There’s nothing futuristic about AI now. Instead, it has become a fundamental element of both daily life and commercial processes. According to a Boston Consulting Group (BCG) analysis, India leads the way in AI adoption, with 30% of enterprises utilising AI compared to a global average of 26%. Regardless of industry, artificial intelligence is revolutionising the way business is done in India today.
Yet, this very speedy technological innovation brings with it a complex matter of regulatory compliance. Governments and regulatory authorities across the globe, including in our country, are making efforts to create systems that would guarantee AI is created and used ethically, responsibly, and securely. Advances in AI mean that companies have to navigate a complex maze of compliance issues involving data privacy, transparency of choice, avoiding bias, and accountability. The question is how to unlock the promise of AI without violating laws or norms hence, regulatory compliance becomes a priority.
AI increasing efficiency and compliance
The largest advantage AI enjoys when dealing with huge volumes of data is how efficiently and accurately it can carry out operations, freeing the company’s time while reducing errors caused by human interference. In many aspects, companies employ AI-powered solutions to automate streamlining of operations and compliance:
- Financial services – AI-based fraud detection systems monitor transactions in real time to detect unusual activities, allowing financial institutions to comply with anti-money laundering (AML) and Know Your Customer (KYC) regulations. AI is employed by several financial institutions to assess creditworthiness, which helps enhance financial inclusion in India.
- Pharma – In 2023, the Indian artificial intelligence (AI) healthcare market size was around $374.7 million, while estimates predicted a huge rise to about $6.9 billion by 2032. Medical diagnostics, drug discovery, and patient management through AI applications are transforming healthcare. However, stringent compliance with data protection laws such as India’s Digital Personal Data Protection Act must be ensured in order to secure patient privacy and avoid misuse of medical records.
- E-commerce – AI is used by online retailers to offer customised shopping experiences, avert fraud, and streamline supply chains. Such websites, however, must comply with consumer protection laws and uphold fair trade practices and consumer privacy.
- Automotive and manufacturing – AI-based automation of manufacturing lines increases efficiency but needs to be compliant with labour laws and safety regulations to protect workers and ensure the ethical use of AI for manufacturing.
Navigating through regulatory frameworks
Many governments, including India’s, are taking proactive steps to address AI regulation. The Reserve Bank of India (RBI) and other regulators have issued guidelines for the use of AI in financial services, with a focus on fairness, transparency, and data protection. Likewise, the Ministry of Electronics and Information Technology (MeitY) is developing AI governance policies to encourage ethical deployment of AI across industries. Some of the considerations of these policies are:
- Data protection and privacy – AI systems are data-dependent, and privacy protection is therefore a priority.
- Eliminating biases – AI systems may pick up bias from training data, resulting in discriminatory or unfair outcomes. Laws need to make sure AI systems are checked for bias and adhere to anti-discrimination legislation.
- Transparency – Black-box AI models, where decisions are made without explicit explanations, are a challenge in regulated sectors. Laws must make it compulsory for AI systems to provide explanations for their decisions, especially in sectors like healthcare, finance, and criminal justice.
- Accountability – When an AI system makes a mistake, a question arises of who is responsible? Better liability frameworks are required to assign accountability in AI processes.
The explainability and transparency challenge
One of the biggest issues for regulators and firms is the explainability of AI decisions. AI programs, especially those based on deep learning, are “black boxes,” and they make decisions through reasoning that isn’t transparent to users. That may be good enough for common uses such as movie recommendations, but it’s not good enough in high-stakes areas like finance, health care, or criminal justice.
In order to respond to this concern, the vast majority of regulation demands the deployment of explainable AI (XAI), meaning that AI models provide results which are understandable and explainable. If a computer program rejects an application for a loan, the client should understand why. When an autonomous vehicle gets into an accident, those responsible for investigation must be aware of what has happened. Explainability is currently legally demanded by most jurisdictions, and companies ought to deploy AI models which fulfill such transparency expectations.
Conclusion
AI impacts all manner of businesses in India, including NBFCs and online marketplaces. The intersection of AI and regulation is a matter that concerns businesses, governments, and the public. The more that businesses and daily life rely on AI, the more imperative it becomes to have rigorous, adaptable, and enforceable regulation.
In the context of India, the test is a dual one: spurring AI-created innovation while making sure that measures of regulation secure citizens’ rights and prevent misuse. By prioritising data privacy, transparency, minimising bias, and accountability, India can establish a regulatory climate to foster responsible AI uptake. As the CEO of Nvidia, Jensen Huang, has stated: “Regulate AI use, not the technology.”
