Generative AI will be a key driver of future business transformation, says ET CIO

As we celebrate National Technology Day, now is a great time to think about the impact technology has on business and its continued evolution. From data analytics to AI/ML to generative AI, technological advances have revolutionized the way businesses operate, opening up new avenues for innovation and growth.

“AI goes beyond basic automation and insight. It can extract insights from vast amounts of data and optimize decision-making processes. It could have a profound impact on how businesses interact and how they deliver products and experiences. Subha Tatavarti, Chief Technology Officer, Wipro

In today’s digital environment, staying current with new technologies and trends is critical for organizations to stay ahead of the curve and stay competitive. The convergence of these technologies will make the use of artificial intelligence mainstream in business, and AI’s potential to revolutionize industries and drive growth is unmatched.Subha Tatavarti, Chief Technology Officer, Wipro Limited

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Generative AI as a business enabler

Generative AI could be further refined and seamlessly integrated with existing applications. This has led to the development of numerous productivity tools designed to enhance business operations.

“Generative AI offers a niche use case of content generation for marketing, enhancing the customer experience with more human and personalized conversations. We can transform your ratings and revolutionize your customer experience.” Pankaj Gupta, CTO, Bharti AXA Life.

AI brings value, but it is increasingly important that AI-powered systems benefit society and operate on principles that avoid issues of bias, fairness, transparency and explainability. increase.Pankaj Gupta, CTO, Bharti AXA Life

Here are some of the ways generative AI can revolutionize your business.

• personalization: Through generative AI, businesses can tailor their products and services to meet the individual requirements of their customers. This increases customer satisfaction and loyalty, which in turn increases sales and revenue.

• automation: Generative AI can automate a variety of tasks such as speech and image recognition, text generation, and video creation. This reduces employee workload, increases productivity, and reduces costs.

• Product development: Generative AI helps companies create new products and services by generating virtual models, testing and refining designs, and predicting how products will perform in the market.

• decision making: Generative AI evaluates a wide range of data and provides insights that support informed decision making. This enables businesses to improve efficiency, reduce costs, and make better decisions.

• creative application: Generative AI can be used for creative purposes such as generating art and music. This unlocks new possibilities for innovation and imaginative expression.

Companies can abuse AI to artificially create preference biases for their products and services, thereby undermining the laws and practices of free markets and independent customer choice. Senior corporate executives can also misuse employee data internally to harass mid-level and junior staff and employees. There are even fears that large tech companies will collude with those in power to help them monitor and monitor people, thereby perpetuating control and authority in the hands of a few power elites.Dr. Karan Thakur, Sustainability and ESG Group Leader and Vice President of Public Relations, Apollo Hospital Group

“Generative AI has the ability to generate vast amounts of data that can identify and understand customer preferences, habits, and demands that turn out to be beyond human perception and comprehension. , helps greatly in driving marketing and sales, helps companies make perfect and accurate forecasts, helps them make well-informed business decisions, and helps companies make perfect and accurate It helps us make better predictions and helps us make better-informed business decisions.” Dr. Karan Thakur, Group Leader of Sustainability and ESG and Vice President of Public Relations, Apollo Hospital Group.

“Images and text were one of the early applications of generative AI. What happened with ChatGPT was that text generation was the main attraction. Marketing materials, news articles, ad copy, press releases, technical manuals. , the use cases for coding have increased significantly.ChatGPT has literally exploded to the point where it can generate almost any kind of text.These LLMs (Large-Scale Language Models) have a wide range of applications. It’s very spacious,” he explains. Brian Burke, Vice President, Research, Gartner.

Generative AI is set to revolutionize the way end-customers interact with products and services, delivering more personalized and dynamic experiences and content. This transformation will be further enhanced by the integration of generative AI and intelligent automation, resulting in enterprise automation platforms becoming the core of enterprise management.

Gartner predicts that 50% less code will be generated by human developers due to a much higher reliance on generative AI.Brian Burke, Vice President of Research, Gartner.

There are some interesting predictions made by Gartner in this regard.

Ethics and Privacy Issues

As the use of generative AI grows, companies will face significant productivity benefits as well as challenges. One of the big challenges is the growing dominance of data in the generative AI arena. This creates a need for companies to manage potential risks and recruit talent with generative AI expertise.

“There are some surface-level issues inherent in the technology itself, but the honest answer is that, like all technological advances, the full extent of future implications is still unknown. Tens of thousands of organizations adopting generative AI capabilities to empower their employees at work, serve their customers through better support interfaces, and provide new depth to their services. We’ve made the game richer by giving NPCs (Non-Player Characters) rich roles.” Nadel Henein, VP Analyst Gartner.

The European Union has long insisted that publicly available data is not freely available and that user consent is required if the data deviates from the original purpose for which it was collected. .Nader Henein, Vice President Analyst, Gartner

There are two main areas of concern when it comes to data and privacy in generative AI, as Henein points out.

• training data: When using generative models, data is often collected from across the Internet, much of which can be personal in nature. Although this data is publicly available, users typically share it for specific purposes, such as making connections or finding job opportunities, rather than for training models.

• prompt data: Another concern is the data generated when the user interacts with the model through chat or photo upload. This data is often used to further train the model and is not considered private. A recent announcement by Open AI aims to give users more control over the data they share with their models, highlighting the importance of transparency and user consent in the use of generative AI.

“AI has the potential to provide convenience, accessibility, automation, and efficiency if the facts are accurately understood and used wisely, all of which have a direct bearing on increased productivity and a better user experience. Ensuring accuracy is critical in the early stages of implementation.” CoinSwitch co-founder and CTO Govind Soni said:

Establishing and continually improving an ethical technology framework is critical to ensuring a moral relationship between technology and its users. Implementing appropriate data protection measures and compliance procedures can help prevent data-related challenges and inappropriate use. Organizations should also include a training and education framework to keep users safe and up to date. These efforts can be implemented through strong public-private partnerships.Govind Soni, CoinSwitch Co-Founder and CTO

Note: This article is part of ETCIO’s exclusive National Technology Day coverage.

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