Evolution of AI and its impact on the workplace

Time of India

20 hours ago

Dr Rao is currently teaching risk management in the institute of Insurance and Risk Management (IIRM). A career banker with Bank of Baroda, he held the position of General Manager - Strategic Planning, Later was Associate Professor with National Institute of Bank Management (NIBM) and was Director, National Institute of Banking Studies and Corporate Management (NIBSCOM). He writes for financial dailies on Banking and Finance and his work can be viewed in the public domain.His academic accomplishments include Ph.d in commerce from Banaras Hindu University (BHU), MBA ( Finance), LLB. He runs a Youtube channel - Bank on Me - Knowledge series He likes to share his perspectives with next generation potential leaders of the banking industry. His book on "Transformation of Public Sector Banks in India' was published in september 2019. His most interesting work is in Ideasforindia.com blog. LESS ... MORE
The most innovative and disruptive enabler in Industry 5.0 is the emerging scope of state-of-the-art technology – Artificial Intelligence (AI)- that has begun to reshape the business world, more so in recent years. In what form AI will evolve and how it challenges human intelligence to control its impact on people's lives is uncertain. AI refers to any system that can simulate human intelligence: reasoning, learning, problem-solving, creating artificial perception, and mimicking human voice.
Keeping AI transition in view, the industry has moved on to build upon Technology 4.0, after exploring innovative tools such as Big Data, data analytics, block chain technology, Internet of Things (IOT), cloud computing, cyber-physical systems (CPS), cloud computing, robotics and automation, augmented reality (AR) virtual reality (VR), 3-D printing, and blockchain technology.
Technology 5.0 is the convergence of advanced digital technologies with a human-centric approach, emphasizing collaboration between humans and machines, environmental sustainability, and societal well-being. AI in technology 5.0 is a great potential innovator with power to create value inconceivable for humans and may look like a disrupter in the near term. AI is a powerhouse possessing human like intelligence minus emotions. AI can achieve its targeted goals based on its design regardless of its consequences. Hence the debate is razing about regulating AI.
Debut of AI
The genesis of AI dates back several decades, it picked up pace after other collaborative technology tools combined with the expanded power of the internet, fuelled its wider applications in industries. The internet has significantly increased the power of AI to transform industries, societies, and everyday life.
AI acts as both a catalyst and an infrastructure backbone for modern business management, transforming workplace dynamics. Moving from one level of technology to another – automation of processes to mimic the human mind, AI is capable of thinking and acting like humans, challenging real human intelligence.
To understand how AI is influencing the industry workplace, creates/distorts employment opportunities, changes job roles/job profiles of workers, reshaping skills, changing shape of jobs, proliferation of gig worker community and many other dimensions of working world, it is necessary to understand its emerging nuances.
Advancement of application of AI began with the rise of Machine Learning (ML) during the 1990s-2000s. Symbolic AI changed to data-driven algorithms based on ML, leading to the development of decision trees. ML models started learning patterns from data rather than rules. The entry of Big Data, the Internet, and Cloud computing in 2000 brought a seminal change in the AI capability. It was possible to create the data and infrastructure needed for training large language models (LLMs) and neural networks to be effectively used in every field generating intricate data sets.
During 2010, Deep learning entered the AI ecosystem with AlexNet (Alex Krizhevsky) innovating the convolutional neural network while ImageNet (a collection of vast images) was created by Fei-Fei Li and her collaborators in 2007. It led to the development of Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs). They collectively increased the capacity of AI to surpass human performance in vision, speech, and translation.
Transition of AI architecture:
The AI has now developed into Generative Pre-Trained Transformers (GPT) models. Google developed a powerful natural language processing model – Bidirectional Encoder Representations from Transformers (BERT) that uses the transformer architecture to understand natural languages. DALL-E, an AI model that generates images from text. AlphaFold developed by DeepMind, now part of Alphabet/Google, predicts 3D structure. AI has developed further on large language models (LLMs) and transformers, understanding coding and reasoning.
Among the subparts of AI, ML is a system where computers learn from data to make decisions and predictions. ML is based on three broad methods (a) supervised learning – learns from labelled data (e.g., spam detection). (b) Unsupervised learning – finds patterns in unlabelled data (e.g., customer segmentation) (c) Reinforcement learning – learns by trial and error (e.g., game-playing AI).
Robotics is also a subset of ML applied to machines that can sense, process, and act in the physical world, such as autonomous vehicles, industrial robots, drones, etc. Remotely controlling them or operating them with robotic process automation (RPA).
Deep Learning (DL) is yet another subset of ML using neural networks with many layers (deep neural networks). DL is excellent for image recognition, speech processing, natural language tasks, etc. Natural Language Processing (NLP) enables machines to understand, interpret, and generate human language. With these tools, AI is extensively used in Chatbots, language translation, and sentiment analysis. Computer Vision (CV) as a part of an AI framework allows computers to interpret and understand visual information, leading to facial recognition, medical imaging, and object detection. Generative AI and Agentic AI can bring a sea change in the productivity of the companies, provided the employees are competent to deploy these tools.
Impact of AI:
The scope of application of AI tools is immense, which has enabled many technology entities to downsize their manpower. Many low-end roles are disappearing. Reskilling is the only option left with such people to stay relevant. AI bots are replacing human coders. It is estimated that during 2024, close to 150000 employees will be laid off globally. Another 50000 in the first five months of 2025. Global giants such as Microsoft, IBM, Google, Amazon, and CrowdStrike have downsized their teams. Traditional back offices in India are also reducing their staff strength, but Global Capability Centres are increasing intake.
The role descriptions of many people are changing, posing a challenge to cope with the new skills. It is estimated that going forward, 19 million jobs are at stake. The role of HR is changing. They need to adopt an AI-based screening and recruitment process, and team members are shrinking. According to a report by US US-based Society of Human Resource Management (SHRM), technology is not a barrier when combined with human intellect, AI can enhance the synergy.
Way forward:
To rationalise the use of AI tools, even individuals should re-skill themselves. They need to reinvent themselves to sync with the AI-driven strategic job roles. Organisations should invest liberally in human capital to strengthen their capacity to harness AI. They should be exposed to using AI tools efficiently. Universalisation of technology literacy with a focus on AI/ML/DL applications is essential.
The next challenge is to protect the digital architecture from cyber threats. Data security and data privacy are a fiduciary onus of the entities. Preventing data breaches, data compromises, and malware intrusions is the other possible risk.
The Thales data threat report -2025 clearly outlines the operational risks arising from technology, including the use of AI. The industry has to balance between harnessing the power of AI, protecting the employees by reskilling them, and employing enhanced methods for robust and invincible data protection in the best interest of stakeholders.
A 360-degree view of AI suggests that a high-quality business transformation is possible in the long run if the near-term hiccups in its operations can be handled with inclusive strategic efforts.
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Views expressed above are the author's own.