Adopting Trustworthy AI and Governance for business success amidst the AI hype

Twenty years ago, could anyone have predicted that we would be relying on artificial intelligence (AI) to make critical business decisions and address complex challenges? What once seemed like the premise of a science fiction film is rapidly becoming reality. Today, businesses are approaching a point where AI systems are capable of making decisions with minimal or even no human intervention.  

To operate effectively in this new model, organisations must focus on building trust with AI. This doesn’t mean trusting the machine in the conventional sense; it’s about building trust-worthy practices around teams and systems we adopt to enable successful outcomes with these technologies.  

Globally, we’ve seen clear evidence of what happens when that trust is broken. From investigations into AI bias in recruitment and home loan processes, to discriminatory outcomes in financial services and workplace tools, the message is clear: When AI is implemented without ethical guardrails, the risks are real, and the consequences are human. These cases reiterate the need for AI governance to be embedded into AI investments, ensuring AI’s acceleration of innovation is met with the assurance of trust and efficacy.    

Balancing Innovation with Accountability  

While mitigating AI bias should continue to be a pivotal business focus, building true enterprise value will remain at the forefront of AI investment strategies. Generating value from AI agents hinges on building collaborative, intelligence-amplifying systems that work in tandem with humans. Trust and governance embedded in AI mitigate the risks and business concerns associated with AI investments, while generating value in terms of accuracy and performance.   

In a SAS-commissioned IDC survey conducted in Q3 of 2024, Data and AI Pulse: Asia Pacific 2024, we identified the top concerns of businesses regarding their AI investments, which included protecting against liability concerns, ethical violations related to bias and discrimination, and regulatory non-compliance risks. While these are supported by trustworthy AI processes, a lack of visibility into AI governance puts the trust, compliance, and success of their AI investments at significant risk.    

We found that the organisations making the most progress in their AI journeys share a common belief: that AI privacy, governance, and ethical policy controls are not optional – they are foundational. By embedding governance into every phase of the AI lifecycle, organisations can innovate faster, with the confidence that they’re not just moving quickly, but moving responsibly to address risks related to bias, fairness and regulatory compliance.   

Embedding Ethics into the DNA of AI  

Data is at the heart of this transformation. It powers the insights that shape strategy, optimise operations, and uncover new opportunities. But it also amplifies risk. That’s why ethical clarity around data usage isn’t just a technical issue; it’s a cultural one. Ethical AI and data embedded into business fosters trust amongst your teams, the boardroom, your customers, and your business partners. It doesn’t just help avoid harm and risk, strong ethical foundations generate the potential to grow trust and breed greater confidence in your business, demonstrating your leadership in ethical AI in every context.   

Given that AI is a powerful new tool that augments human teams, achieving trust is precisely a question of giving our people clarity and confidence in the answers AI provides. This makes Explainable AI crucial for attaining the transparency we need. To achieve reliable human oversight and bias mitigation, our AI systems must report on how and why it arrives at the outputs it offers our teams.   

Mapping the Path to AI Governance  

Understanding the challenges businesses face, we launched the AI Governance Map, a comprehensive resource that supports organisations in navigating their AI governance journeys with confidence. Beginning with an online assessment, organisations are offered a tailored view of their current AI governance maturity. From there, it outlines next steps, providing clear and actionable insights for progressing responsibly and with purpose.   

This is part of a growing portfolio of offerings from SAS, with tools that help organisations build AI governance into every stage of their operations, from data stewardship to model monitoring and compliance oversight. Because AI governance is more than risk mitigation—it’s a strategic lever for responsible, scalable innovation.  

The ethical norms are still changing, as are compliance laws throughout Australia and New Zealand. Trust and governance are not fixed targets, but by building responsible AI platforms, a business can adapt quickly as requirements change. With the right AI architecture in place, you can be confident that your approach to trusted AI is both aligned with your values today and adaptable to meet the requirements of tomorrow.   

Because in the race to innovate, it’s those who lead responsibly who will steer the way.