Published on: 7th February 2026
Authored By Nivedita Roy
Dr. D.Y. Patil Law College, Pune
INTRODUCTION
The world today is moving at an unimaginable pace. Machines have taken over almost every task we once did manually from cooking and cleaning to driving and diagnosing diseases. But what’s even more striking is that now, we have websites and artificial intelligence tools that think for us. We no longer pause to reflect, analyse, or create independently; instead, we seek instant answers generated by algorithms. While this technological progress showcases how far humanity has advanced, it quietly erodes our ability to think critically and reason deeply. In our pursuit of efficiency, we are slowly surrendering the very essence of human intellect, our capacity to imagine, question, and innovate.
But despite these concerns, progress remains unstoppable. The world continues to embrace technology as an inseparable part of modern existence, and artificial intelligence now stands at the forefront of this transformation. As society learns to coexist with this evolving technology, it becomes crucial to understand its foundation and implications. This article explores the simple fundamentals of artificial generative intelligence, its meaning, diverse types, major functions, and the profound potential it holds for reshaping the future of human thought, creativity, and progress.
ARTIFICIAL GENERATIVE INTELLIGENCE
The term artificial generative intelligence is attributed to Mark Avrum Gubrud, who is recognized for having used the phrase “advanced artificial general intelligence” as early as 1997 in an article exploring the military applications of AI. Generative AI captured global attention following the release of ChatGPT a chatbot built on OpenAI’s GPT-3.5 neural network model in 2022.
Artificial General Intelligence (AGI) refers to a theoretical form of AI that would match or surpass human intelligence across a broad spectrum of tasks and domains. It is designed to excel at a single function, AGI would demonstrate capabilities such as that it would possess the ability to reason and learn by adapting to new information and acquiring knowledge beyond its initial programming. It would apply common sense, enabling it to understand implicit facts about the world and make informed decisions. According to Oracle, generative artificial intelligence, unlike its predecessors, can create new content by extrapolating from its training data. Its extraordinary ability to produce human-like writing, images, audio, and video have captured the world’s imagination since the first generative AI consumer chatbot was released to the public in the fall of 2022. GenAI now powers a range of consumer and professional applications and services that help save time, money, and effort.
Furthermore, AGI would be capable of solving unfamiliar and complex problems efficiently. It would communicate naturally, interpreting context, forming insights, and engaging in sophisticated conversations using human language. It would demonstrate creativity and imagination by generating novel concepts and mental imagery. AGI might also exhibit emotional intelligence, allowing it to perceive and respond to emotions with understanding. Importantly, it would have the capacity for self-improvement, continuously enhancing its own capabilities without external intervention.[1]
Now, there can be three types of AGI.
Artificial Narrow Intelligence, also known as Weak AI, refers to AI systems designed and trained to perform a specific task or a narrow range of tasks within a defined domain. These systems operate under limited constraints and are not capable of generalizing their knowledge beyond their programmed functions. Examples include virtual assistants like Siri and Alexa, recommendation systems such as Netflix’s algorithm, chess-playing AI like Deep Blue, and various image recognition software. While ANI can perform these tasks with remarkable efficiency and accuracy, it lacks the ability to adapt to new or unforeseen situations. As of now, ANI is the only form of AI that exists and is widely utilized across various industries.[2]
Artificial General Intelligence, or AGI, represents a theoretical stage in AI development where a system possesses the ability to understand, learn, and apply knowledge across a wide range of tasks, matching or surpassing human cognitive abilities. Unlike ANI, AGI would not be limited to specific functions but would exhibit general intelligence, capable of reasoning, problem-solving, and adapting to new challenges in a manner akin to human beings. While AGI remains a subject of extensive research and debate, it has not yet been achieved. Experts in the field continue to explore the pathways and challenges associated with developing AGI systems.[3]
Artificial Superintelligence, it refers to a hypothetical AI that surpasses human intelligence across virtually all cognitive domains, including creativity, general knowledge, and problem-solving. ASI would not only perform tasks better than humans but would also have the capacity to improve and enhance its own capabilities autonomously. This level of intelligence is considered far in the future and remains highly theoretical. The development of ASI raises significant ethical, philosophical, and safety concerns, particularly regarding its potential impact on society and humanity.[4]
AGI IN INDIA
India is witnessing a growing research focus on Artificial General Intelligence (AGI), with premier institutions like the Indian Institutes of Technology (IITs) in cities such as Bangalore, Mumbai, Delhi, Madras, Hyderabad, and Kharagpur emerging as key centers for advanced AI research. These institutions are actively exploring theoretical foundations that could contribute to AGI.[5]
Also, recognizing the strategic significance of AGI, the Indian government has incorporated it into the National AI Strategy spearheaded by NITI Aayog.[6] This strategy includes initiatives such as dedicated research funding for AGI, the creation of regulatory sandboxes to facilitate experimental development, promotion of public-private partnerships, and the establishment of specialized educational programs to nurture talent.
Although private sector involvement in AGI is still developing, India’s vibrant tech industry especially in Bangalore, is playing an indirect yet vital role through foundational AI research and innovation in advanced technologies. Indian researchers are also delving into critical areas for AGI advancement, including cognitive computing architectures, cross-domain learning, and adaptive AI systems.
In parallel, India is making strides in formulating ethical and governance frameworks for AI. The Digital Personal Data Protection Act of 2023, while not AI-specific, lays down important principles for data privacy essential to AI development. The government is committed to a “pro-innovation” approach, aiming to balance technological progress with ethical safeguards. An advisory group is currently working on an “AI for India-Specific Regulatory Framework” to ensure that the nation’s AI ecosystem remains trustworthy, responsible, and aligned with national interests.[7]
CHALLENGES
While generative AI has made remarkable strides, several limitations have been noticed that highlight why the journey toward Artificial General Intelligence (AGI) remains highly challenging. One major drawback is the absence of true understanding and reasoning in current AI systems. These models operate primarily by detecting patterns and correlations within their training data, enabling them to generate coherent text or realistic images, yet they do not genuinely comprehend the underlying concepts or the real world. In contrast, AGI would require deep understanding, logical reasoning, strategic planning, and the ability to make informed decisions.
Another significant limitation is the lack of common-sense knowledge. Humans possess vast amounts of implicit, intuitive understanding that guides daily decision-making and interactions, something extremely difficult to encode into machines. For AGI to function effectively in real-world scenarios, it would need not only to acquire this kind of knowledge but also to apply it flexibly across different situations.
Additionally, the capacity for generalization and transfer learning remains a major challenge. Today’s generative AI can be fine-tuned for specific tasks, but AGI would need to learn in one domain and then successfully apply that knowledge in entirely different contexts, much like humans do.
Finally, human intelligence is deeply shaped by embodiment and physical interaction with the environment. Our ability to perceive, move, and interact with the world influences how we think and learn. Replicating this in machines would require AGI systems to develop sensory perception, fine motor skills, and the ability to navigate and respond to dynamic surroundings an area where current AI is still severely limited.
CONCLUSION
While generative AI can mimic creativity through pattern recombination, genuine human creativity often involves novel thinking that breaks free from learned patterns. Achieving this level of innovation in AGI is still a major challenge. Alongside these technical obstacles are growing ethical and safety concerns. As AI systems become more autonomous and powerful, ensuring they act in ways that align with human values commonly referred to as the “alignment problem” is vital. The risk of a misaligned AGI pursuing harmful objectives cannot be ignored. Also, the computational and data demands of AGI are expected to be immense, potentially surpassing the capabilities of current infrastructure.
As for the timeline, opinions among experts vary widely. Some predict AGI could emerge as early as 2026 or 2027, spurred by rapid generative AI advancements, while others argue it may take until mid-century or might never be achieved at all. Regardless of when or whether it arrives, AGI would represent a transformative leap, reshaping global economies, labor markets, cultural norms, and even our understanding of intelligence itself.
Ongoing research efforts focus on multiple fronts, including cognitive architectures modeled after the human brain, advanced machine learning methods such as meta-learning and reinforcement learning, and ethical frameworks to ensure AGI development remains responsible and aligned with societal values.
Ultimately, the transition from generative AI to true AGI demands not only groundbreaking technological innovations but also robust ethical safeguards and massive computational advances. While current AI systems offer a glimpse into what is possible, AGI remains the most ambitious and challenging goal in the field of artificial intelligence.
[1] ‘Generative Artificial Intelligence’ (QAA) <https://www.qaa.ac.uk/sector-resources/generative-artificial-intelligence> accessed on 1st October 2025
[2] ‘What Is Artificial Narrow Intelligence?’ (Coursea, 1st Feb, 2025) <https://www.coursera.org/articles/what-is-artificial-narrow-intelligence> accessed on 2nd October 2025
[3] Cole Stryker and Mark Scapicchio ‘What is generative intelligence?’ (IBM Think) <https://www.ibm.com/think/topics/generative-ai> accessed on 2nd October 2025
[4] libid
[5] PM-STIAC ‘Artificial Intelligence’ (Office of the Principal Scientific Adviser to the Government of India) <https://www.psa.gov.in/ai-mission> accessed on 4th October 2025
[6] NITI Aayog, ‘National Strategy For Artificial Intelligence #AIFORALL’ (June 2018) <https://www.niti.gov.in/sites/default/files/2023-03/National-Strategy-for-Artificial-Intelligence.pdf> accessed on 4th October 2025
[7] The Digital Personal Data Protection Bill, 2023 (PRSIndia Legislative Research) <https://prsindia.org/billtrack/digital-personal-data-protection-bill-2023> accessed on 4th October 2025
