We’re at a pivotal moment as agentic AI — autonomous AI agents that can act, decide, and drive business outcomes without constant human intervention — are poised to transform business operations.
Agentic AI presents a significant opportunity. Salesforce estimates that the digital labour market could reach as much as US$6 trillion. In Singapore alone, AI adoption could unlock up to SG$198.3 billion in economic benefits by 2030.
Yet despite 84% of CIOs globally believing that AI will be as transformative as the internet, only 11% have fully implemented it — a stark reminder of the complexity holding businesses back.
As AI start-ups and solutions flood the market with flashy demos, CIOs are under pressure to separate hype from impact. The focus must shift to AI implementations that deliver measurable gains in quality and productivity.
Overcoming integration challenges and other complexities is essential for CIOs to turn AI into a true success. CIOs should anchor their strategy around five core pillars:
1. Develop a strategic and integrated AI approach
Rather than pursuing isolated AI projects, CIOs should adopt a pattern-centric strategy — identifying common processes and patterns across the organisation for scalable optimisation and higher ROI.
It’s crucial to treat AI as an integrated layer of intelligence, not just a niche tool. This requires cultivating a culture of experimentation from the top down to foster broad acceptance. A unified approach to building and deploying agents can help streamline operations, improve security, and manage costs.
2. Establish a data foundation
An AI agent’s effectiveness is directly tied to the data it can access. Every AI transformation begins with preparing the underlying technology. Organisations need a system that connects business data and metadata, providing agents with the necessary context to act.
Data standardisation is essential. According to MuleSoft’s 2025 Connectivity Benchmark Report, 93% of APAC IT leaders say data silos are creating challenges in their organisations — particularly among those already deploying AI agents. CIOs should lead initiatives to ensure data is clean, consistent, and readily accessible. Breaking down silos and modernising infrastructure can also help unlock insights from archived data through stronger data governance and integration.
3. Ensure responsible and trustworthy AI
In regulated industries such as finance, healthcare, and government, CIOs face added pressure to ensure responsible AI use and meet strict compliance requirements. Building trust in the technology is essential — according to a Salesforce survey, 52% of CIOs globally cite a lack of trusted data as a top concern when implementing AI.
This trust is built on transparency (seeing what the agent did), explainability (understanding why it did it), and control (knowing what to do next). According to Salesforce’s State of AI Connected Customer research, 76% of consumers in Singapore want to know if they are interacting with an AI agent, 60% are more likely to use one if its logic is clearly explained, and another 60% if there is a clear escalation path to a human.
For CIOs, this underscores the need to embed transparency and accountability into every AI agent touchpoint. Done right, trust becomes a competitive advantage — not just a compliance checkbox.
4. Align AI with business goals and demonstrate value
Technical expertise alone is not enough; CIOs must align AI initiatives with broader business goals. They should clearly articulate how AI drives growth, enhances efficiency, and improves the experience for both customers and employees.
By focusing on tangible outcomes, CIOs can position AI as a strategic asset rather than a novelty. Communicating the purpose and benefits of digital labour transparently is crucial, highlighting how automation reduces repetitive tasks and improves employee satisfaction.
5. Manage the human element of AI adoption
AI isn’t just a technological shift; it’s a cultural one. CIOs also play the role of chief education officers, proactively addressing resistance and fostering innovation. Natural concerns about job displacement and workflow disruption must be addressed by explaining how AI augments human capabilities, freeing employees for higher-value, creative, and strategic work. Identifying internal change agents can further drive adoption from the ground up.
Continuous reskilling and upskilling should be part of the workforce strategy — building AI literacy while reinforcing essential human skills such as adaptability, collaboration, and emotional intelligence. Setting measurable goals for reskilling underscores its importance.
To accelerate adoption, spotlight internal wins, such as improved first-call resolution. Use gamification, recognition, and incentives to motivate teams to embrace their digital coworkers.
Embracing AI-human collaboration
As industries continue to prioritise trusted, inclusive, and impactful AI, CIOs remain central to this next phase of digital transformation.
To unlock the full potential and ROI of agentic AI, CIOs must adopt a strategic, holistic, and human-centric approach. By aligning AI with enterprise data and automation strategies, and focusing on AI–human collaboration, CIOs can manage complexity, enable innovation, and drive long-term productivity gains.
