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In an era when generative AI rose to prominence, speculation ran rife about employees facing potential job losses as AI emerged as a potent replacement. Notably, IBM garnered attention when it disclosed plans to employ AI in lieu of its laid-off workforce. Even amidst this climate of uncertainty, numerous AI startups witnessed an unprecedented surge in funding. However, amidst the hype, only a handful of companies managed to effectively harness the technology and identify practical use cases. GoTo, formerly known as LogMeIn, emerged as one such company, solidifying its position as one of the largest Boston-based enterprises.
Analytics India Magazine got in touch with Andrew Kernebone, APAC solutions consulting director, GoTo, to understand how the company leverages generative AI to provide solutions to customers and what are the challenges they face. “I think there are a lot of unknowns for many companies, but I’m excited by what I see already,” he said, when asked about how he feels about the adoption of generative AI in the IT sector.
Giving an example, he says, “If you look at the service industry, for instance, in BPOs, where they provide service desk functionality for organisations, customer experience is the key to success.” According to him, being able to have augmented or AI instant advice for the agent is powerful. AI can think faster than humans and guide them with customised responses, which results in a much better experience for the end user.
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“The agents receive real-time advice and have a voice in their ear, and that’s really exciting to me. In the near term, the augmentation of our capabilities in this space excites me the most,” he said.
However, when asked about the issue of the company’s IP codes falling into the public database when using models like ChatGPT, he pointed towards the email he received minutes ago. It was an update from the company’s internal IT security team discussing guidelines on how the company should use generative AI capabilities internally. They emphasised the importance of being cautious with public tools like ChatGPT, as they are accessible to anyone. “By inputting intellectual property into such tools,” says Kernebone, “we essentially add it to the engine’s knowledge base, making it potentially accessible to others. Security is undoubtedly a top concern for many people in this regard.”
Kernebone believes that having access to a private, exclusive language model becomes crucial, rather than relying solely on the public interface. From a systems perspective, he says, the challenge lies in integrating the company’s own toolset with a secure implementation of generative AI.
Additionally, says he, on the employee side, there’s the aspect of ongoing security education and training. Phishing attacks are incessant, and they are likely to become more sophisticated with AI. It’s essential to constantly remind and train employees to be vigilant and adept in using these tools within a secure framework.
ChatGPT Use Cases and Layoffs
Speaking of the use cases of ChatGPT in the company, he said, “One of the main areas we’re currently focusing on is our global use of unified communications capabilities.” He explained that the company has a feature called customer engagement, which essentially provides a streamlined call centre capability, allowing agents to interact with customers across multiple digital mediums. “We now have an integration with ChatGPT that gives the agent real-time advice on responses. So when they’re dealing with customers, they get real-time customised messages for that customer, in banking or any other industry,” said Kernebone.
When asked if the adoption of generative AI will lead to less hiring in future, he was of the opinion that it goes back to any of the great leaps in technology. “If we look back to when we transitioned from manual to machine manufacturing, those who manufactured things with their hands, lost their jobs. Jobs changed,” he said.
However, he believes that it’s more about augmentation and making people more efficient. He agreed that the companies will likely use these advancements to grow without needing to hire as many people. “But at the same time, this opens up new ideas and possibilities that we haven’t even thought of yet. It presents opportunities for new businesses, new models, and new employment opportunities,” said Kernebone. “While we tend to focus on what we might lose, I believe there is tremendous potential for what we might gain.”
Kernebone also asserted that when it comes to countries like India with cheap labour, the adoption of AI might be costlier than hiring new people. “AI is not free, it relies on computational resources housed in data centres or distributed across multiple data centres,” he said.
He believes that the excitement of the adoption of AI may be more pronounced in countries with higher labour costs, where companies see the potential for achieving more with fewer employees. In contrast, in countries where labour costs are lower, he believes that the equation may change over time.
“While AI might seem like a compelling idea on paper, cost analysis becomes a significant factor to consider. This backend information adds an intriguing layer to the conversation that is often overlooked,” said he.