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TELUS Mental Health Index: 44 per cent of workers feel exhausted after work; excessive workload is the leading cause of burnout

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2 years ago

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Study also shows 31 per cent of workers believe that AI will have a positive impact on their industry

LONDON, June 12, 2024 /PRNewswire/ — Today, TELUS Health released its TELUS Mental Health Index (“the Index”) with reports that examine the mental health of employed people in the United Kingdom, the United States, Canada, Europe, Singapore, New Zealand and Australia. The UK report reveals that 44 per cent of workers feel mentally and/or physically exhausted at the end of their workday, with too much work cited as the top cause of burnout. The Index also found that 31 per cent of workers believe that Artificial Intelligence (AI) will have a positive impact on their industry.

“There is no question that AI’s advancement will bring significant benefits, potentially as pivotal as the industrial or internet age,” said Paula Allen, Global Leader, Research & Client Insights, TELUS Health. “Organizations have the opportunity to engage employees in this evolution by ensuring that AI tools and training are readily accessible to employees, and enabling them to explore the technology firsthand so they can discover the ways it benefits them in their own work. As with any change, the best way to implement change is to engage people from the start, empowering them to grasp the possibilities and contribute valuable insights.”

The TELUS Mental Health Index also found:

Thirteen per cent of workers are considering upgrading their AI skills.Managers and younger workers are three times as likely as non managers and workers over 50 to be considering upgrading their skills related to the use of AI.Parents are nearly three times as likely as non-parents to consider upgrading their AI skills.Half of workers believe that AI will have a positive impact on healthcare.Workers under 40 are 70 per cent more likely than workers over 50 to find it increasingly difficult to be motivated to do their work.

As a leader in technology, TELUS is at the forefront of integrating and scaling AI and generative technologies across its business operations, team members and customer interactions. By fostering a culture of innovation and continuous learning, TELUS empowers its team members to adopt and experiment with its internal AI tools in a safe and secure environment, free from the fear of making mistakes. TELUS is committed to developing a skilled, AI-enabled workforce to fully harness the potential of AI-powered innovation and growth.

“We see a clear opportunity for employers to help extend the openness that younger employees are demonstrating towards leveraging AI compared to other colleagues who might be later adopters or initially hesitant to learn to use AI,” said Philip Mullen, Vice President EMEA, TELUS Health. “By proactively addressing what their teams need to embrace the AI evolution and feel equipped to do so, they can act as an enabler for employee empowerment and ensure that their teams are equipped and ready to thrive in a future where AI is an integral part of our working lives.”

While many workplaces offer Employee Assistance Programs (EAP) that could help support employees in this situation, TELUS Health research reveals that 68 per cent of workers are unsure whether or not their employer offers an EAP. The mental health scores of workers who don’t know or report that their employer doesn’t offer an EAP is at least three points lower than workers with an EAP.

In April 2024, the mental health scores of workers in various regions were:

United States: 71.0United Kingdom: 64.6Canada: 64.0Australia: 62.5Singapore: 62.9Europe: 62.0New Zealand: 60.6

The TELUS Mental Health Index is based on a response scoring system that turns individual responses into point values. Higher point values are associated with better mental health and less mental health risk. Scores between 0 to 49 correspond with distress levels, scores between 50 to 79 correspond with strain levels and scores between 80 to 100 correspond with optimal levels of mental health.

The June TELUS Mental Health Index also includes insights related to workplace productivity and motivation in addition to burnout levels and causes. Read the full UK TELUS Mental Health Index here.

About the TELUS Mental Health Index
The data for the TELUS Health Mental Health Index was collected through an online survey from April 5, 2024 to April 15, 2024 with 2,000 respondents. All respondents reside in the United Kingdom and were employed within the last six months. The data has been statistically weighted to ensure the regional and gender composition of the sample reflects this population.

About TELUS Health
TELUS Health is on a mission to become the most trusted wellbeing company in the world by enhancing the overall efficiency of healthcare and championing workplace wellbeing. By integrating advanced healthcare technology with comprehensive employee support services, TELUS Health provides a holistic approach to primary and preventive health and wellbeing for 72 million people across 160 countries. Our innovative digital health platforms, including electronic medical records (EMRs) and virtual care solutions, empower healthcare professionals, individuals, employers and governments to deliver personalized care efficiently. Our employee wellbeing programs offer extensive support through Employee Assistance Programs (EAPs), mental health resources, financial counselling, and workplace wellness initiatives. At TELUS Health, we are committed to revolutionizing healthcare to ensure people receive the support they need and employees thrive both personally and professionally. Together, let’s make the future friendly. For more information, visit: www.telushealth.com.

Media Contact:
Hanover Communications
Email: telushealth@hanovercomms.com

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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39 minutes ago

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July 24, 2026

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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Video: CNPC offers green chemical answer

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39 minutes ago

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July 24, 2026

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

View original content to download multimedia:https://www.prnewswire.com/apac/news-releases/video-cnpc-offers-green-chemical-answer-302834036.html

SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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39 minutes ago

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July 24, 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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