Understanding AI and Its Transformative Potential

There is so much that AI can impact in our current world. So we are creating a series of articles to help understand AI as it not a threat but an opportunity. The focus is on AI and Management. Given that the majority of businesses eventually fail, it is challenging to grow them and sustain that growth. Within an organization, AI can significantly influence business expansion. Therefore, we will explore AI from this perspective.

This is an exciting time for business and AI. While there is much discussion about AI in headlines, few truly understand its impact. Let's step back and grasp the meaning of AI within an organization. It's about a perspective, and once understood, it can be harnessed.

To effectively use AI in organizations, it's essential to understand the core concepts in the areas of interest. Artificial Intelligence has been a term around for a long time, but current software developments make this an exciting period for organizational functions and business growth.

Let's revisit IBM in 1970, which developed SQL, a database language to manage and create databases. Ashton Tate in the mid-1980s developed database software that allowed users to create fields for market and customer information. IBM pioneered SQL, and Ashton Tate created dBase Database Software, selling it for PCs before being acquired by Borland. Microsoft partnered with Sybase and then created SQL Server. This was an intelligent way to manage marketing information in the late 1980s and, along with the development of Local Area Networks in the late 80s and early 90s, contributed to the growth of data in databases worldwide. Over the last 40 years, the challenge has been extracting and interpreting this data through analytical tools like Excel, a process that was heavily manual and time-consuming.

It's helpful to view software development as an evolutionary conveyor belt, with powerful innovations emerging to make tasks easier and more enjoyable for humans. This evolution is continuous, and we, as humans, must adapt to embrace these changes as part of our existence, rather than viewing them as a threat.

Software engineers often refer to "full-stack developers," likening it to a stack where SQL represents the starting point. At the top of this stack, we now have new tools for building UIs and enhancing user interfaces, built upon legacy database systems that store vast amounts of information. Language frameworks like REACT, pioneered by Facebook, and Angular, by Google, along with their foundation in JavaScript, are examples. We also have large language models (LLMs), originating with Alan Turing's work in 1950, evolving into prediction models and Neural Networks capable of processing large datasets. This forms the basis of LLMs, and in recent years, we've seen the emergence of Generative Pre-trained Transformers (GPT).

Another crucial language is Python, released in 1991, which evolved from the ABC programming language and is now the core language used by data scientists and machine learning engineers. Software development is a continuous process of innovation.

Current Landscape of AI Adoption in Business

Since ChatGPT's emergence and Nvidia's subsequent share price surge in late 2024, a narrative has taken hold. While many companies and markets stagnated from 2022 until then, forward-thinking businesses quietly innovated, transforming their technologies and introducing new products and services. Suddenly, the focus shifted to "Large Language Models" (LLMs) and training software to harness public domain information. In 2025, many companies remain uncertain about AI implementation and its benefits, yet a pervasive "Value Proposition" suggests that AI adoption guarantees profitability and organizational efficiency. Journalists and influencers amplify this message. However, let's delve deeper and revisit the concept of "intelligent software" rather than just AI. Furthermore, let's consider "organizations" broadly, encompassing entities beyond for-profit companies, such as government departments.

Organisations can be viewed as a series of tasks designed to benefit society. For example, consider processing an immigrant's application or scheduling a doctor's appointment. These tasks involve steps that either generate more tasks or conclude the process. Currently, individuals manually process these tasks using user interfaces, often leading to delays and communication gaps. This raises questions: Is the software inadequate? Are the processes flawed? Or are human operators lacking flexibility and decision-making capabilities? Intelligent software, designed to map processes and address these inefficiencies, could offer significant improvements. While such software might have been initially developed to reduce labour and time, the question remains: Does AI offer a substantial advantage?

This example illustrates how AI, alongside software, could enhance business efficiency. However, AI adoption requires careful consideration. Currently, there's an overemphasis on marketing and sales through chatbots, which are often less intelligent than perceived. Business and organizational success hinges on innovation and scale, differentiating between large and small entities. Achieving a competitive edge through AI is paramount.

AI will impact various industries differently, influenced by data types, management, and sector-specific knowledge bases. Each industry must carefully evaluate AI's impact and cost. Businesses should analyse AI across key areas to gain a competitive advantage, remembering that this advantage diminishes as competitors adopt similar technologies.

Focusing on AI to enhance customer interactions, such as chatbots and personalized recommendations, is prevalent. However, AI's potential extends beyond these applications.

We will explore more in our next chat