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AI’s next horizon is closer than you think. As we move rapidly into a new era of intelligence, directors need to ask, is your board investing early enough to remain competitive and are your governance systems fit for the future? And are you ready for an AI-human hybrid workforce?
To understand where we’re headed next, you only need to look where the money is being invested. Of the $5.1b raised by Australian startups last year, $3.1b went to those with AI in their product offerings and investors ranked AI the most exciting sector for the third year in a row, according to Cut Through Venture research.
The future of work is fast becoming less about human output and more about AI integration.
AI is expected to have a multi-trillion-dollar global economic impact, with a recent estimate from IDC placing its cumulative potential at US$20 trillion by 2030. Companies across the globe are investing heavily – a report from Boston Consulting Group indicates one in three companies planned to allocate more than US$25m to AI in 2025.
With the future of AI predicted to be even more transformative, the question for boards is no longer whether the technology will matter, but whether organisations are investing early enough to remain competitive and how governance can keep pace with the remarkable innovation.
“Boards shouldn’t just govern for what AI is doing today,” says Des Viranna, advisory and AI head at data and analytics consulting firm Altis. “They need frameworks that won’t become outdated, and the smarter governance approach is to track how fast that gap is closing and build frameworks that can flex as it does.”
Beyond the hype
Investment in AI has surged in the past three years, fuelled by breakthroughs in generative models and a race to build the infrastructure that powers them. Technology giants like Microsoft, Amazon and Alphabet are committing tens of billions of dollars annually to AI models, cloud infrastructure and specialised chips.
Venture capital is following a similar trajectory, with AI firms accounting for 61 per cent of global VC investment in 2025 (OECD). This is more than double the share in 2022, reflecting the growing maturity of AI-enabled products and services as well as investor confidence in its transformative potential.
In Australia, the latest State of Australian Startup Funding Report, from research firm Cut Through Venture and venture capital investors Folklore Ventures, shows that AI dominated investments in 2025.
“AI is best understood as a progression of software development,” says Alister Coleman, managing partner and founder at Folklore Ventures. “The difference now is the speed of change – how quickly software can be deployed, solve problems and reshape workflows. That’s the exciting thing. This rate of development is having a compounding effect. Engineers are building on top of previous improvements and now the curve is going vertical. It’s changing not just workflows, but how decisions are made inside businesses.”
Investment is shifting from experimentation to operational AI embedded at the core of organisational systems, with capital flowing to key areas like foundation models trained on vast data sets to generate text, images and video, or to analyse data. Investment in domain-specific models is also accelerating as businesses shift from general-purpose models to specialised solutions in industries like healthcare and finance. Last year, VC investment in AI companies focused on healthcare, drugs and biotechnology reached US$20b.
AI’s increasing demand for computing power is also seeing a boom in related infrastructure. The global data centre market size is projected to grow from US$269b in 2025 to US$699b by 2034. Amazon has announced plans to invest $20b to expand its Australian data centre infrastructure through to 2029, while Microsoft intends to invest $5b to expand its data centre portfolio in the country.
While AI copilots embedded into everyday productivity tools continue to attract investment, greater attention is turning to AI agents, or agentic AI – a new breed of semi- or fully autonomous AI systems. The deal count for AI agent startups increased by more than 81 per cent over the past year, attracting over US$8b in investment.
Elea Wurth, Deloitte lead partner for Trustworthy AI, Australia and Asia Pacific, says agentic AI is “scaling broader and higher every day”.
“We’ve moved from traditional machine learning, which required constant human prompting, to generative AI and now to agentic systems that can integrate with software, systems and processes in increasingly complex chains of action,” she says. “As you link agents together into multi-agent ecosystems, you get increasing levels of complexity and autonomy across broader environments.”
The new agentic workforce
Research from Deloitte shows 74 per cent of companies worldwide plan to deploy agentic AI within two years, which shifts AI from simply providing insights to breaking down complex tasks, interacting with software tools and achieving specific goals with minimal human oversight.
In the banking and financial services space, companies such as JPMorgan Chase are exploring the use of AI agents to detect fraud, provide customised financial advice and automate loan approvals and compliance processes. This year, retail giant Bunnings launched Buddy, Australia’s first AI-powered agentic shopping assistant, which can guide customers through projects, answer complex questions and help them find what they need.
This evolution of AI effectively creates a new category of autonomous digital workers, raising new governance and control challenges. Deloitte’s research shows that only 21 per cent of Australian companies have advanced agent governance models.
“Every employee now effectively has access to one or more PhD-level resources in their pocket, working 24/7,” says Coleman. “This expands the workforce dramatically, but it raises questions about responsibility, oversight and guardrails. In traditional environments, you knew who made a mistake. With AI, accountability becomes less clear.”
What is becoming clearer, is the impact of AI on workforce design.
“We’re already seeing engineering teams shrink in some large companies,” says Coleman. “The irony is that the people building these systems are also contributing to the automation of their own roles. This will extend across customer service, sales, product development and financial analysis.”
AI gets physical
While agentic AI presents a significant shift in capability, Wurth says developments in physical AI present the next phase.
An intelligence layer that combines sensing, decision models, simulation‑trained behaviours and adaptive control, physical AI allows machines and physical systems to perceive their environment and act autonomously. Almost 60 per cent of companies worldwide are already using it to some extent and adoption is projected to reach 80 per cent within the next two years.
While manufacturing, logistics and defence lead the way globally, Deloitte’s research shows markets in Asia Pacific are spearheading adoption, driving widespread integration of robotics, autonomous vehicles and drones. “Looking to 2030, the real frontier is bringing AI from the digital into the physical world,” says Wurth. “That includes robotics, but also our built environments, like homes, factories and cities. It’s about how the physical world becomes enabled by AI, with greater levels of autonomy in real-world environments.”
The ROI of AI
The AI horizon to 2030 presents many pressing questions for boards. Among them is AI’s return on investment. AI usage is scaling, but ROI remains elusive with results of the 2026 Global CEO Survey showing only 12 per cent of CEOs think AI has delivered both cost and revenue benefits. However, the survey also reveals that organisations with strong AI foundations – such as Responsible AI frameworks and technology environments that enable enterprise-wide integration – are three times more likely to report meaningful financial returns.
“It comes back to clearly establishing ROI metrics at the outset,” says Wurth. “What we often see is AI implementation without the right-sized measurement programs in place from day one. You might be getting productivity uplift and efficiency gains, but if you can’t measure and demonstrate those outcomes, then you can’t prove success. There is still a way to go in benefit planning, value mapping and measurement before we get clear demonstrations of AI’s impact. True transformation at scale is still maturing, but even less mature is our ability to measure the benefits and outcomes.”
Kai Riemer, Professor of Information Technology and Organisation at the University of Sydney Business School, a facilitator for the AI Fluency for Directors Sprint course, and director of Sydney Executive Plus, describes AI as a “general-purpose technology”.
“It doesn’t come with an instruction manual telling you exactly what it’s for, and that’s why it’s difficult to determine ROI,” he says. “It functions more like infrastructure. You bring it in, and then you have to figure out how it fits into your workflows. That’s an iterative process that leads to work redesign and changes in how teams operate. In the short term, productivity might even go backwards as people learn how to use it, but once it’s embedded properly, you can see significant gains at the team or process level.”
AI capability is becoming a core strategic asset across all industries, but Viranna says investment and deployment must be pinned to organisational strategy.
“You need to come back to first principles,” he says. “What is your strategy? Where do you create value for your customers? What makes you unique? Is that under threat? How does it need to evolve given these new tools?
“Organisations that look back with confidence in 2030 won’t just be the fastest movers,” adds Viranna.
“They’ll be the ones that made deliberate choices about where AI matters in their business and built towards that with discipline.”
This article first appeared as 'The future of work is not human' in the June/July 2026 Issue of Company Director Magazine.
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