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The need for immediate tech results often outweighs long-term stability, presenting organisations with a series of critical challenges. This is especially true in APAC markets, where businesses face intensifying competition, evolving regulations and economic volatility.
The Rackspace State of Cloud 2025 Research reveals that 98 % of APAC organisations are integrating AI into their cloud strategies to drive business outcomes. Yet, a pressing question lingers as how can they harness AI to deliver measurable value today while building resilience for the future?
Agentic AI, or autonomous AI, presents itself as a next generation approach to this challenge, combing automation with ethical oversight to enhance workflows, reduce costs and maintain trust. It offers a pathway by focusing on scalable, adaptable automation. For example, businesses in retail can use AI to optimise inventory management through real-time demand forecasting, reducing overstock and waste. Meanwhile, the same AI systems, when designed with future-readiness in mind, can seamlessly adapt to shifting consumer behaviours, economic conditions or regulatory changes.
As digital transformation is increasingly prevalent for Australian businesses, integrating Agentic AI technologies to improve workflows whilst also while building trust and collaboration is essential. This approach creates a partnership between AI and humans, working collaboratively to improve workflows and achieve lasting. Central to this evolution is Machine Learning Operations( MLOps) as the backbone of Agentic AI. MLOps streamlines the deployment and lifecycle management of AI models, ensuring they stay aligned with evolving market needs while improving agility and scalability. Without this foundational framework, the ability of Agentic AI to deliver sustainable outcomes is significantly reduced.
AI adoption is surging across industries. According to the World AI Spending Guide, investment in AI across the APAC region is projected to hit US $ 78.4 billion by 2027 – growing at a compound annual growth rate of 25.5 % from 2022 to 2027.
For CIOs, this surge in adoption highlights the need for AI systems that deliver not only short-term results but also sustainable, long-term value. Industries like retail, finance and manufacturing are experiencing the impact, where operational efficiency and the
ability to adapt quickly to change often determine success. As these sectors navigate rising pressures to innovate, the dual goals of immediate impact and lasting growth become essential benchmarks for effective AI implementation.
However, to achieve this balance CIO’ s must embed ethical practices into their AI strategies. By prioritising transparency trustworthiness and inclusivity, organisations can ensure that immediate wins do not come at the expense of long-term resilience.
One of the key challenges CIOs face is integrating AI systems that deliver immediate operational improvements without sacrificing future flexibility. To achieve this, organisations must embed ethical guardrails into their AI strategies from the outset. Ethical AI ensures that decisions made by these systems remain unbiased, explainable, and aligned with organisational values. For instance, transparent
Adhil Badat, Chief Operating Officer, APJ, Rackspace Technology
One of the key challenges CIOs face is integrating AI systems that deliver immediate operational improvements without sacrificing future flexibility.
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