keep human.

Adoption is here, but the gap is widening

Globally, AI has crossed the tipping point: 78 per cent of organisations now use it in at least one business function (McKinsey, 2025). This isn’t trial and error anymore — it’s mainstream.

Singapore tells an interesting story. Larger enterprises report 44 per cent AI adoption, while SMEs lag at just 4.2 per cent. The top SME reason for holding back? “No need at current scale.” It’s not resistance; it’s timing. When workflows aren’t yet repeatable, automation feels like over-engineering.

Yet leaders are bullish: 87 per cent of Singapore’s C-suite executives rank generative AI among their top three business priorities. And workers see what’s coming — 64 per cent expect their tasks to be automated or augmented within five years. The message is clear: AI isn’t optional, but its adoption curve isn’t even. Some founders will surge ahead; others will wait too long.

Automate → augment → amplify

Here’s how I think about building AI-first companies:

• Automate survival work: Repetitive, rule-based tasks like lead capture, confirmations, and basic reporting.
• Augment decisions: Train an AI twin to mirror your tone and SOPs, helping with briefs, prioritisation, and routing.
• Amplify the human layer: Reinvest saved time into sales, partnerships, creativity — the things that compound.

This order matters. In one large-scale experiment, giving workers AI assistance raised productivity by ~15 per cent on average, especially for junior staff. But those gains showed up only where structured workflows existed. AI multiplies workflows, not chaos.

Also Read: Policy warning: Without intervention, AI could deepen the digital divide

The revenue-first lens

Here’s my rule: Revenue drives the system, not the other way around.

• If you have customers and repetitive tasks → automate.
• If you have no inflow → focus on outreach first.
• If you’re caught in between → experiment manually, then scale what sticks.

I’ve seen founders proudly demo elaborate automations — while struggling to land their first ten paying clients. That’s a distraction. On the other hand, I’ve also seen lean teams using AI twins to triple their qualified outreach without hiring headcount. That’s leverage.

In my own community, I sometimes challenge students: “How many customers do you have?” When the answer is zero, automating a half-imagined platform isn’t a strategy — it’s procrastination.

Outreach before optimisation

Your first stack should bias toward bringing in revenue. A simple CRM, WhatsApp or email sequences, a booking tool, and analytics are often enough. AI twins and agents shine once the volume builds — when you’re drowning in DMs, juggling multiple funnels, or qualifying leads at scale.

That’s when automation saves you hours and stops revenue from slipping through the cracks.

For lean founders, tools like Sintra’s “AI employees” make the twin concept tangible. You can spin up an AI helper for support, email, or analytics in minutes. But they only deliver when connected to real, active workflows. Otherwise, you’re just paying for idle software.

Guardrails for smart adoption

Being pro-AI doesn’t mean automating everything blindly. Some tasks require nuance and should stay human.

For example, I sometimes use my AI twin, Seraphina, to help me draft a sensitive reply. But I wouldn’t fully automate that exchange. Contrast that with hundreds of social comments or event DMs — there, automation plus AI makes perfect sense.

The rule is simple: Automate where scale creates friction, keep it human where nuance drives trust.

Also Read: AI-powered marketing: How to generate leads, nurture customers, and close deals on autopilot

Why this matters now

Singapore’s digital economy already contributes nearly 18 per cent of GDP, and infrastructure is scaling fast. Keppel, for instance, is more than doubling its data-centre capacity to handle the AI workloads of tomorrow. Similar investments are happening across Asia and beyond.

This isn’t just infrastructure; it’s a signal. The cost of not using AI will soon outweigh the cost of adopting it.

That’s why events like Flux Series 2025 are so important. The conversation has shifted. It’s no longer “should we use AI?” but “how do we redesign our companies around it?” My view is simple: The winners will be those who treat AI twins and agents not as add-ons, but as the foundation of how lean teams operate.

Closing thought

I believe in AI because it has given me back time for relationships, creativity, and growth. It extends me, not replaces me.

For founders, the lesson is clear:

• Automate with purpose.
• Augment with AI twins.
• Amplify the human edge.

Automation is not about doing less. It’s about doing more of what matters. And the sooner we embrace that mindset, the sooner we build companies that are not just bigger, but smarter.

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