AI-powered supply chain optimization

AI: A Game-Changer for Business Productivity – Part 1


Artificial Intelligence (AI) has become a focal point in contemporary discussions, particularly on social media and the vast digital landscape, evoking a spectrum of reactions and apprehensions. This intriguing response stems from our historical fascination with AI, notably in the realm of science fiction. However, the narrative has shifted dramatically with the advancement of AI technologies and their integration into our everyday lives.

The Evolution of AI Discourse: From Fascination to Apprehension

The discourse has evolved from fascination to apprehension. The idea of entrusting our Google credentials to an AI system has kindled unease. This apprehension is primarily fueled by a lack of understanding and the portrayal of AI in media as a potentially hostile force, capable of taking over the world and replacing us in the workforce. Such depictions have fostered a widespread panic, largely rooted in misinformation and ignorance. In this upcoming series of articles on AI, We aim to debunk these misconceptions and alleviate some of these fears.

AI as a Business Necessity

Our objective is to underscore the real-world benefits of AI and emphasise that adopting AI isn’t just an option – it’s a vital business necessity for ensuring survival and competitiveness in the rapidly evolving business landscape. We are confident that a clearer understanding of AI technology will turn apprehension into appreciation for this transformative technology.

Historical Revolutions in Human Activity

Over the past centuries, human activities have undergone numerous revolutions, with technological advancements permeating every industry. As one sector reaps the benefits of emerging technologies, there’s a spillover effect onto adjacent sectors, instigating and sometimes mandating change. It’s a classic case of adapt or perish. For instance, in the automotive manufacturing industry, robots were initially introduced as assistants on the production line to boost productivity and ease laborers’ work. Initially, this was a welcome innovation. However, as robotics advanced, it paved the way for new career paths such as industrial engineering, robotic programming, and quality assurance, all refined by the advent of robotics in manufacturing.

Understanding AI in Context

Understanding AI in context is crucial as we need to evaluate whether it’s the new operational paradigm or the tools and advancements resulting from this paradigm. Just as the production line led to robotic automation, and later the technologies and disciplines that stemmed from it. Regardless of the terminology used—AI, machine learning, or deep learning—there’s no genuine intelligence yet, but rather the computational power and vast data resources enabling traditional statistical methods to address contemporary problems at an unprecedented scale. This is essentially Statistics 101 in the 21st century.

Bill Gates on AI

Bill Gates, who spearheaded the computer revolution in the ’80s, argues that the advent of AI chatbots like ChatGPT is as significant as the emergence of the internet or the evolution of personal computers.

In an interview with Forbes, Gates projected, “AI will be the most debated topic of 2023.” He added, “This is as pivotal as the PC, as the internet.”

AI: The Overarching Paradigm

When examining AI in the context of available technologies, AI serves as the overarching paradigm—a technique that enables machines to mimic human behavior. From there, Machine Learning and Deep Learning are subsets of this overarching AI paradigm. Machine Learning facilitates statistical methodology to improve with each interaction and iteration, while Deep Learning computes a multi-layer neural network to make this possible. In the end, it all distills down to pattern recognition at a scale only feasible today due to massive computing power combined with vast volumes of data for “learning.”

The Transformation of Manufacturing with Data-Driven Insights

Manufacturers are reshaping their traditional product strategies, from raw material procurement to the final production stage, through data-driven insights and analytics. For businesses employing Just-In-Time (JIT) Manufacturing, the need for long-term inventory storage is eliminated. With AI technology enabling real-time click-to-order and fulfillment, value creation is driven by enhancements in supply chain efficiency.

The Next Generation of Production Processes

AI-enhanced supply chains, supplemented with machine learning and robotics, are ushering in the next generation of production processes. These provide more intelligent and optimal ways to streamline production activities. The role of AI in supply chain management is transforming how inventory is managed and how smart factories resolve production issues on the shop floor. Technology has empowered manufacturers to further fine-tune the core principle of Just in Time Manufacturing. This is achieved by providing a real-time optimization feedback loop to support quicker decision-making, lower work-in-progress, and ultimately superior customer service.

AI Innovations: ThroughPut’s ELI

An illustration of such innovation is ThroughPut’s AI-Powered Supply Chain Software Suite, ELI. ELI is a real-time industrial data analysis engine powered by AI. With ELI, businesses have access to an industry-scale, automated, enterprise-ready AI software solution. This gives complete control over inventory and facilitates the seamless implementation of JIT Manufacturing principles. This is achieved without compromising on product quality improvement in manufacturing and maintaining smart supply chain standards.

The Pervasive Use of AI in Our Lives

Without necessarily realizing it, many platforms already leverage AI technology. The motivation behind this implementation is customer-centricity and maintaining active user engagement.

The Rapid Growth of AI-Driven Solutions

The value of AI-driven solutions can be gauged by how rapidly they achieve the 1 million user milestone.

Stay tuned for the next part in this series where we will delve deeper into the practical applications and advantages of AI in various industry sectors.