IT provider Tata Consultancy Services (TCS) teamed with Anthropic to accelerate enterprise AI adoption, with a focus on highly regulated sectors where accuracy, auditability and governance requirements have historically slowed deployments.

As a Global Premier Partner in the Claude Partner Network, TCS will establish a dedicated business unit focused on delivering industry services and AI expertise built on Anthropic’s Claude family of models, with early access to new releases.

It will also provide Anthropic’s Claude AI assistant to more than 50,000 employees across engineering, finance, legal, marketing, and sales.

The two companies will jointly go to market with AI capabilities across financial services, public services, life sciences, healthcare, aviation, telecom, and medtech.

The partnership also spans several TCS businesses and platforms. Diligenta, TCS’s UK-based life and pensions business with over 22 million customers, will use Claude to improve customer experience through agentic process transformation.

TCS iON, which conducts more than 75 million annual assessments across 1,500 cities in India, will deliver learning and certification programmes on Claude models to help build an AI-certified workforce.

K Krithivasan, CEO and managing director of TCS, stated enterprise AI value comes from understanding business context, orchestrating complex systems and applying deep AI engineering talent.

“By combining Claude with our industry expertise, engineering rigour and large-scale transformation capabilities, we will help customers move faster to production, especially in industries where trust, resilience and regulatory discipline are critical,” he said.

The partnership comes as Anthropic, now valued at $965 billion, looks to extend the momentum which has pushed its valuation above rival OpenAI, with both startups moving towards public listings.

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Global logistics player LX Pantos made a major move around robotics, tasking LG’s consulting unit with helping to research the potential around using humanoid and shuttle variants.

LG CNS is to work with LX Pantos on an automation system to incorporate the two types of robots into the specialist’s Megawise Cheongna Logistics Centre, a fulfilment facility in South Korea spanning 142,852 square metres

The facility is one of 380 logistics hubs LX Pantos operates globally. Shuttle robots are to be used to retrieve items which humanoid versions would then sort and dispatch.

Robots are to be trained using LX Pantos’ field data through a proprietary learning platform. The machines themselves are being sourced from US specialist Dexmate, a company which LG CNS previously invested in.

Park Sang-kyun, EVP and head of Telecommunications, Distribution and Service Business division at LG CNS, said the companies would look to “verify the applicability of various robots”, learning and “operation platforms to logistics sites”.

The company explained the Dexmate mobile shuttle robot has a velocity of 1.5 metres per second and can handle goods weighing up to 1,500kg.

LG CNS and LX Pantos intend to establish a demonstration zone to showcase the potential of their robotics collaboration later this year, pitching possible benefits including a reduction in repetitive tasks at the logistics facility.

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AI platform disruptions rose sharply in early 2026 as growing enterprise adoption and heavier workloads exposed reliability issues across the full infrastructure stack, according to research from Ookla.

Analysing 471 days of US Downdetector data from 1 January 2025 to 16 April 2026 across ChatGPT, Claude, Gemini, Microsoft Copilot, AWS and Microsoft Azure, Ookla recorded 3.7 million user-reported problems.

High-signal disruption days, defined as when a service recorded more than 10 times its own median daily report volume, rose from six across four major AI apps in Q1 2025 to 51 in Q1 2026, according to the report by Ookla analyst Luke Kehoe.

Anthropic’s Claude model accounted for 39 of those 51 disruption days, making it the clearest example of scale-up volatility in the period. Gemini accounted for seven, Copilot three and ChatGPT two.

Claude recorded near-zero Downdetector reports in early 2025 before moving into a sustained report baseline from mid-July as adoption grew.

In Q1 2026, Claude generated 314,996 reports, while March volume alone was nearly three times February’s level. Ookla noted the pattern cannot be attributed to a single outage, with disruption clustered around demand surges, model-release windows and platform instability as Claude Code and Cowork usage scaled rapidly.

OpenAI’s ChatGPT produced the largest individual disruption signals in absolute terms, including roughly 68,000 reports on 2 December 2025, but its underlying reliability trend has improved.

Its monthly median daily report volume fell from a peak of 2,157 in April 2025 to 1,166 in April 2026, even as OpenAI reported more than 900 million weekly active users and rapid growth in Codex usage.

Google’s Gemini and Microsoft’s Copilot showed smaller but distinct patterns. Gemini’s high-signal disruption days rose from zero in Q1 2025 to seven in Q1 2026, consistent with rapid user growth.

Copilot’s outage pattern reflected its position inside Microsoft’s broader enterprise range, with far fewer reports on weekends, reflecting enterprise-aligned use.

Cloud infrastructure also featured prominently in the reliability picture. AWS’s 20 October 2025 DynamoDB DNS event generated more than 315,000 US reports, while Microsoft’s Azure Front Door incident on 29 October produced nearly 96,000, illustrating how failures in cloud control planes can cascade into AI platform disruptions.

Ookla concluded AI reliability has moved well beyond model serving, with failure points now spanning feature gates, GPU fleets, developer APIs, login systems and demand-management policies, all of which can appear to the end user as a single outage.

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