What is Intelligent Automation?

The advent of Large Language Models (LLMs) has heralded a new era in artificial intelligence. OpenAI’s o1 represents a significant leap forward in LLM reasoning, offering a platform to explore the untapped potential of machine intelligence.

Reasoning-enabled LLMs advance beyond traditional pattern recognition by employing a “chain of thought” technique to create multi-step solutions, where problems are decomposed into sub-problems, and a series of logical steps or hypotheses are generated, before culminating in a synthesized answer that reflects human-like reasoning.

While this could massively boost productivity and help automate processes that previously could not be automated, the true value lies in harnessing the unique computational strengths of LLMs for sophisticated problem-solving, which leverages the use of Intelligent Automation, a framework that allows businesses to make automation better through the correct application of AI, with the necessary amount of human intervention, rather than relying solely on AI or other automation tools to get tasks done.

Let’s look at a real-world example using supply chains.

In the quest to optimize a company’s supply chain, managers start with spreadsheets, gathering data through laborious meetings and analyses. They’ll hypothesize, implement, and iterate, a process that could stretch over months, potentially missing out on the most efficient solutions due to human biases or limited data processing.

LLMs, armed with the ability to reason through vast datasets, analyze and simulate scenarios, predict outcomes, and iterate solutions quickly while offering a level of precision and speed unattainable by human analysts alone.

However, human intervention is still necessary to ensure the data supplied to the AI agents are free from noise, have robust governance standards and adhere to any regulatory requirements, necessitating the right balance of AI-based automation with human oversight for automation to work in the intended manner.

AI for Intelligent Automation with Mu Sigma

While LLMs excel in speed and scale, humans bring the nuanced touch of creativity and robust sensory systems. The synergy lies in using LLMs for their computational prowess to handle complexity and scale. At the same time, humans provide strategic vision and adaptability to real-world nuances, ensuring that business decisions are not only efficient and effective but also wise. Combining AI with human reasoning is what we refer to as Intelligent Automation.

Mu Sigma’s platforms for Intelligent Automation employ LLM agents that use the “chain of thought” process employed in LLM reasoning to engage in a sophisticated dialog, simulating real-world scenarios to test and refine operational plans. Businesses can leverage the superior speed and computational capabilities of AI, combining them with the inferring and contextual thinking capabilities humans possess to create systems that deliver their full potential.

Enhancing LLMs with reasoning capabilities marks a pivotal moment in AI’s integration into business operations. As we embrace this technology, the potential to solve complex business problems with AI reasoning opens new avenues for innovation, efficiency, and strategic foresight. For businesses ready to adapt, the future looks not just intelligent but profoundly reasonable.

If you’d like to learn more about LLM reasoning or explore the possibilities of using AI for Intelligent Automation with Mu Sigma, talk to us today!