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At MWC 2026, HCLTech explores how AI-native transformation, silicon innovation and ecosystem partnerships are reshaping the future of telecom, media and technology
Read the articleHCLTech and Intel powering secure innovation
Watch nowAs AI agents begin to discover, negotiate and transact with one another, governance must move from system-level safeguards to ecosystem-scale
Read the articleHCLTech–Microsoft Partnership: Turning AI Ambition into Measured Business Outcomes
Watch nowAt a GoI approved pre-summit for the India AI Impact Summit, leaders from HCLTech, Intel and Cisco discussed how Agentic AI, edge intelligence and new trust models are reshaping resilience
Read the articleA modern testing strategy that shifts from code-centric checks to continuous data, model and risk validation to ensure AI systems are reliable, fair and production-ready
Read the articleAs electrification reshapes transportation, AI-powered customer experience innovation is becoming a strategic differentiator across the EV charging ecosystem
Read the articleAs automotive companies invest heavily in electrification and digital mobility, AI-led finance transformation is proving to be a powerful enabler of resilience, recovery and sustained innovation
Read the articleOrganizations face a pivotal moment in 2026 as AI, data proliferation, trust and economic models intersect with how work is designed and executed
Read the articleAt HCLTech’s Davos pavilion, leaders from HCLTech, Cisco and CrowdStrike mapped the partnership shifts required to move AI from costly experimentation to trusted, scalable value creation
Read the articleAt HCLTech’s pavilion during the 2026 WEF in Davos, a panel discussed the important role of AI in advancing education and preparing the workforce of tomorrow; a premise that no longer feels debatable
Read the articleResponsible AI trends in Retail and CPG: The consumer impact of agents, trust and personalization
As AI becomes the new interface between shoppers and brands, Retail and CPG leaders must balance trust, authenticity and agent‑driven personalization while rapidly scaling AI with clear ROI
Read the articleTrending 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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