The past few years have been nothing short of revolutionary for AI. We have seen the rise of foundational models, an explosion of AI-first startups, and an unprecedented wave of venture capital flowing into the sector.
But as AI continues to evolve, investors must look beyond the hype to identify where the real opportunities lie.
How we got here
The AI landscape has shifted significantly over the past two years, largely due to the rise and now widespread availability of foundational models, which has shaped where we focus our investments. This has largely been driven by advances in computing power, neural network architectures, and access to massive datasets. The introduction of large language models (LLMs) and their integration into everyday workflows has fueled a surge in AI-driven products and productivity.
However, as foundational models become commoditised, differentiation now lies in leveraging domain expertise, proprietary data, and enhanced architectures to drive real impact.
In 2024, over 50% of global VC funding went into AI-focused companies. Startups in this space are reaching $100M in annual revenue within 21 months, as seen with Cursor—a fraction of the time it took traditional SaaS companies. This accelerated growth makes AI one of the most attractive sectors for investors seeking high-reward opportunities.
The challenge now is finding the companies whose growth and value proposition can stand the test of time. The fundamental requirement of all good companies remains true for AI companies—you must solve an interesting global problem and build a product customers love. It will become pivotal that all companies have a strategy for unlocking greater productivity and decision-making with AI.
Our AI opportunity
Drawing from both the market and technology changes witnessed, as well as our deep expertise gained from managing one of Australia’s largest AI portfolios, we have refined our thinking on where our most exciting AI opportunities lie. This is what we’re particularly excited about:
- Efficient AI: As the demand for AI skyrockets, so too does its energy and computing costs. We want to invest in technologies that reduce these factors, including software architecture plays (model-level) and hardware-focused innovations (chip-level).
- Agentic AI: AI is catapulting beyond simple prediction tasks to autonomous decision-making. We see AI agents as a major step toward AI systems that can execute complex workflows with minimal human intervention. This shift represents a huge opportunity to drive efficiency and unlock new applications in business productivity and industrial automation.
- Verticalised AI: We believe that the most durable AI businesses will leverage deep industry expertise and proprietary data to solve high-value problems. We are particularly interested in companies applying AI to industries that have yet to see major disruption, such as biotech, cybersecurity, industrial productivity, and healthcare.
- Physical AI: AI-powered robotics is making automation more scalable and efficient. Rather than investing in capital-intensive robotics hardware, we are focused on companies building software stacks that improve robotics programming and decision-making. Our investment in Breaker, which leverages LLMs to build intelligent robotic systems, highlights our interest in this space.
Where to from here
Looking forward, agility will be key. The AI landscape will undoubtedly continue evolving rapidly so understanding emerging trends, anticipating technological shifts, and remaining focused on companies with genuine, sustainable competitive advantages will be key.
The winners will be companies that go beyond wrapping a foundational model with a thin application layer. The future belongs to those who innovate at the intersection of AI and deep industry expertise, focusing on defensibility, efficiency, and real-world impact.
Given the rapid evolutions happening in AI, we will continue to fine-tune our thinking (just like an AI model).
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