Emerging Tech Outlook 2025
Disclaimer
This publication is an independent project produced by researchers and the business team at the AI and Cyber Futures Institute. All opinions expressed herein are our own and do not necessarily reflect the views, policies, or positions of our employer or affiliated organisations.
Artwork
The original artwork for this publication was personally created by Ganna Pogrebna without the assistance of AI tools. The portrait art, however, was crafted by Ganna Pogrebna using a custom algorithm specifically developed for this project.
Copyright © December 2024
Researchers and the Business Team at AI and Cyber Futures Institute. All rights reserved. Sharing this publication in its entirety is encouraged. However, reproduction of this publication (or any of its parts) is not permitted without prior written permission from the authors.
Prof Ganna Pogrebna
Superpowers:
Behavioural Data Science, HumanMachine Teaming, HDI, Decision Data Science, Decision Theory
As we look ahead to 2025, the rapid evolution of emerging technologies continues to redefine how we work, live, and interact. This report highlights pivotal trends that will shape the next phase of innovation:
AI Agents: Autonomous AI-driven systems are already contributing to workflows across industries, handling tasks such as customer support, decision-making, and complex automation with unprecedented efficiency and accuracy.
Edge AI: Real-time data processing closer to its source is transforming IoT applications, enabling faster and more reliable decision-making.
Digital Twins for Business Strategy: Digital twins, enhanced with generative AI, allow businesses to simulate and optimize strategies by creating virtual replicas of processes and systems. This technology, now accessible to organizations of all sizes, enables precise decision-making and reduced risks through real-time data-driven insights.
Explainable AI (XAI): In 2025, transparency in emerging tech systems will become critical for fostering trust and mitigating biases, ensuring that these technologies can be responsibly integrated into society.
AI Ethics and Governance: Ethical considerations are paramount as AI and emerging tech adoption accelerates, necessitating robust governance frameworks for responsible development.
AI for Sustainability: Leveraging AI to tackle environmental challenges as well as to resolve how emerging tech systems themselves could be sustained in the future is key to promoting sustainable practices in agriculture, energy, and beyond.
FROM THE EDITOR
This edition of Emerging Technology Outlook 2025 provides insights into these trends and others, emphasizing their transformative potential for industries, governments, and communities.
Dr Immaculate
Motsi-Omoijiade
Superpowers:
Law of Emerging Tech,
Ethics of Emerging Tech, Responsible AI
Breaking the Hype Cycle
Artificial intelligence (AI) continues to dominate the headlines, with promises of transforming industries, solving global challenges, and reshaping how we live and work. In 2025, some industries are riding the AI wave, embracing innovations in automation, customer service, and sustainability. In areas like healthcare, finance, and logistics, AI systems are delivering tangible results streamlining processes, improving outcomes, and creating efficiencies that were unimaginable a decade ago. Yet, the excitement around AI isn't universal. In industries where ethical concerns, regulatory hurdles, and technical complexities loom large, progress is uneven. Autonomous vehicles, for example, remain stuck in the testing phase in many regions due to safety concerns. Similarly, debates around bias, transparency, and accountability are slowing adoption in sensitive areas like criminal justice. This dual narrative one of rapid adoption and another of cautious progress underscores the complex interplay between AI’s potential and its limitations
KEY TRENDS
Autonomous AI agents are evolving from promising prototypes to practical tools, capable of managing complex tasks in areas like customer service, supply chains, and operational workflows. These systems thrive in environments that demand independent decisionmaking and quick adaptability, but their rise brings questions about accountability and control. As AI systems permeate high-stakes industries like healthcare and finance, transparency is no longer optional. XAI focuses on making AI’s decision-making processes understandable to humans, ensuring trust and fairness. By demystifying complex algorithms, XAI is fostering broader acceptance of AI technologies. Responsible AI is no longer a buzzword it’s a necessity. With concerns about AI bias, discrimination, and privacy breaches, the focus is on creating systems that are equitable, accountable, and transparent. AI Ethics is the glue that holds these trends together. As AI adoption accelerates, ethical frameworks are essential to guide innovation responsibly.
RESEARCH IMPACT
AI trends are reshaping academia by driving interdisciplinary research across fields like machine learning, decision theory, and ethics. Studies on AI agents and XAI focus on improving trust, accountability, and transparency, while responsible AI and ethics emphasize societal implications, fostering collaboration between technical experts and social scientists to ensure innovation aligns with human values.
OPPORTUNITIES FOR BUSINESS AND POLICY
In 2025, AI offers businesses transformative opportunities. AI agents enhance productivity by automating tasks and enabling efficient decision-making, while Explainable AI (XAI) builds trust by making AI decisions transparent, especially in critical sectors like healthcare and finance. For policymakers, XAI (if done right) is capable of supporting fair and accountable regulations. Adopting responsible AI practices helps businesses navigate regulatory challenges, address ethical concerns, and build trust with stakeholders, positioning them as leaders in an increasingly competitive and conscious market.
Dr Fendy Santoso
Superpowers:
Robotics, Cyberphysical Systems,
Human Machine
Teaming, Cyber Security
Gen, Edge, & Autonomous Trends
The integration of generative AI and autonomous systems is set to reshape robotics and automation in 2025. These advanced models, powered by neural networks, enable robots to process natural language instructions with precision, navigate unstructured environments, and make real-time decisions. This adaptability is particularly vital in dynamic, high-stakes scenarios such as disaster response and unmanned aerial vehicles (UAVs). For example, generative AI allows robots to interpret ambiguous commands, analyze complex contexts, and execute tasks autonomously, reducing the need for constant human oversight. Enhancing this technological leap are edge computing and 5G connectivity, which together enable faster, localized data processing and decentralized decision-making. By minimizing latency and increasing data bandwidth, these innovations allow autonomous systems to operate efficiently in environments with limited access to cloud infrastructure. Whether in agriculture, aerospace, or law enforcement, this combination of technologies ensures precision, adaptability, and reliability key factors in critical operations.
RESEARCH IMPACTS
The ripple effects of these advancements extend to academia and industry. Generative AI fosters interdisciplinary research spanning AI, telecommunications, control systems, and human-robot interaction. A growing emphasis on secure data sharing is prompting the development of tailored cybersecurity solutions, while scalable machine learning models are being designed to accommodate diverse hardware, from resource-constrained devices to high-performance systems. Importantly, these technologies are also shaping ethical discourse, as researchers seek frameworks to ensure that the adaptability of autonomous systems does not compromise trust or safety. Transparency in decision-making processes is becoming a cornerstone of innovation, driving progress in testing, validation, and deployment. For UAVs, the integration of generative AI and connectivity is particularly transformative. These technologies enable UAVs to interpret mission objectives, navigate complex airspaces, and adapt to challenges like extreme weather or unexpected obstacles. Real-time sensor data processing, powered by 5G and edge computing, enhances UAV responsiveness, making them indispensable in applications like precision agriculture, infrastructure inspection, disaster response, and military operations. However, these advancements also highlight the critical need for robust cybersecurity measures to protect UAV communication and scalable AI models to support diverse and collaborative scenarios, such as UAV swarms.
OPPORTUNITIES FOR BUSINESS AND POLICY
From a commercial perspective, businesses can leverage these technologies to optimize logistics, automate remote maintenance, and improve service delivery. Governments, meanwhile, must address challenges such as data security, workforce adaptation, and equitable access to technology. International cooperation will be essential to establish global standards for the safe and interoperable deployment of autonomous systems. Ultimately, generative AI and connectivity are not just technical upgrades they are transformative forces with far-reaching implications for industries and societies. By addressing ethical, security, and scalability challenges strategically, stakeholders can harness these technologies to build a future where autonomous systems are both innovative and impactful.
Dr Jian Liu
Superpowers:
AgriTech, Environmental Data
Science, Ecology
Emerging Tech for Agriculture & Sustainability
KEY TRENDS
In 2025, agriculture is witnessing a transformative shift with the advent of digital twins and robotics. Digital twins are essential for simulating and refining agricultural strategies. Providing real-time data and predictive analytics, digital twins assist farmers in optimizing operations, ranging from crop management to equipment maintenance, substantially improving productivity and sustainability. Simultaneously, robotics is playing an increasing role in modern farming. Autonomous machinery is executing tasks like planting and harvesting with high precision, reducing labour costs and environmental impact by ensuring optimal use of resources like water and fertilizers. Together, these technologies herald a new era of efficiency and resilience in agriculture, addressing global food demands while promoting sustainable farming practices. Sustainability is becoming a cornerstone of digital agriculture as we move towards 2025. Robotics and autonomous machinery perform tasks such as planting and harvesting with high precision, ensuring optimal utilisation of resources like water and fertilizers, thereby minimizing environmental impact.
RESEARCH IMPACTS
Digital twins and robotics in agriculture have a significant influence on academic fields such as agricultural engineering, computer science, and sustainability studies. Researchers are innovating solutions that integrate these technologies to tackle agricultural challenges, fostering a multidisciplinary approach to sustainable food production and environmental conservation. These advancements are not just about increasing productivity but ensuring that farming practices are sustainable and resilient to climate change. Innovations such as soil health monitoring, climate resilience strategies, and efficient water management technologies are critical in addressing the global challenge of food security while protecting the environment. By integrating digital technologies into farming, the agricultural sector is poised to achieve a balance between meeting the rising food demands and conserving natural resources.
OPPORTUNITIES FOR BUSINESS AND POLICY
For businesses, the emergence of digital twins and robotics in agriculture presents opportunities for investment and innovation. Adopting these advancements enables stakeholders to boost productivity, reduce costs, and enhance eco-friendly practices. Integrating sustainability in digital agriculture offers avenues for eco-conscious investments and collaborations. Policymakers can utilize data-driven insights to formulate strategies that support sustainable agricultural development, enhancing food security and environmental stewardship. Embracing sustainability ensures long-term productivity and costeffectiveness while fostering a positive environmental impact.
Dr Juliette Tobias-Webb
Superpowers:
Behavioural Science, Behavioural Design
Behavioural Science and Emerging Tech
Behavioural Science & AI Integration
KEY TRENDS
The integration of behavioural science and AI in 2025 is poised to reshape multiple sectors, especially in personalization and customer experience. Behavioural AI leverages insights from behavioural science combined with the sophisticated processing power of AI to model and predict human behaviour. This enables the development of personalised interventions and experiences by analysing vast amounts of data to discern habits, preferences, and decision-making processes. In the retail and marketing arenas, companies are utilizing behavioural AI to craft personalized customer journeys and targeted campaigns that enhance user engagement and loyalty. By understanding the nuances of consumer behaviour better than ever, businesses can tailor their offerings to meet the specific needs and preferences of individual customers, thus driving higher satisfaction and retention rates.
RESEARCH IMPACT
The intersection of behavioural science and AI is creating new pathways for research in fields such as psychology, data science, and human-computer interaction. Researchers are developing AI-driven models that more accurately predict and influence human behaviour, leading to advancements in areas like consumer behaviour analysis and personalized education, fostering a deeper understanding of human-machine interactions.
OPPORTUNITIES FOR BUSINESS AND POLICY
For businesses, the convergence of behavioural science and AI opens doors to more effective marketing strategies and product enhancements. Policymakers can apply insights from behavioural AI to develop public policies that encourage sustainable consumer practices and better address societal challenges. Embracing these technologies allows organizations to stand out in a competitive market while aligning their practices with human-centric values.
Sasha
Sarago
Superpowers:
First Nations Innovation, Creativity, Digital Fashion, Inclusive Emerging Tech
Inclusive Emerging Tech in Digital Fashion
KEY TRENDS
Fast fashion’s environmental impact makes the industry the second-largest consumer of water, contributing roughly 10% of the world’s carbon emissions. The global fashion industry is actively calling for innovative and sustainable business practices to be incorporated to solve this environmental crisis. Digital fashion, often touted as a trend, surpasses such status and presents a solution to achieving a circular economy our Australian and global fashion industries seek to achieve. In addition to global societies embracing new and emerging technologies, digital fashion plays a pivotal role in this technological future. Digital fashion’s utilisation of virtual tools such as 3D design, AI, AR, VR, naturally upskills society in preparation for Web 3.0 and the metaverse (virtual worlds where online communities and digital economies are fostered); a natural progression from the digital societies we currently operate in. But it also helps to democratise industries once inaccessible by socially impacted communities due to diversity and inclusion issues.
RESEARCH IMPACT
Digital Fashion represents a significant opportunity for economic empowerment, cultural preservation, and technological advancement for First Nations communities. Digital fashion can blend traditional Indigenous artistry with cutting-edge 3D design technologies. It can equip First Nations communities with the skills and knowledge needed to build profitable, scalable fashion and creative businesses, leveraging digital tools that bypass traditional physical barriers like capital, production, and marketing costs. Digital fashion also aligns with the goals of increasing Indigenous data sovereignty, intellectual property protection, and fostering economic empowerment through decolonial frameworks co-designed and developed by First Nations peoples.
HOT!
OPPORTUNITIES FOR BUSINESS AND POLICY
As the Australian Government works towards achieving proposed actions outlined in its First Nations Digital Inclusion plan across three key areas: access, affordability, and digital ability – the need for digital literacy is equally important. Digital fashion offers educational and career pathways for First Nations communities to build cultural and economic prosperity and a selfdetermined future regardless of geographical location. In addition to overcoming challenges experienced by the ever-growing First Nations fashion and textile industry.
Nathan Damaj
Superpowers:
Data Engineering,
Data and Emerging
Tech Systems
Architecture, Secure
Cloud Architecture
Trends in Data Engineering
KEY TRENDS
In data engineering, the key trends are around Multi AI Agents ability to create automated workflows end to end, using Gen AI coupled with APIs and automated tasks. This trend will be heightened in 2025, based on all the players in the market. The continuing push for Gen AI, seeing which LLM produces the best results. Possibly we will see the stagnation of LLM performance or not? And instead see proprietors leaning on Agents. LangGraph , N8N and Microsoft Copilot AI Agents are examples of the offerings. Gen AI Multimodal models now encroaching into video generation, will also challenge the tools labels of being discovery generators not content creators.
RESEARCH IMPACTS
This will further the chasm between AI practitioners and advocates vs non advocates. Gen AI models are opaque at this stage when you add layers of workflow logic (agents); competing different tasks with different biases and assumptions. Making it harder to govern, understand and monitor; as a human in the loop scenario may not be possible. Another concern is the impact this technology is and will continue to have on our education system. What are the jobs of the future? If so, what are the academic fields that are important and hence what research areas? These tools will also create possible challenges in cyber space, as the requests become more sophisticated and self-learning, while being continues in its seamless actions and reactions.
OPPORTUNITIES FOR BUSINESS AND POLICY
For business and policy, the emergence of multi-AI systems presents both an opportunity and a challenge. Organizations must embrace these tools to enhance productivity while safeguarding against biases and governance failures. This creates an opening for businesses to develop ethical workflows and monitoring solutions. Institutes like ours can play a crucial role by creating products that integrate local communities into the AI ecosystem, ensuring inclusivity and fairness. Moreover, understanding people and systems will remain central to delivering impactful solutions, even as the underlying technologies and platforms evolve. This focus can drive both regional development and global relevance.
Dr Mohammad Ali Moni
Superpowers: Digital Health, AI and Digital Health technology
Emerging Tech In Health
As we move into 2025, AI and digital health technologies are driving a paradigm shift in precision medicine, delivering individualised care tailored to patients' unique genetic, environmental, behavioural and lifestyle profiles. These innovations are reshaping healthcare with transformative impacts on diagnostics, treatment, and disease management, especially in the rural and remote areas.
• Advanced AI for Radiomics Integration: AI algorithms are becoming more adept at analysing vast imaging and multiomics datasets (genomics, proteomics, metabolomics) alongside clinical and realworld data. These insights enable the identification of disease biomarkers and predictive models for personalised therapies.
• Wearables and Real-Time Monitoring: Digital health devices, including advanced wearables, portable devices, and mHealth apps, provide continuous, real -time data for early disease detection and remote patient monitoring.
• AI-Driven Drug Discovery: Predictive AI models are accelerating the identification of new drug candidates, optimising drug design, and repurposing existing treatments.
• Digital Twins: Simulating patient-specific treatment outcomes through AI-driven digital twins allows clinicians to personalise care with unprecedented precision.
• Telemedicine and Blockchain Integration: AI-powered telehealth platforms and blockchain-based data-sharing systems are improving accessibility, security, and interoperability in healthcare.
RESEARCH IMPACTS
The integration of AI and digital health technologies into precision medicine will significantly impact academia by advancing interdisciplinary research and education. It will drive innovation in bioinformatics, computational biology, and multiomics, fostering collaboration between computer scientists, clinicians, and geneticists. Researchers will gain access to more comprehensive datasets and analytical tools, enabling deeper insights into complex diseases and treatment responses. Additionally, focusing on personalised care will shape academic priorities, emphasising ethical AI use, data privacy, and translational research, ultimately accelerating the practical application of discoveries to improve healthcare outcomes.
OPPORTUNITIES FOR BUSINESS AND POLICY
The adoption of AI and digital health technologies in precision medicine will transform business and policymaking by driving the development of patient-centred healthcare solutions and fostering innovation in the biotech and pharmaceutical industries. These advancements will influence policies around data sharing, interoperability, and ethical AI use, ensuring equitable access and patient privacy. Businesses will benefit from AI-driven efficiencies in drug discovery and healthcare delivery, while policymakers will focus on creating frameworks to regulate and incentivise the integration of precision medicine into healthcare systems, shaping a more effective and personalised approach to public health.
A/Prof Dr
Ivan Maksymov
Superpowers:
Physics and Machine
Learning, Physics and AI, Quantum
Physics & Emerging Tech
KEY TRENDS
AI and Machine Learning continue to rise as transformative forces in physics and related disciplines, with their influence set to grow further in 2025. A landmark event in 2024 was the award of the Nobel Prize in Physics to pioneers of neural networks, recognising their profound impact on scientific advancement. However, this decision sparked a notable divide within the physics community. Critics argued that neural networks are merely sophisticated tools rather than foundational contributions to physics, deeming the award misaligned with the discipline's traditional focus. This controversy underscores a broader tension between classical physics paradigms and the rapid integration of computational methodologies.
RESEARCH IMPACT
Despite these differing perspectives, AI applications have already revolutionised areas such as quantum computing, astrophysics and materials science, blending computational innovation with theoretical research. As the field evolves, the interplay between traditional physics and AI-driven approaches promises to redefine the boundaries of scientific discovery.
OPPORTUNITIES FOR BUSINESS AND POLICY
The rise of AI in physics positively impacts our work by supporting the integration of social aspects into AI research, such as sociophysics and quantum cognition theory. These frameworks push physics beyond its traditional boundaries, enabling us to explore human decision-making and cognitive processes using computational methods. By embracing advancements of AI, we use its methodologies to bridge physical and social sciences, enriching both fields with innovative insights.
Dr Ibrar Yaqoob
Superpowers:
Blockchain and Applications, Metaverse,
Edge-Cloud Computing, IoT and Smart Cities
Smart and Resilient Supply Chains
The metaverse is set to evolve significantly in 2025 with trends like blockchain integration, social metaverse platforms, and AI-driven solutions. Blockchain will enhance decentralization by enabling secure ownership of digital assets and transparent transactions. This will improve supply chain management by ensuring transparency and traceability of goods from production to delivery. AI will drive intelligent virtual experiences. It will personalize environments based on user behavior, which can enhance supply chain predictions and customer engagement. Digital twin technology will create virtual replicas of real-world assets. This will revolutionize industries like agriculture and improve supply chain logistics by enabling precise monitoring and simulation. The convergence of XR (Extended Reality), NFTs, and immersive education will redefine how we interact, learn, and manage resources in virtual spaces, including supply chains. Disinformation management will become increasingly important as virtual environments grow. False narratives and misleading information will increase, which can affect both users and industries.
RESEARCH IMPACT
Blockchain in the metaverse will establish secure, decentralized economies, transforming commerce and ownership. Its integration into supply chains will provide end-to-end transparency. This will allow for the traceability of products and goods. AI and generative AI will enhance user experiences by making virtual environments adaptive and intelligent. These technologies will improve demand forecasting and supply chain management. Digital twin technology will bridge the physical and virtual worlds. It will offer real-time simulations for fields such as agriculture and supply chains. This will improve crop management, resource efficiency, and inventory optimization. These trends will create new opportunities in decentralized systems, virtual collaboration, and smart decision-making. Disinformation management will play a key role. Blockchain will ensure data authenticity, while AI algorithms can detect and mitigate misinformation. This will prevent disruption in both supply chains and virtual interactions.
OPPORTUNITIES FOR BUSINESS AND POLICY
The convergence of AI, blockchain, digital twins, and the metaverse offers transformative potential for decentralized decision-making and smart systems. In agriculture, digital twins can optimize resource use and improve sustainability. They will provide real-time simulations and predictive analytics, benefiting supply chains by improving forecasting and reducing waste.
Prof Ganna Pogrebna
Superpowers: Robotics, Cyberphysical Systems, Human Machine
Teaming, Cyber Security
Strategy Twins
Strategy Twins (digital twins for business strategy) represent the application of advanced digital twin technology to business strategy. By integrating generative AI (gen AI) with digital twins, organizations can create dynamic virtual models of strategic decisions and simulate complex scenarios. This approach moves beyond traditional physical object modelling to virtual representations of processes, customer behaviour, and strategic outcomes. Organisations can now experiment with strategic changes in a risk-free virtual environment, gaining insights to optimise decisions before implementation. This technology's reduced cost and accessibility make it viable for both large corporations and SMEs, democratizing sophisticated strategic planning tools. The result is a significant shift in how businesses approach strategy design, enabling continuous iteration and improvement.
RESEARCH IMPACTS
In the academic realm, Strategy Twins provide a novel methodological tool for behavioural data science, decision theory, and strategic management research. They facilitate the empirical testing of theoretical models by simulating realworld complexities and allow for the integration of behavioural insights into decision-making frameworks. This technology promises to refine how researchers model uncertainty and organizational behaviour in strategic scenarios.
OPPORTUNITIES FOR BUSINESS AND POLICY
Strategy Twins offer transformative potential for policymaking and business practices by enabling evidencebased decision-making. Policymakers can use these tools to model the impacts of legislative changes, while businesses can simulate customer interactions, market shifts, and operational improvements. This trend enhances agility and precision in strategy formulation, allowing organizations to anticipate challenges and adapt proactively.
Sermin Yavuzer
Superpowers: Executive Education, Market Research, Partnerships
Emerging Tech Education
KEY TRENDS
AI's rapid adoption has profound implications for the workforce. While technology is projected to displace 630,000 Australian jobs by 2028, it is also expected to create a net gain of 12 million jobs globally. The Tech Council of Australia estimates that by 2030, the country will require up to 200,000 AI-related professionals, spanning both technical and managerial roles. This transition emphasises the critical role of education and training in aligning workforce skills with emerging technological needs.
IMPACTS FOR ACADEMIA
AI’s rapid adoption necessitates curriculum redesign, integrating technical AI skills with ethics and governance to meet demand for diverse roles. Lifelong learning programs, including micro-credentials and stackable degrees, will reskill professionals for AIdriven careers. Emphasis on soft skills, such as critical thinking and human-AI collaboration, will prepare students for hybrid roles. Research opportunities will expand in workforce dynamics, AI ethics, and equitable skill distribution. Academia must also address the socio-economic impacts of AI, offering strategies for inclusive skill development. These efforts will align workforce skills with technological advancements while addressing challenges of governance, transparency, and ethical AI use.
BUSINESS OPPORTUNITIES
Businesses can leverage executive education to upskill leaders for AI adoption. Custom leadership programs will focus on AI strategy, governance, and ethics. Technical courses for non-specialists will equip managers to oversee AI-driven projects. Industry-academic collaborations can co-design tailored training for specific sectors like healthcare or finance. Reskilling programs will support displaced workers, aligning with corporate social responsibility. AI governance training and workshops on human-AI collaboration will address ethical and operational challenges. Executive education also presents opportunities to enhance workforce planning and build a future-ready workforce, ensuring businesses remain competitive in an AI-driven economy. Executive education in 2025 will prioritize AI strategy for executives, ethical governance, and technical upskilling for non-technical leaders. Programs will address workforce transitions by reskilling professionals for hybrid roles combining AI knowledge and soft skills. Sector-specific courses will focus on applying AI in industries like healthcare, agriculture, and logistics. Workshops on AI-driven decision-making and human-AI collaboration will enhance productivity and innovation. Businesses need to engage in programs fostering leadership and practical AI integration to stay competitive. These areas will ensure leaders and workers are equipped to adapt to AI’s evolving role in reshaping industries and the workforce. The AI and Cyber Futures Institute (AICF) addresses these trends through its AICF Executive Toolkit, providing tailored solutions for industry alignment with technological advancements.