AI Video Is a Real Business Now—Lessons for Singapore

AI video has crossed a threshold: it’s no longer a novelty you laugh at for the extra fingers. It’s a product category people are paying for—at meaningful scale.

A recent case from China makes the point clearly. Kuaishou’s Kling AI (a text-to-video and image-to-video platform) reportedly hit an annualised revenue run rate of about US$240 million by December, while monthly active users jumped 110% from 3 million to 7.7 million from December to January, according to Sensor Tower figures cited in the original commentary. Paying users reportedly surged 350% month-on-month in January (per LatePost, as cited in the article). That’s not “AI hype”; that’s a business model.

For Singapore companies following the AI Business Tools Singapore series, this matters for one reason: video is the fastest path from “AI experimentation” to measurable marketing output—ads, product explainers, social clips, training videos, even customer support visuals.

What changed: “Good enough” video is now sellable

The big change isn’t perfection. It’s usability at speed. AI video tools still make mistakes, but the baseline quality has improved to the point that many clips are credible on a phone screen, in a social feed, and inside an ad unit.

That quality jump shows up in product features, not research papers. Kling’s “motion control” update—more accurate transfer of movement from a reference video into a generated clip—went viral because it helped creators produce results that feel less stiff and less “AI.”

Here’s the practical implication for businesses: the market rewards tools that remove friction from production, not tools that win benchmarks.

Why this matters for Singapore marketing teams

Singapore brands operate in a high-cost content environment—agency fees, studio time, talent, locations, and endless revisions. AI video doesn’t eliminate those costs for every campaign, but it does something valuable:

• Turns iteration into a cheap habit (multiple versions per audience segment)
• Shortens approval cycles (faster drafts, clearer storyboards)
• Makes “always-on” content realistic for SMEs

If you’re trying to do consistent TikTok/Instagram/YouTube Shorts output with a lean team, AI video is quickly becoming the tool you reach for first.

The real monetisation story: enterprise budgets, not creator tips

Kling’s traction is interesting, but its revenue mix is the real lesson. The commentary notes that professional and enterprise clients account for 70% of total revenue (as reported to the South China Morning Post).

That’s the playbook Singapore businesses should pay attention to:

Consumer virality is helpful, but B2B budgets are what keep AI tools alive.

What enterprises buy that consumers don’t

Businesses don’t pay for “cool.” They pay for predictable output and reduced risk. In AI video, that usually means:

1. Brand consistency: reusable characters, defined styles, repeatable templates
2. Workflow controls: team collaboration, project libraries, versioning
3. Usage rights clarity: commercial terms that don’t create IP surprises
4. Reliability at scale: rendering speed, queue priority, support

For Singapore SMEs, this is good news. Vendors that are serious about enterprise revenue tend to build the boring-but-critical features that make adoption easier.

A Singapore-friendly use case map (what to produce first)

Start where AI video is strongest: short, repeatable, performance-driven content. Don’t begin with your flagship brand film.

1) Performance ads for paid social

AI video works best when the objective is testing and learning.

• Produce 10–30 variants of a concept (hooks, offers, CTAs, backgrounds)
• Run A/B tests by audience segment (e.g., new parents vs. working professionals)
• Keep the winners and scale; discard the rest

This is especially relevant for Singapore’s competitive ad markets, where incremental creative improvements can reduce CPA meaningfully.

2) Product explainers for e-commerce and B2B

If your product has steps—setup, before/after, key benefits—AI video can create simple demos fast.

A practical pattern I’ve found works:

• Use real product photos or packshots
• Generate motion scenes around them
• Add human review at the end for factual accuracy

3) Seasonal campaigns without seasonal production stress

We’re in February 2026 and many teams are already planning for major retail beats (Ramadan/Hari Raya promotions, mid-year sales, year-end gifting). AI video can reduce the “content panic” that hits a few weeks before launch.

Coca-Cola has already run AI-generated holiday ads multiple years in a row (noted in the original article). The public debate can be loud, but marketers keep doing it because the economics work.

4) Internal enablement: training and SOP visuals

Not every AI video investment needs to be public-facing.

• New staff onboarding
• Retail scripts and roleplay scenarios
• Short SOP videos for operations

Internal video often has clearer ROI because you can tie it to reduced training time and fewer errors.

What can go wrong (and how to avoid it)

AI video’s biggest risk is also its biggest selling point: it’s convincing quickly. That creates operational, legal, and reputational risk—especially in Singapore, where trust and compliance matter.

Deepfakes and impersonation: treat as a brand safety issue

If a tool can generate a believable clip of a public figure dancing (an example described in the commentary), it can also generate believable clips of your executives, your staff, or your customers.

Company policy should be explicit:

• No real-person likeness generation without documented permission
• No using competitor logos/mascots or “lookalike” characters
• Mandatory review for any video featuring humans, voices, or testimonials

Copyright and IP: don’t build your campaign on borrowed characters

The commentary notes seeing familiar IP (e.g., Barbie, Pikachu) remixed in app feeds. That’s a reminder that what is technically possible isn’t necessarily commercially safe.

For Singapore businesses, the safest route is:

• Use owned brand assets
• Use properly licensed stock
• Create original characters (and document their creation)

Cost reality: inference isn’t free

Even with revenue growth, Kuaishou reportedly raised funds (including bonds) to support AI investment. That aligns with what we see across the market: running video models is expensive.

For adopters, this means:

• Expect usage-based pricing to tighten over time
• Budget for “render overruns” during experimentation
• Measure cost per usable asset, not cost per render

A simple evaluation checklist for AI video tools (SME-ready)

Pick tools based on workflow fit, not leaderboard rankings. Benchmarks are interesting; your production pipeline is what determines ROI.

Use this checklist when assessing AI video platforms as part of your AI business tools stack:

1. Output control: Can you keep characters consistent across scenes?
2. Motion control: Can you guide movement using reference video or poses?
3. Commercial usage rights: Are the terms clear for paid ads?
4. Team features: Can multiple people manage assets and approvals?
5. Speed and stability: How long does a typical render take at your settings?
6. Safety features: Watermarking, moderation, and restrictions for misuse
7. Data handling: What happens to uploaded images/videos? Any opt-out?

If a vendor can’t answer (3) and (7) clearly, don’t use it for client work.

The bigger trend: the “killer AI app” might be video

A lot of attention is still locked on foundation models and chat interfaces. The China AI video story is a useful correction: people pay for outcomes, not model architecture.

Video tools produce visible outcomes quickly:

• A clip you can run as an ad
• A product demo you can publish today
• A storyboard that reduces agency rounds

That’s why AI video is turning into a revenue engine—and why Singapore marketing teams should treat it as a near-term capability, not a future experiment.

Where to start this month (a practical 14-day plan)

If you want traction without chaos, here’s a workable rollout plan for a small Singapore team:

1. Days 1–3: Pick one channel + one KPI
   Example: Instagram Reels, optimise for CTR or CPA.

2. Days 4–7: Build a “prompt + assets” kit
   10 hooks, 5 offers, brand colours, product shots, do/don’t rules.

3. Days 8–10: Generate 20 variations
   Keep clips short (5–8 seconds), and change one variable at a time.

4. Days 11–14: Launch tests + document learnings
   Track cost per usable asset and performance per concept.

By day 14, you’ll know whether AI video belongs in your ongoing marketing workflow.

Most companies get this wrong by aiming for the perfect “AI film.” Start with repeatable performance content. Earn the right to go bigger.

If AI video is now a real business in China, the real question for Singapore is simpler: which local brands will build the operational muscle to use it responsibly—and profitably—before it becomes table stakes?

Source referenced: https://www.channelnewsasia.com/commentary/china-ai-videos-kuaishou-bytedance-profit-5906516