Agentic AI: The Next Wave of Artificial Intelligence

Technology trends often progress in waves, with each phase introducing incremental improvements that build upon the advancements of the previous one. However, once in a generation, a transformative change comes along that causes seismic shifts that impact far beyond the technology industry. The last time this happened was the displacement of traditional enterprise software with B2B SaaS in the late 2000s. Before that, the 1990s saw the emergence of client-server architectures that disrupted legacy products and business models. This gave us new options, such as COTS (Commercial off the Shelf) software, which caused significant disruptions to traditional enterprise vendors. Each time, such changes generated waves of innovation. Agentic AI, artificial intelligence systems that can independently pursue goals, make decisions, and take actions with minimal human intervention, will be another such transformative change.  

Recent Technology Shifts 

In recent memory, each time a major technological shift has occurred, three factors converged at once:  

1) A technological step forward,  

2) A step-change in business practices and  

3) A strategic innovation 

In the 1990’s, we saw:  

1. Client-server architectures and networking improvements,
2. The displacement of custom builds with off-the-shelf 
3. The emergence of CRM, ERP and other centralization trends

In the 2000’s came: 

1. Infrastructure as a service (cloud providers),
2. A surge in demand for annual subscriptions over perpetual licenses, globalization
3. The emergence of ecosystems and app stores

The Next Wave 

Now, 20 years later, Agentic AI is shaping up to be the next transformative change, causing ripples far beyond the technology industry. This time we have: 

Large Language Models

1. A productivity crisis + information overload
2. Upending software customization

Regarding productivity, many people are working on low-productivity efforts in the strict economic product sense. Automation of all kinds has been adding efficiency for a long time. In a macro sense, GDP per hour worked has been flatlining in most developed economies, and the developed world is facing demographic challenges. 

Agentic AI has the potential to shape these massive challenges by democratizing knowledge and automating middle management. Large language models are a technological catalyst, but they only comprise one of our three change factors. Knowledge work meeting artificial intelligence is a collision that will have far-reaching consequences on companies, industries, and nations. Meanwhile, our understanding of what it means to customise software to meet specific requirements will be transformed. Taken together, these changes will change the trajectory of industries, especially but not exclusive to financial services and societies in the future.

Junshu is transforming how financial institutions handle regulatory compliance through intelligent automation. Born from our firsthand observation of mounting “regulatory debt” – the accumulation of manual processes and inefficient systems that emerged after the 2008 financial crisis – Junshu developed an AI-powered platform that streamlines compliance operations, helping banks, investment managers, insurers, and fintechs break free from resource-intensive manual processes while enhancing accuracy and adaptability in an ever-evolving regulatory landscape.