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How can enterprises overhaul their operating models, across strategy, structure, culture and metrics, to become truly AI-led and customer-centric?
Read the articleExplore the transformative power of cloud and AI in the healthcare and life sciences sectors
Listen nowEnterprises must overcome process, data, security and interoperability challenges to unlock the full potential of Agentic AI
Read the articleModular GenAI platforms are redefining enterprise AI delivery - offering scalable, pre-built solutions that boost efficiency, reduce costs and accelerate implementation across industries
Read the articleEnterprise AI adoption jumped from 55% to 78% in a year, driven by GenAI, data readiness and business impact. Scaling AI now hinges on ecosystem-first, silicon-to-software collaboration
Read the articleOT/IT convergence, led by transformation in operational technology and powered by AI, is reshaping industries and organizations that act now will gain a decisive competitive edge
Enterprise AI at scale
Watch nowEnterprises can adopt an AI-led model by aligning leadership, encouraging experimentation, and scaling Generative AI through product and platform strategies
Read the articleA product‑aligned operating model unites infrastructure, data, AI and business expertise with accountability and governance, enabling enterprises to scale AI with agility, trust and repeatability
Read the articleGenerative AI empowers non-technical professionals to create transformative, efficient solutions, as highlighted by the transformation of employee onboarding at HCLTech
Read the articleGovind Chandranani, Practice Head of Engineering and R&D Services at HCLTech, discusses how enterprises adopting GenAI must embed responsible governance to balance innovation with trust and compliance
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Trending questions
The term "artificial intelligence" was coined by John McCarthy in 1956. Alan Mathison Turing, followed by Newell, Simon, McCarthy and Minsky, are key figures in AI development. Newell and Simon's 1956 "Logic Theorist" program marked a milestone. These pioneers, known as the founding fathers of AI, significantly advanced the field.
- Increased productivity
- Increased automation
- Smart decision-making
- Solve complex problems
- Managing repetitive tasks
- Strengthens economy
- Personalization
- Disaster management
- Enhances lifestyle
- Global defense
Machine learning is the brain of AI that emulates logical decision-making based on the data fed to it and an AI model is the creation, training and deployment of the ML algorithms. With advancements in intelligence methodologies, AI models support in tandem with real-time analytics, predictive analytics and augmented analytics using natural language processing (NLP), ML, statistical analysis and algorithmic execution.
Loaded with human capabilities and beyond, the importance of artificial intelligence (AI) is rising and gradually spreading to various industries, making way for new possibilities and better efficiencies. Data in today’s world is an asset and valued across industries. With AI, humans are now able to absorb, interpret and make complex decisions.
While artificial intelligence is a system that mimics or imitates human intelligence, machine learning is the brain that helps it work.
Generative AI refers to a subset of artificial intelligence algorithms and models designed to generate new data that resembles existing data. These sophisticated algorithms can create content in various forms, such as text, images, music and even complex structures like designs and models. Generative AI is primarily powered by advances in neural networks, particularly Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
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