Enterprises have existed for over a hundred years, and with new technologies knocking on the door, enterprises are often required to change their technology stack and adapt their strategies to remain competitive and meet evolving market demands.
Today, we have moved from rule-based systems to advanced machine learning and deep learning models that can perceive, reason, and interact.
To be more precise, we are stepping into the age of AI Agents. This evolution has enabled AI to be integrated into various enterprise functions, offering unparalleled opportunities for growth and transformation.
At Cypher 2024– India’s largest AI conference– hosted by AIM Media House– Madhusudan Shekar, Customer CTO at Google Cloud, explores the future of enterprise architecture and discusses how organisations should adapt their structures to navigate this disruptive change effectively.
Evolving Enterprise IT
Shekar points out that enterprise IT looked very different a few decades ago when there were no mobile applications or the Internet.
“If you reflect on it, enterprise IT was vastly different before the advent of the internet and mobile technology. For those who were part of the industry in the mid-90s, consumer engagement primarily involved physical stores, print materials, or call centres. There were no mobile apps or internet services; shopping meant visiting a store or relying on catalogues and brochures,” he said.
Then mobility happened, transforming how we connect and interact, leading to a surge of new roles across various industries.
This evolution paved the way for big data and the age of cloud computing, which further revolutionised data storage, accessibility, and collaboration, enabling businesses to thrive in an increasingly digital and interconnected world.
As enterprises navigated various technological waves, one thing remained constant–change. “We had to change when data came. We had to change when mobility came. We had to change with cloud. We had to change,” he said.
The Age of Generative AI
However, today, we are in the age of generative AI. Shekar envisions a future where enterprises increasingly develop AI agents tailored for specific tasks. This shift will necessitate streamlined processes for rapidly building these agents to enhance operational efficiency.
As organisations implement multiple agents, the need for a centralised directory becomes crucial—serving as a canonical source for all agents within the enterprise. This central repository will facilitate easier management and access, ensuring that teams can leverage AI effectively.
Furthermore, to provide a seamless user experience, these agents must be able to coordinate and communicate with one another. By fostering collaboration among agents, enterprises can enhance workflows, improve service delivery, and ultimately create a more integrated technological ecosystem that meets their users’ evolving needs.
This approach not only optimises task execution but also helps businesses stay competitive in an increasingly automated landscape.
He believes enterprises must also consider several critical factors, including agent complexity, which refers to the intricacies of the systems and processes in use.
Additionally, they need to address the dynamics of a changing environment, ensuring their technology can adapt. Scalability needs are also essential to support growth, while fault tolerance is vital for maintaining operations during unexpected failures.
Lastly, communication overhead—how much communication is required between agents—plays a significant role in efficiency and overall system performance.
