Summary Bullets:
• At this year’s AWS Summit in Sydney, AI has moved further along from conversation around large language models (LLMs) to practical AI examples driven by agentic AI.
• AI adoption is now across start-ups, SaaS companies, service providers, and enterprises with modern tech stacks.
It is no surprise that at the AWS Summit Sydney 2025, AI is still front and center. What is different from a year ago however, is the shift in conversation from LLMs and what they can potentially achieve to more practical AI including agentic AI and how they are now being deployed across different scenarios. While AI companies continue to formulate new models and enhance their accuracy and capability, there are now more ways enterprises can extract the value from AI models for different use cases. When posed a question how enterprises should go about selecting the right AI model, an AI advisory firm explained aptly that it should depend on the problem AI is meant to solve, and the level of IQ you need for that purpose. A less sophisticated, but more economical AI model, should suffice if the purpose does not require extensive reasoning or an LLM that is capable of performing a wide range of tasks.
From the technology point of view, the landscape is becoming more mature as more options such as small language models, drag-and-drop agent builder, and solutions that enable enterprises to put in place guardrails and to control/monitor their AI projects. The industry is also moving towards more collaboration and open standards to accelerate adoption. AWS Bedrock for example, offers a broad range of fully managed models including its own Nova models as well as those from AI21 labs, Anthropic, Cohere, DeepSeek, Luma, Meta, Mistral AI, Poolside, Stability AI, TwelveLabs, and Writer. The model context protocol (MCP), an open standard developed by Anthropic to enable secure connections between AI systems and data sources is also gaining traction.
From the enterprise perspectives, the adoption of AI is also underway and particularly in a few areas. Firstly, many start-ups are developing disruptive businesses leveraging AI. According to AWS, 81% of start-ups in Australia are leveraging AI in their business, with 42% developing new AI-driven products and services. These are often businesses built on innovation, without the baggage of legacy systems and likely born in the cloud. The second group of companies are the SaaS providers who see the need to build AI capabilities, especially AI agents to help customers simplify the way they interact with their software. This is crucial for gaining competitive advantages and survival. Being cloud-native, and with many skilled technologists, many SaaS companies have embedded AI into their products. Thirdly, many system integrators are leveraging AI to streamline their processes and deliver better outcomes for enterprise customers. This is also necessary to stay competitive since the industry is moving from labor arbitrage to AI-enabled service management to lower operational costs. They have been quick to scale up their AI expertise internally to leverage the technology for internal productivity, embedding AI into existing platforms, and engage enterprises in AI-powered projects.
Finally, the broader enterprise landscape is more mixed even though most companies are curious about what they can achieve with AI. However, those who have gone through digital transformation and modernization of their IT will tend to be more ready to put AI into production. The financial services sector in Australia has long been early adopters of emerging technologies to transform their businesses. Based on Celent’s research, Australian banks are projected to allocate 56% of IT spending to fuel transformation efforts, topping the regional ranks. During the AWS event, ANZ bank discussed their program to launch a multi-agent chatbot ‘amie’. CommBank has also completed migrating its data platform to AWS, paving the way for integrating AI across its operations. This was accelerated through its partner HCLTech.
AWS announced its AI Spring Australia program at the event in Sydney which can further accelerate the adoption AI. The program will support start-ups (AWS Generative AI Accelerator) and enterprises (AWS AI Launchpad) to move the GenAI workloads more rapidly from concept to production through its expertise, partner support, and dedicated funding. Ultimately, enterprises have to recognize that in driving operational changes with AI, there will need to be cultural change. It is also crucial for stakeholders from different lines of business to work with IT to ensure buy-in and collaboration. Users of AI need to appreciate the benefits of the technology and have a say in how AI will assist them to be more productive. An effective engagement process will also alleviate fear related to job security and drive the workforce in embracing AI.