By Raj K Gopalakrishnan, Co-Founder and CEO, KOGO
AI Agents have been in our phones and homes for years with apps like Siri and Alexa. And as AI becomes more powerful with Large Language Models and the less talked-about Large Action Models, businesses in India are presented with the unique opportunity to leverage AI Agents to improve entire workflows, regardless of which industry. Unlike conversational chatbots that operate on the ‘understand, decide and respond” model, AI Agents take it a step further and proactively take action.
Indian businesses are optimistic about generative AI and its potential use in helping them grow. When it comes to AI investments, Indian businesses are looking for Advances in AI tools that make them more accessible (59%), the need to reduce costs and automate key processes (48%), and the increasing amount of AI embedded into standard off the shelf business applications (47%) are the top factors driving AI adoption. However, business leaders say the lack of skill and the right AI tools are the top two barriers to AI adoption. When businesses think about investing in AI tools, they must consider how these tools can help improve their bottom line.
The next wave of growth lies with AI Agents
Currently, the conversational AI chatbots in the market listen to what businesses want and deliver exactly that. This is only one aspect of what generative AI can do. AI Agents take it a step further by performing the same functions as conversational AI bots but with the added capability of acting intuitively. For example, while planning a vacation it can complete an expense report without being asked or plan a travel itinerary, book tickets and more. However, there is more than just one use case and these assistants can be used across industries.
Let’s consider a simple scenario. A retail business operates a chain of supermarkets with expensive drink-dispensing machines. Soft drink sales generate a lot of money so when the dispensing machine breaks down, it would amount to huge losses in revenue for the retailer. Imagine a scenario where an AI Agent is deployed in tandem with the IoT device monitoring signals that indicate when a machine needs to replace parts. AI Agents can be used to automatically order parts, and have them shipped to specific locations along with recommended times for the technician to arrive for the maintenance work. All of this with no downtime. This is merely scratching the surface of what AI Agents can do.
Built on Large Actions Models, AI Agents can automate a wide range of tasks across various industries. From customer service and logistics, to manufacturing and healthcare. For example, AI Agents can be deployed along with manufacturing robotic devices to collaborate with humans on the shop floor, adapting to dynamic situations and making real-time decisions to optimise production. Additionally, it improves productivity, as AI Agents can tailor their actions and recommendations to an organization’s specific needs and preferences. From writing emails to managing daily schedules, planning vacations, providing personalized health coaching and financial advice, AI Agents will be the next wave of innovation that drives operational efficiencies and improves the bottom line of any business. In a workplace, it can identify which meetings to accept or decline, and which emails to ignore or raise for attention to.
Choosing the right AI Agent
With the buzz around generative AI, a lot of tools have flooded the market, making it a challenging prospect to identify which solution is the right fit. Businesses in India are concerned about not finding the right tools. In fact, 60% of Indian enterprises want to implement generative AI solutions and 34% of them are exploring the right fit.
Among the major concerns is the trustworthiness of an AI solution. Since AI is only as good as the data it is built on, it’s rational for businesses to be worried about biases and inaccuracies. Large Action Models stack multiple models together. When these models connect, any inaccuracies can intersect and amplify each other in unpredictable ways, potentially leading to runaway interactions.
It’s important for businesses looking to adopt AI Agents to ask the right questions and determine if the technology fits the bill. These include: Does the AI Agent understand human intent in multiple languages, no matter how complex? Can it see and understand images, and detect objects, variations and items? Can it collect structured or unstructured information from documents, databases, and even by searching the internet? Can it interact with voice, text, or a phone call across devices? Can it analyze structured or unstructured data and offer real-time insights? And most importantly, can it take real-world actions on other third-party apps?
When businesses find a solution that ticks all these boxes, it is also important to ensure that the AI Agent platform is built with enterprise-grade security to ensure data privacy. With cybersecurity top-of-mind for a majority of organizations, the solution must be able to continuously monitor interactions and system activities, detect and mitigate potential security threats. When AI Agents are built with security in mind, it can minimize the risk of data breaches and reduce AI-generated hallucinations.
AI Agents have the potential to transform Indian businesses and supercharge human capabilities. The future of AI lies in actionable intelligence, and AI Agents represent a monumental step in this direction. By combining language understanding with the ability to interact with the world, this technology will revolutionise the way we live, work, and interact with technology at the workplace.