New Delhi, May 3 -- AI is undoubtedly shaping the trajectory of innovation across industries. No longer just a trend, it is a transformative force poised to add $450-500 billion to India's GDP by 2025. The pace of AI innovation and adoption is only accelerating as businesses strive to find new ways to harness its full potential.
As we embrace the AI-driven future, it now becomes critical for businesses to develop a sound framework that supports ethical and secure AI deployment. New data privacy and protection regulations such as the Digital Personal Data Protection Act (DPDP) are ushering in a new era of accountability for organisations in India. Given the pressure to maintain stakeholder trust, businesses need to reassess their current AI and data strategies to mitigate the potential risks of AI misuse and miscalculation. This includes implementing innovations that help refine the AI risk-benefit equation while fostering data transparency and compliance. As AI algorithms advance, fostering collaboration between governments and businesses is essential to establish and implement ethical standards along with ensuring the beneficial integration of AI.
The criticality of Safe AI
The output of AI is only as good as the quality of the input. Maintaining well-rounded data sets and ensuring that data is being aggregated from various sources into a unified reliable repository is a step in the right direction towards achieving data accuracy. Organisations need to train AI models on the intricacies of business functions to mitigate the risk of biases in AI algorithms. For example, good financial decisions hinge on unbiased algorithms that support equitable resource allocation across the organisation and prevent unintended consequences. A combination of human and machine capabilities can help create a solid foundation for robust AI ecosystems.
Ethical lapses in AI governance can undermine organisational integrity. AI models lacking robust data security measures can compromise the trust of customers. According to a recent study, the average cost of a data breach in India reached Rs.179 million in 2023, which is almost a 28% increase since 2020. A breach not only jeopardizes individual financial well-being but also erodes confidence in the industry. To mitigate these potentially harmful outcomes and better strengthen public trust in AI systems, companies must develop and implement mature AI governance frameworks.
Where are organisations today in their AI governance journey
According to the AI Asia Pacific Institute's report, a key challenge around AI implementation in Asia Pacific (APAC) revolves around a lack of trustworthy AI operationalization. AI advancements are predominantly concentrated within large corporations, reflecting a disparity in the distribution of initiatives, especially in startup communities.
Prevailing global AI frameworks prioritise a human-focused, ethical, and risk-based approach. Ethical and safe AI deployment entails algorithmic transparency, ethical review boards, a comprehensive monitoring process, and regular impact analysis. Amid this, process and task mining capabilities can provide insights around the behavior of AI systems and ensure tasks align with ethical, legal, and regulatory standards. Having greater visibility on actual processes and workflows empowers organizations to better uncover potential compliance issues and take corrective actions.
Data fundamentals such as integrity, quality, and security are a bigger concern in APAC than in any other region. This could be due to the inability of legacy systems to keep pace with the rapid rate at which enterprise data is expanding, which in turn, impacts the mainstream adoption of digital technologies. On top of talent shortage, 40% of the companies in the study do not have these basics in place.
To counter AI risks, organisations are developing strategies and technologies like bias detection tools and privacy-preserving techniques. The implementation process involves practical steps such as the adoption of ethical AI frameworks, staff training, ongoing monitoring, robust incident response plans, and partnerships with cybersecurity firms. Leveraging process- and task-mining, organisations can effectively monitor and assess their workflows to further enhance protection.
Putting the focus on the human
The right balance between innovation and ethics is key to harnessing the potential of AI. Harnessing solutions equipped with embedded guardrails and governance mechanisms help ensure the ethical and compliant use of AI models. Real-time monitoring of AI systems enables the swift detection of anomalies in AI algorithms.
As AI algorithms become more complex, many companies are realising the indispensable role of human oversight in ensuring the accuracy and ethicality of AI-generated results. A study has found that 96% of AI professionals agree on the criticality of human expertise to the success of AI data models, with 86% calling it essential. Human reviewers bring nuanced understanding, empathy, and contextual awareness that AI algorithms lack. A human-in-the-loop approach can help mitigate liability - a significant concern with the rise of Generative AI. Harnessing the potential of human-in-the-loop systems, however, entails refining the synergy between humans and software workers and optimising workflow integration.
Amid rapid digital transformation, employees face the uncertainties of new systems, altered job roles, and shifting responsibilities. Organisations need to drive employee training, establish well-defined governance structures, and implement sound change management. AI governance should encompass guidance on architecture and best practices that empower employees to leverage innovation to create new value for the business.
Ultimately, it's the people who breathe life into AI initiatives - or stop these in their tracks. Managing change holistically will enable organisations to optimise the positive impact of AI on organisational processes while ensuring that employees are able to keep pace with innovation.
Published by HT Digital Content Services with permission from TechCircle.