Opinion

The latest controversy around defense AI is less about science fiction-style autonomy and more about process. Data quality, workflow design, and meaningful human review are becoming the real fault lines in military AI governance.

Agentic AI is reshaping how organizations think, operate, and serve. The challenge is sustained execution at scale.

Business continuity planning in the AI era needs a wider lens. It should identify where AI is operationally critical, reduce concentration risk across cloud and data environments, test for integrity failures as well as outages, assume faster attack and decision cycles, and bring leadership, legal, operations, and communications into the same response…

Ultimately, the success of agentic AI depends on access to high-quality, real-time data. Mining organisations that get it right stand to gain stronger margins, improved fuel efficiency, and safer operations. 

Real-world asset tokenization creates an unexpected tailwind for crypto infrastructure. As billions in bonds, real estate, and institutional funds migrate onto blockchain rails, the underlying settlement networks gain legitimacy and liquidity depth. Digital assets become integrated into traditional finance workflows rather than sitting in isolated silos. 

Being a remote-first startup can offer many advantages, such as a larger hiring pool, greater candidate interest, and higher retention rates. Even so, challenges can arise, requiring affected parties to think strategically and creatively to navigate them. What are some of the most common difficulties, and how can leaders solve them?

AI risk is no longer confined to cybersecurity teams. As geopolitical conflict disrupts both physical and digital systems, businesses are being pushed to treat AI exposure as part of continuity planning.

As AI becomes more deeply embedded in enterprise systems, cybersecurity is starting to look less like a separate layer of defense and more like part of the infrastructure story itself. In Southeast Asia, that shift could shape how securely and sustainably the next phase of AI growth unfolds.

Southeast Asia’s AI momentum is no longer defined by experimentation alone. As adoption moves toward scale, the region’s next phase will depend on the infrastructure beneath AI, from compute and cloud to power, connectivity, and deployment readiness.

Achieving visibility is not a one-time project but a continuous discipline. It involves aligning data sources, integrating detection tools, and adopting a mindset where infrastructure is treated as an evolving ecosystem rather than a static perimeter.