News related to
across

A sector assessment by PhillipCapital said the April-June quarter had already shown resilience despite geopolitical disruptions, with industry occupancy rising by two to four percentage points from a year earlier. Average room rates increased 6-8 per cent, while revenue per available room, or RevPAR, advanced 11-13 per cent.

The brokerage expects business conditions to improve further during the October-March period, helped by a heavier wedding calendar, stronger meetings, incentives, conferences and exhibitions activity and higher international travel during the traditional peak season. Corporate travel, which was softer earlier in the year amid uncertainty linked to the West Asia conflict, has also shown signs of gradual recovery.

Limited additions to room supply in key markets are expected to give operators continued pricing power if demand strengthens as projected. That imbalance between demand and new capacity has been an important support for average room rates across several major destinations and is likely to remain favourable through the second half of the financial year.

The outlook is consistent with ICRA’s projection that hospitality industry revenues will rise 7-9 per cent year on year in FY27, following an estimated 9-12 per cent increase in FY26. The ratings agency expects pan-India premium hotel occupancy to remain at 72-74 per cent, broadly unchanged from FY26, while average room rates for premium hotels rise to Rs 8,600-8,800 from Rs 8,200-8,500.

Domestic travellers remain the principal source of demand and have helped cushion the industry from weaker foreign arrivals and disruptions to international air routes. ICRA estimated occupancy at 66-68 per cent during the first two months of FY27, compared with 62-64 per cent a year earlier, while average room rates were estimated at Rs 7,800-8,000 against Rs 7,500-7,700.

Leisure destinations have generally performed better than business-focused hotels during the opening months of the year. Indian Hotels Company reported strong demand across its domestic portfolio, with revenue from operations within India rising during the June quarter and leisure markets contributing significantly to growth.

Other listed hotel operators have also reported positive RevPAR trends, though performance has varied by city, customer mix and exposure to international guests. The sector’s recovery in the first quarter was more occupancy-led than in earlier periods, when sharp increases in room rates were the dominant driver of revenue growth.

Demand from corporate customers is expected to become more supportive as travel budgets normalise and business activity strengthens. Bengaluru, Hyderabad and Delhi have shown firmer room rates in parts of the second quarter, aided by technology, global capability centre and broader corporate travel demand.

International traffic remains a key variable. Foreign tourist arrivals were hit earlier by disruptions associated with the conflict in West Asia, but the Ministry of Tourism’s data portal indicates arrivals during 2026 have begun to show year-on-year improvement in available updates. A seasonal rise from October would add higher-paying international travellers to the domestic base.

Wedding demand is also expected to provide a material lift. Hotels typically benefit not only from room bookings during large celebrations but also from food and beverage, banquet and event revenue, making the wedding calendar an important contributor during the second half.

Meetings and exhibition business is another area expected to improve as companies resume travel and events. Stronger MICE demand can lift weekday occupancy at city hotels, complementing leisure traffic that is often concentrated around weekends, holidays and destination markets.

Risks to the outlook remain. A prolonged escalation in West Asia could again disrupt international travel and corporate spending, while inflation could weigh on discretionary consumption. ICRA has said these factors remain monitorable even though domestic demand has so far limited the direct impact on the sector.

J-HRTI, short for Japan Humanoid Robot Training & Implementation, opened its Kanto Data Factory in Narashino on August 26 with 35 humanoid robots across about 1,400 square metres. The centre can expand to 40 machines and is designed to generate, label and test the physical data needed to train robots for practical industrial work.

The consortium says the facility is Japan’s first physical-AI and robot data factory operated by a group composed solely of private companies. Its model is intended to reduce the cost and duplication involved when manufacturers try to build large robot-training systems independently, while allowing participating businesses to share common training data and testing infrastructure.

Operators telecontrol the humanoids to create imitation-learning data from tasks such as gripping, moving and handling objects. Cameras mounted on the robots record movements while motor parameters are also collected. Specialist staff then annotate the footage and motion information so AI systems can distinguish actions, errors and acceptable performance before the robots are tested in environments designed to resemble participating companies’ workplaces.

J-HRTI says members divide the cost of equipment and data generation while contributing real-world tasks from their own operations. Common datasets can be reused across companies, reducing the thousands or tens of thousands of training repetitions that an individual business might otherwise need to undertake from scratch. Sensitive company-specific work can be handled separately in a secure area, where information is not shared with other members.

That approach could widen access to humanoid development beyond the largest manufacturers, although J-HRTI has not published membership fees or a standard deployment price for factories. Claims that the system makes humanoids broadly affordable for mid-sized manufacturers therefore remain difficult to quantify. What is established is that participating companies can spread investment and technical risk rather than financing a dedicated data facility alone.

The operating group includes machinery trader Yamazen, pharmaceutical manufacturer Tsumura, direct-mail and logistics company DMS and Fuyo General Lease, alongside another participant that was not publicly identified in the August 26 announcement. INSOL-HIGH serves as the consortium secretariat and operates the data platform and overall system design.

J-HRTI’s programme is aimed initially at straightforward industrial duties. The group plans to place humanoids into workplaces for tasks such as material transport during the 2026 financial year, which ends in March 2027. It then intends to broaden the range of tasks and improve autonomy as more operational data becomes available.

The consortium is also developing a physical-AI foundation model using data collected at the Chiba site. Several thousand datasets had already been accumulated and annotated by the time full operations began, according to INSOL-HIGH officials. Participating companies are expected to use the model and return additional operating data and feedback, creating a cycle in which the shared training resource is continually updated.

Plans call for the data-factory network to expand to 10 locations nationwide during the 2027 financial year. The Chiba facility is intended to serve as the first “mother” site, with future centres positioned closer to industries that can supply specialised tasks and operational conditions. J-HRTI has said those regional facilities could also support maintenance after robots are deployed.

By the 2028 financial year, the group aims to provide foundation models specialised for sectors including manufacturing and logistics. The timetable remains a target rather than a guaranteed commercial rollout, and performance will depend on whether robots trained in controlled environments can operate safely and reliably in varied workplaces.

Devanathan is due to take up the newly created role in October and will be based in Singapore, reporting to Kiran Mani, OpenAI’s managing director for Asia-Pacific. Her responsibilities will cover consumer growth, enterprise adoption and partnerships, regulatory engagement and operations across Southeast Asia and Australia.

The move gives OpenAI an experienced technology executive as competition intensifies among artificial intelligence companies for users, corporate customers, developers and public-sector partnerships. Devanathan has spent more than a decade at Meta and has held senior roles spanning ecommerce, gaming and country leadership across Asia-Pacific.

Devanathan announced her departure from Meta on Friday, describing the decision as “bittersweet” and saying she would take a short break before beginning her next chapter. OpenAI subsequently confirmed that she would join the company in the regional position.

Her departure also reshapes Meta’s reporting structure in one of its largest markets. Arun Srinivas, Meta’s managing director and country head for India, will report directly to Benjamin Joe, the company’s vice-president for Asia-Pacific. Srinivas had been reporting to Devanathan.

Devanathan joined Meta in 2016 and helped build its businesses and teams in Singapore and Vietnam, as well as ecommerce initiatives across Southeast Asia. She moved in 2020 to lead Meta’s gaming business in Asia-Pacific before being appointed vice-president and head of India, taking up that position in January 2023. Her remit was later expanded to include Southeast Asia.

At Meta, her work covered the company’s business and revenue priorities, relationships with major brands, advertisers, creators and partners, and the expansion of digital commerce and messaging services. She has more than 25 years of experience across banking, payments and technology.

OpenAI’s appointment places Devanathan in charge of markets where governments and companies are accelerating investment in generative artificial intelligence while also debating rules on safety, data, copyright and the use of advanced models. Her remit includes regulatory engagement, making her role important to OpenAI’s efforts to navigate differing policy regimes across Southeast Asia and Australia.

The company has been expanding its physical and management presence across Asia-Pacific, with offices in Singapore, Tokyo, Seoul, Sydney and Delhi. It has also strengthened its leadership in India, where it appointed former Uber executive Prabhjeet Singh as managing director earlier this year.

OpenAI has made India a significant part of its regional growth strategy as demand for generative AI tools rises among consumers, developers and businesses. In February, the company launched OpenAI for India, an initiative focused on artificial intelligence infrastructure, enterprise adoption, skills development and education partnerships.

Devanathan’s appointment extends that regional build-out beyond India, giving OpenAI a senior executive responsible for Southeast Asia and Australia from Singapore. The role combines commercial expansion with policy and operational responsibilities rather than focusing solely on sales or partnerships.

For Meta, the leadership change comes as the company continues to manage its advertising, messaging and social-media businesses across the region while increasing investment in artificial intelligence. Devanathan’s departure removes an executive who had overseen both India and Southeast Asia and had been part of Meta’s Asia-Pacific leadership structure.

When Meta appointed Devanathan to lead its India operations in 2022, the company said she would bring together its business and revenue priorities and strengthen relationships with brands, creators, advertisers and partners. She moved back to India for the role after earlier assignments in Singapore and Southeast Asia.

In her departure message, Devanathan highlighted work involving government citizen services delivered through WhatsApp in India and small businesses using Meta’s applications as digital storefronts in Vietnam, Indonesia and Thailand. She also referred to her experience helping technology companies and creators grow across the region.

Figures unveiled at the 2026 China International Big Data Industry Expo in Guiyang, Guizhou province, showed that data-related software products, including AI application software, and data-resource products involving token services generated a combined 4.99 trillion yuan. The two categories accounted for 73.6 per cent of the industry’s total output, underlining the growing commercial connection between data resources and AI development.

The number of data enterprises operating across China reached 482,000 by the end of 2025, an increase of 17.9 per cent from a year earlier. The eastern regions remained the largest concentration of activity, with their data industry valued at about 5.23 trillion yuan.

Growth has accelerated steadily over the past three years. China’s data industry was valued at 5.06 trillion yuan in 2023 and 5.86 trillion yuan in 2024 before climbing above 6.7 trillion yuan last year. Expansion has increasingly shifted from basic data collection and processing towards higher-value services designed for AI models, intelligent agents and industry-specific applications.

High-quality datasets have emerged as a particularly important segment. By August 2026, more than 126,000 such datasets had been established nationwide, containing more than 1,815 petabytes of data. Their combined volume has risen by more than 89 per cent since March, reflecting rapidly expanding demand from developers training and refining AI systems.

The broader supply of digital information is also growing sharply. China generated 52.26 zettabytes of data during 2025, up 27.28 per cent from the previous year and representing roughly 27.4 per cent of global data production. Enterprises accounted for about nine-tenths of the increase, with manufacturing, transport and logistics, software and information technology services recording especially strong gains.

That expansion is occurring alongside rapid growth in AI itself. China’s core AI industry exceeded 1.2 trillion yuan in 2025, with more than 6,200 specialised AI enterprises operating nationwide. More than 30 per cent of large manufacturing enterprises had adopted AI technologies by the end of the year, widening demand for industrial datasets capable of training systems for production, quality inspection, predictive maintenance and automation.

AI development is also changing the composition of the data market. Large language models initially depended heavily on publicly accessible text and image material, but developers are increasingly seeking proprietary industrial, scientific, financial, medical and operational data. The expansion of intelligent agents and embodied AI is adding demand for video, three-dimensional information, sensor readings, physical interaction records and synthetic data.

Intelligent-agent innovation has become another growth area. More than 3,400 patents associated with agent technologies were authorised during 2025, with the pace of growth more than doubling from the previous year. Commercial platforms are simultaneously combining access to multiple AI models with tools that allow companies to select, adapt and deploy systems without developing every component internally.

Policy is increasingly focused on turning China’s vast quantity of information into commercially usable AI resources. A national programme launched this year calls for high-quality industry datasets covering areas including scientific research, manufacturing, agriculture, energy, transport, financial services, healthcare, education, e-commerce, tourism, meteorology, urban governance, autonomous driving, embodied intelligence and biotechnology.

The programme is intended to expand dataset supply, improve annotation and quality assessment, encourage controlled circulation and connect dataset development more closely with practical AI applications. Authorities are targeting significant progress by the end of 2028, including industry datasets tested through real-world applications and specialised companies capable of developing tools and standards around them.