Why Boardrooms Can’t Ignore Generative AI

Samsung later banned employees from using such AI tools. An internal memo reportedly argued that data transmitted to AI platforms such as ChatGPT and Google Bard would be stored on external servers. Therefore, it would be difficult to recover or delete the data and sensitive company information could be compromised.

The Samsung events offer a glimpse into the Pandora’s box of concerns that, if opened, could run into global enterprises as they grapple with the dizzying pace of the rise of generative AI. Since its launch five months ago, ChatGPT has amassed over 100 million users. Individuals (and even small companies) around the world are using it to do everything from writing blogs, reviews and resumes to creating short films and realistic illustrations, building software code and analyzing macroeconomic trends . All this without any human intervention.

While interest has made generative AI impossible to ignore, larger companies are probably right to proceed with caution.

Chatbots like ChatGPT are trained on billions of words from the Internet, books, and many online sources including Common Crawl and Wikipedia, which makes them more knowledgeable but not necessarily more intelligent than most humans. Bots may be able to connect the dots but not necessarily understand what they spew.

There are other concerns. The US Federal Trade Commission (FTC) has warned that a scammer could use these AI tools to clone a relative’s voice with just a short audio clip and create havoc. For example, on April 29, CNN An Arizona woman, Jennifer DeStefano, believes she was the victim of a virtual kidnapping scam in which someone cloned her daughter’s voice and demanded a ransom. Similarly, a fraudster can use these tools to impersonate a sibling and ask us for an OTP (one-time password) and withdraw money from the bank account.

Several prominent tech leaders, including Elon Musk, Yoshua Bengio and Stuart Russell, have called for a six-month moratorium on training systems that are “more powerful than GPT-4”, arguing that they should only be developed if The world believes that it can happen. There are risks. The risks are high, and it’s not just industry leaders who are sounding the alarm. No less than Geoffrey Hinton, one of the godfathers of AI, known for his work on the deep learning that powers today’s generative AI tools, recently “speaking freely about the risks of AI” Leave it to Google.

Given this clear and present threat, mid-sized and large companies, especially those in the banking, financial services and insurance (BFSI) sector and healthcare, are proceeding with extreme caution. Major financial institutions including CitiGroup, Bank of America, Deutsche Bank, Goldman Sachs, Wells Fargo, and JPMorgan Chase have already banned the use of ChatGPT by their employees amid concerns that sensitive information may be leaked when using the technology.

Speaking on the condition of anonymity, the Chief Information Officer (CIO) of a leading multinational bank in India said Peppermint: “ChatGPT clearly has potential but it is a bit early for the highly regulated BFSI sector. We deal with very sensitive customer information and cannot play with it. I’d rather wait for the technology to mature and put some guardrails around it.”

use cases emerge

Still, corporate boardrooms are abuzz with conversations around generative AI, which was discussed by 17% of CEOs in the January-March quarter of this calendar year, according to the latest release of ChatGPT and its potential use cases. The discussion inspired ‘What CEOs Talked About’, reports IoT Analytics, a Germany-based provider of market insight and strategic business intelligence.

AI and AGI (Artificial General Intelligence) were mentioned eight times in fintech company Paytm’s earnings call on May 11. Experts believe that in the not too distant future, an AGI machine will be able to understand the world as well as any human, and in many cases, even surpass human intelligence.

Microsoft, Google, International Business Machines (IBM) and Nvidia are enhancing their generative AI platforms so that companies can use them with less data and security concerns. For example, Microsoft has begun providing “the tools needed to build ChatGPT-powered applications” to enterprise users.

And OpenAI is also working on ‘ChatGPT Business’ which, it claims, “will by default not use end users’ data to train its models”. Amazon Inc. has its own generative AI platform called Bedrock, while IBM offers WatsonX and has partnered with open source generative AI company Hugging Face, whose HuggingChat competes with ChatGPT.

Skepticism about data security hasn’t stopped enterprise use cases from sprouting up. Companies such as travel and holiday fare aggregator Expedia have already started using ChatGPT to provide the best flight tickets and also help travelers plan their trips and holidays.

Shopify Magic, an AI product from e-commerce platform Shopify, is generating product descriptions from a list of keywords or product descriptors in a tone chosen by merchants, while retail giant Carrefour is creating videos answering customer questions. Has been experimenting with ChatGPT for topics such as ‘How to ‘Eat Healthy for Less’.

Generative AI also has use cases in the human resources (HR) world. Tasks such as onboarding, training, performance management and employee queries and complaints can be automated using ChatGPT. In the financial sector, AI can help with compliance, credit risk management, investment research, and legal document processing.

drama of india

In India, the Mahindra Group is exploring some use cases for its business units. “Generative AI is evolving at a rapid pace and finding the right use cases for our business is something we are very excited about. There is no FOMO (fear of missing out) and no pressure (from top management) – we are focused on finding the best use of this technology for our businesses,” said Rucha Nanavati, Chief Information Officer, Mahindra Group.

Walmart-owned Flipkart also believes that generative AI has great potential to address one of the main problems any e-commerce platform is trying to solve – connecting consumers with products that they can find. They may be interested in buying.

Jayandran Venugopal, Chief Product and Technology Officer, Flipkart said, “Gen AI allows us to create more conversational, human-like agents or assistants to handle the user through this entire search, purchase and post-purchase customer service journey. Is.” AI can help us create high-quality content (images and descriptions) for our products catalogue, and for our merchandising and advertising campaigns. This can help us summarize product descriptions and user reviews to reduce cognitive load for our customers.”

Sanjay Mohan, Group CTO of MakeMyTrip, is currently using generative AI for proof-of-concept (PoC) work. According to Mohan, Large Language Models (LLMs) are very good at summarizing things very cleverly and concisely. In case of review if someone is saying ‘excellent’ and someone is saying ‘excellent’ then it knows that both are same. So, that summary is something we can use”.

Audio platform Pocket FM uses generative AI to automate the creation of long-tail content (that uses specific keywords like ‘size 7 hiking boots for men’ instead of just ‘hiking boots’), trailers and Promo, and provides personalized recommendations by analysis. User Data, according to its co-founder and CTO Prateek Dixit. Adoption of this technology has helped Pocket FM reduce translation time by more than 40%, he added.

Haptik, a Mumbai-based startup, is using generative AI to make bot conversations less robotic and more free-flowing, according to its co-founder and CEO Akrit Vaish. With ChatGPT, Haptik also hopes to “create content and connect countless variations of bot responses”. Homegrown Zoho Corp. has also launched 13 generative AI Zoho application extensions and integrations powered by ChatGPT.

Limitations

But integrating application programming interfaces (APIs allow applications to talk to each other) with the business workflows of other units poses its own set of challenges for companies. Sumanta Kar, technology partner at consulting firm EY India, points out that once you adopt a tool like ChatGPT, you need to continuously monitor, re-train and fine-tune to ensure that the model is accurate. Keep outputting and stay on top. -to date.

According to Sanjeev Menon, co-founder and head of technology and product at E42.ai, a natural language processing-based AI platform, while ChatGPT excels at generating text and answering questions, it fails to automate complex workflows. may not be able to. enterprise environment, which explains why such models need to be fine-tuned before they can be put to use.

The reason is that enterprise data includes structured and unstructured data such as videos, audio files, social media posts, emails and more. So organizations rely on specialized tools that can interact with third parties and internal systems. Also perform specific actions based on the data collected.

“Today, there isn’t a customer meeting without a discussion on generative AI,” said Jaya Kishore Reddy, co-founder and CTO of conversational AI startup Yellow.AI. Generative AI models such as ChatGPT to business systems, which require significant customization. He added, “Even plugins (tools that help ChatGPT access up-to-date information, run computations, or use third-party services) can be integrated into different systems and multiple workflows across enterprises. need to be able to connect.”

Bharat Shankar, vice president of engineering at conversational AI company gnani.ai, stressed the importance of defining a range or scope for GPT systems in specific domains in order to make them efficient. Shankar also underlined that GPT “requires a lot of effort to integrate with enterprise backend systems such as ticketing tools, CRM (customer relationship management), etc.” He said that the companies have to ensure that there is no regulatory violation. For example, in accessing or sharing patient data, which would result in a violation of HIPAA (Health Insurance Portability and Accountability Act) in the healthcare sector. Furthermore, he pointed out that the response time of the ChatGPT bot may not work in scenarios where real-time response is required without user lag.

But then again, generative AI models are rapidly growing in power. IBM predicts that so-called ‘foundation models’ – models that are trained on a broad set of data and can be used for a variety of tasks – will soon make use of self-supervised learning. They can apply the information they learn to a specific task, dramatically accelerating AI adoption in business.

The frantic pace at which these models are training themselves, and the imminent launch of ChatGPT Business, doesn’t bode well for business executives sitting on the sidelines.

Prasid Banerjee & Abhijit Ahaskar contributed to the story