Company: ARBB
Filing Date: 2025-10-31
Form Type: 20-F
Source: 0001213900-25-104705
Chunk: 16

Company: ARB IOT Group Ltd
Filing Date: 2025-10-31
Form: 20-F
Item: Item 3
Chunk 16
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, change orders, or cancellations. Regional logistics, permitting, and regulatory requirements may slow deployments.
Fulfilling large-scale orders can also strain working capital due to inventory purchases, capacity expansion, and milestone-based billing,
and adverse customer credit or payment term extensions could negatively affect liquidity.

Our AI Data Centre
Experimental Laboratory and broader AI offerings may not achieve their research or commercialization objectives and may increase compliance,
cybersecurity, and intellectual property risks.

The AI Data Centre Experimental
Lab established with academic and commercial partners may not produce commercially viable technologies, datasets, or reference deployments
on the anticipated schedule or at all, and may require ongoing investment in infrastructure, energy, and specialized personnel. Collaboration
arrangements can involve complex governance, restrictions on publication and data use, and uncertainties over intellectual property ownership
and licensing, any of which could limit productization. As we scale AI solutions, we face heightened obligations related to data protection,
cybersecurity, and emerging AI governance frameworks; security incidents, misuse of data, biased or non-representative datasets, or noncompliance
with evolving standards could result in service interruptions, legal liability, regulatory inquiries, and reputational harm. Loss of or
restrictions under third-party licenses, reference designs, or partner support could also impair our ability to assemble, localize, or
maintain AI servers and applications.

Our AI-driven smart
farming, robotics, and drone systems may not deliver expected results and are subject to agronomic, safety, regulatory, and product liability
risks.

Orders to deploy our
AI smart IoT palm farming system across plantations in Sabah, Malaysia, and the introduction of AI-powered fertilizer robots and AI-enabled
drone mapping systems depend on reliable connectivity, sensor accuracy, device uptime, and effective analytics under real-world field
conditions. External factors - including weather variability, soil conditions, pest and disease pressure, terrain, labor practices,
and adherence to operating procedures - may prevent these solutions from achieving targeted yield improvements, loss reductions, or
cost savings, which could reduce expected recurring revenues. Autonomous ground equipment and unmanned aerial systems are subject to permitting,
pilot qualifications, airspace and pesticide application regulations, and environmental constraints; failures, accidents, or noncompliance
could result in deployment delays, enforcement actions, or product liability claims. Changes in government policies, incentives, or regional
conditions in Sabah and Sarawak may further affect adoption, increase costs, or diminish anticipated benefits.

If demand for our services and solutions
does not develop as expected