The Hype of GenAI and the Criticality of Data Protection for Businesses

By: Pradeep Yadlapati, Senior Vice President, India Country Head & APAC SBU Head, Innova  Solutions

Generative AI upholds immense potential to transform diverse industry verticals. With its ability to produce content, design products, and improve customer experiences, GenAI is poised to revolutionise how businesses function. However, as with any emerging technology, there are inherent risks and intricacies that businesses must comprehensively analyse to unlock the full potential of GenAI.

GenAI’s integration into varied use cases brings both promise and apprehension. While it offers efficiency, concerns about data leaks and security vulnerabilities rise significantly.  A recent study by BCG highlighted that among global executives over 50 percent expressed reluctance towards GenAI adoption. Some of their major concerns were compromised privacy of personal data, higher vulnerabilities of hacking, biases in decision-making, and increased carbon footprints, etc. Interestingly, these concerns might also explain the silence amongst ChatGPT users at work where nearly 70 percent have not disclosed their usage to employers as found in another survey. 

The vulnerability to major breaches arises when individuals overlook data sensitivity. In 2023, more than one-third of the global ChatGPT users were between the age group of 25-35. It includes corporate entrants and mid-level managers who are mostly aligned for tactical responsibility, potentially overlooking the sensitivity of crucial data, and seeking swift outputs from GenAI tools like ChatGPT. By estimate, this age group also contributes to 35 percent of the working population in India. This is where establishing a robust enterprise privacy and data protection policy becomes imperative. To address this, enterprises must prioritise implementing policies and frameworks regulating prompts, integrating anomaly-free models from public domains, and upholding confidentiality, essential for a secure environment.

The ethical and responsible utilisation of GenAI technology requires a detailed understanding of its probable drawbacks, including bias and ethical challenges. This comprehension enables the formulation of strategic mitigation plans and guardrails to effectively tackle these concerns. For example, the technology’s remarkable capability to generate authentic-looking content, including images, videos, and audio, elevates the potential for Deepfakes, which are manipulative media created to deceive viewers. This underlines the imperative need for extensive monitoring and regulation of GenAI to mitigate its negative impact on enterprises and our society at large. 

Effectively mitigating risks tied to GenAI demands a comprehensive strategy, involving various facets such as robust data protection strategies like anonymisation, differential privacy, and watermarking. Implementing robust data encryption methods across different stages (In-Motion, At-Rest, In-Process, In-Memory) is crucial. Compliance with data protection regulations like GDPR and the practice of anonymising or pseudonymising data to shield individual identities are imperative. Establishing a mechanism to measure the performance and accuracy of GenAI systems is equally essential in ensuring accountability and reliability within this innovative landscape. When adopting best practices, enterprises should consider some of these aspects:

Creating ethical AI committees and framework: The aim of setting up ethical AI committees and frameworks is to ensure that AI is used responsibly. These committees oversee the development and application of AI, involving teams from different fields to handle ethical issues. These committees should regularly monitor AI systems for performance, bias, and ethical considerations. Conducting periodic audits to ensure ongoing compliance and ethical standards. 

Regulatory and compliance body: Businesses across various global regions including India, are navigating established GenAI Regulations. For instance, India implemented the Digital Personal Data Protection (DPDP) Act in August 2023, outlining rules for managing consumer data. Simultaneously, the Artificial Intelligence and Data Act emphasises the need for accountability mechanisms within businesses. Being on top of these regulations helps us adjust and make changes early on to keep up with the laws.

Creating awareness within organisation 

The most effective strategy for mitigating vulnerability involves raising awareness among users. Educating users on using appropriate prompts when interacting with GenAI systems is crucial. Additionally, individuals implementing these systems within organisations must thoroughly document and communicate how AI algorithms reach decisions, providing understandable justifications for their outcomes.

An important point to consider here is that navigating the regulatory frameworks and ethical considerations when using GenAI can be daunting for businesses. The intricacies of adhering to evolving data privacy laws and moral guidelines demand businesses to consistently adapt to ensure the responsible use of GenAI. However, these challenges also offer opportunities for businesses to exhibit their dedication to ethical practices, which can nurture trust among clients and other stakeholders. Moreover, strengthening customer trust is a critical challenge for businesses utilising GenAI, especially considering concerns encompassing Deepfakes and data privacy. Contrarily, this also presents a unique prospect for decision-makers to prioritise transparency, data security, and emphasise open communication to build customer trust. This, in turn, can lead to enhanced customer retention and brand loyalty.

Conclusion 

Furthermore, embracing an ethical framework is pivotal for using GenAI ethically. In this regard, developing transparent, accountable guidelines that support privacy is crucial.

By meticulously assessing the benefits and risks of GenAI and implementing comprehensive protection measures, businesses can maximise its potential while minimising potential harm, driving innovation and growth.