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ISC2 Research Finds AI Is Reshaping Cybersecurity Roles and Increasing Human Oversight

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Cybersecurity professionals reporting higher work-related stress from AI are significantly more likely to spend time validating outputs and deciding when to trust AI recommendations

ALEXANDRIA, Va., July 14, 2026 /PRNewswire/ — ISC2 – the world’s leading nonprofit member organization for cybersecurity professionals – today released findings from its Rethinking AI’s Impact on Cybersecurity Roles report, revealing that artificial intelligence (AI) is reshaping cybersecurity roles, workflows and decision-making while increasing the importance of human judgment, validation and governance. Approximately two-thirds of participants spent more time deciding when to trust or act on AI-generated recommendations (65%) and reviewing or validating AI outputs (63%) over the past year.

Based on a survey of 856 cybersecurity professionals who use AI in their roles, the research shows that while AI is improving efficiency and enabling more strategic work, it is also introducing new risks, increasing accountability pressures and accelerating changes to early-career pathways.

While nearly half of cybersecurity professionals (48%) report that AI has reduced workplace stress, almost one-third (32%) say it has increased stress levels. Those experiencing higher stress are significantly more likely than those with decreased stress to spend additional time deciding when to trust AI-generated recommendations (76% versus 57%) and reviewing or validating AI outputs (74% versus 57%). When AI-recommended actions lead to incorrect outcomes, half of the participants (50%) say their organizations hold human decision-makers ultimately accountable. Nearly 9 out of 10 (89%) respondents report having experienced AI recommendations that lead to incorrect outcomes at their organizations.

The research also finds that many cybersecurity professionals believe AI is changing early-career pathways. While 56% of participants say AI has reduced the need for entry-level roles, 53% believe AI is creating new entry-level opportunities and 48% say AI makes them feel more optimistic about their long-term career prospects.

“AI is not replacing cybersecurity professionals; it is changing what the profession requires of them,” said ISC2 CEO Scott Beale, CC. “As AI takes on more repetitive tasks, as well as performing some complex cybersecurity analysis at speed and scale, cybersecurity roles are shifting toward higher-value work, from asking the right questions to validating findings, interpreting outputs and applying human judgment. This evolution is not limited to entry-level roles. It changes how work is distributed across security teams, making continued investment in governance, validation practices, mentoring and skills development essential at every level.”

Additional findings from the report include:

AI’s impact on work-related stress is mixed. 48% report lowered stress due to AI, while 32% say stress has increased. Those reporting increased stress were significantly more likely than those with decreased stress to have spent more time deciding when to trust or act on AI recommendations (76% versus 57%) and reviewing or validating AI outputs (74% versus 57%).AI raises significant concerns. Top concerns include over-reliance on AI (62%), undetected errors scaling across systems (61%) and reduced human judgment at critical decision points (56%).Accountability remains human-led. When AI-recommended actions lead to incorrect outcomes, half of participants (50%) say their organizations hold human decision-makers ultimately accountable. Another 21% say accountability varies depending on the severity of the issue, while others reported ambiguity (10%) or a lack of clear ownership (8%) when AI recommendations are incorrect.AI is changing how cybersecurity professionals spend their time. Over the past year, nearly half (48%) report spending less time on tasks that do not involve AI, signaling a shift toward AI-assisted workflows. Responses on hands-on work are split: 35% report less time, 32% more time and 33% no change.Foundational cybersecurity skills remain essential. Nearly two-thirds (62%) do not believe that AI has reduced the need for foundational cybersecurity skills, compared to just 26% who say it has.Governance and trust frameworks are critical. Around 4 in 5 say it is very important to establish when to trust AI outputs(82%), knowing when to  override decisions (80%) and having clear governance frameworks in place (80%).

For cybersecurity leaders, hiring managers, workforce development teams and HR professionals navigating how AI is reshaping cybersecurity roles, skills and decision-making, read the full Rethinking AI’s Impact on Cybersecurity Roles report here.

Methodology
The ISC2 2026 Rethinking AI’s Impact on Cybersecurity Roles report is based on responses from 856 cybersecurity professionals who use AI in their roles. Conducted in May 2026, the research explores how AI is influencing time allocation, skills development, entry-level roles, decision-making, risk and workplace stress across the cybersecurity profession.

About ISC2
ISC2 is the world’s leading member organization for cybersecurity professionals, driven by our vision of a safe and secure cyber world. Our more than 265,000 certified members, and associates, are a force for good, safeguarding the way we live. Our award-winning certifications – including cybersecurity’s premier certification, the CISSP® – enable professionals to demonstrate their knowledge, skills and abilities at every stage of their careers. ISC2 strengthens the influence, diversity and vitality of the cybersecurity profession through advocacy, expertise and workforce empowerment that accelerates cyber safety and security in an interconnected world. Our charitable foundation, the Center for Cyber Safety and Education, helps create more access to cyber careers and educates those most vulnerable. Learn more, get involved or become an ISC2 Candidate to build your cyber career at ISC2.org. Connect with us on X, Facebook and LinkedIn.

© 2026 ISC2 Inc., ISC2, CISSP, SSCP, CCSP, CGRC, CSSLP, HCISPP, ISSAP, ISSEP, ISSMP, CC, and CBK are registered marks of ISC2, Inc.

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Beghou Expands Pune Office, Strengthening Data, Analytics, and AI Capabilities

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The expanded office brings together multidisciplinary teams to solve increasingly complex life sciences commercialization challenges 

PUNE, India, Nov. 11, 2026 /PRNewswire/ — Beghou, a life sciences commercialization consulting and technology company, today announced the expansion of its Pune office. Opened on October 7 to foster cross-team collaboration, the new space reflects Beghou’s growing global delivery and innovation model. The Pune office is home to consulting and product teams with expertise spanning analytics, data engineering, technology, and AI. Beghou has also expanded its offices in Hyderabad and Bengaluru this year as its workforce continues to scale. The larger Pune space makes room for that growth, along with expanded leadership opportunities, specialist capabilities, and global client exposure for teams based there. 

“There’s a real sense of momentum at Beghou right now, and it’s exciting to see that reflected in our global expansion. We’re growing across markets, expanding the capabilities we bring to clients, and investing in the people and technology behind that work,” said Adrienne Lovink, CEO, Beghou. 

Commercialization challenges rarely sit within a single discipline, and Beghou’s model is built around that reality. Teams work together to move from identifying a business question to designing, building, and implementing the solution. The new office gives them dedicated space to collaborate, share knowledge, and learn from one another. 

“It is incredibly fulfilling to see the growth of our India organization and the world-class talent and capabilities we have built over the years. I see this growth as a stepping stone to something much bigger – not just scaling, but driving innovation, developing differentiated offerings, and solving increasingly complex commercialization challenges for our clients. Our new office reflects this ambition, bringing together diverse expertise and creating more opportunities for our teams to collaborate, innovate, and build meaningful solutions,” said Sonam Dubey, India Head, Beghou. 

The office is also a key hub for Beghou’s AI and product innovation, with teams working to embed AI in the solutions clients use across planning, analysis, and execution. They are also helping to develop new products that pair Beghou’s commercialization expertise with modern data capabilities. 

“We are at an exciting point in Beghou’s journey. I see this office as a melting pot of deep commercial expertise, technology, product thinking, and AI, the capabilities that will shape our next phase of growth. The opportunity is to combine those strengths to build differentiated solutions that solve real client problems and scale our impact,” said Abhigya Jain, Partner, Beghou. 

About Beghou 

Beghou drives commercialization that works for life sciences. For over 30 years, Beghou has been a long-term consulting and technology partner to more than 250 life sciences clients. We connect the dots between strategy, data, technology, and teams, helping clients accelerate launches, deepen customer engagement, and advance patient access. Whether a company is pre-commercial and building from scratch or refining an existing commercial strategy, Beghou provides fresh ideas and pragmatic, technology-enabled solutions to help organizations adapt and thrive in an increasingly complex environment. 

We build enduring partnerships by remaining engaged and accountable beyond project delivery to help ensure solutions take hold and deliver results. Combining strategic thinking, technical expertise, and hands-on execution, we help clients achieve faster outcomes and lasting impact. 

Find out more at www.beghou.com.

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TIER IV unveils end-to-end autonomous driving adaptable to map information and sensor configurations

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Multiple open-source AI models are available with Autoware

TOKYO, Nov. 11, 2026 /PRNewswire/ — TIER IV, the pioneering force behind Autoware, open-source software for autonomous driving, today announced the development and open-source release of multiple end-to-end (E2E) autonomous driving AI models that support different system requirements, including map information and sensor configurations. The models offer flexible options ranging from camera-only configurations to those incorporating LiDAR, radar and high-definition (HD) maps, enabling developers to select AI models suited to their performance requirements. Through Autoware, TIER IV provides a development environment for optimizing these models and integrating them into vehicle systems, helping automakers and technology partners develop and deploy their own autonomous driving stack.

Overview of the Autoware 2.0 Architecture

TIER IV is leading the development of Autoware 2.0, the next-generation architecture of Autoware. Autoware 2.0 is a scalable and adaptable architecture that flexibly combines AI models with conventional rule-based technologies. By supporting different AI models and sensor configurations, it enables autonomous driving systems to be built for a range of applications and system requirements. The E2E autonomous driving AI models announced today are concrete technological outcomes designed to leverage this architecture.

NVIDIA Alpamayo 2 Edge

As part of its collaboration with NVIDIA announced in March 2026 , TIER IV has been evaluating the performance of NVIDIA Alpamayo, a vision-language-action (VLA) foundation model, and integrating it with Autoware. The latest model, Alpamayo 2 Edge, is an E2E autonomous driving AI model that takes only camera images as input and uses reasoning to generate driving trajectories. With 2 billion parameters, compared with 34 billion in Alpamayo 2 Super, it is substantially smaller and offers promise for practical deployment in vehicles. TIER IV is currently optimizing the model and adapting it to real vehicles, while having completed its integration with Autoware.

GitHub (source code): https://github.com/autowarefoundation/alpamayo-autowareHugging Face (AI model): https://huggingface.co/nvidia/Alpamayo2-Edge

AutoE2E

AutoE2E, whose development is led by the Autoware Foundation (AWF) and TIER IV, is an E2E autonomous driving AI model capable of running on computing platforms beyond NVIDIA hardware. It adopts a Fast–Slow architecture combining a Reactive Model for real-time driving decisions, a World Model for predicting future changes in the surrounding environment, and a Reasoning Model that supports driving decisions. It can accommodate configurations ranging from cameras alone to those incorporating LiDAR and radar sensor data. With 79.9 million parameters, it is lighter than Alpamayo 2 Edge. The Reactive Model has been released, while development of the World Model and Reasoning Model continues, alongside consideration of commercialization for robotaxi applications. Integration of the Reactive Model with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/auto_e2eHugging Face (AI model): https://huggingface.co/AutowareFoundation/auto_e2e

METEOR

Developed independently by TIER IV, METEOR is a lightweight, multitask E2E autonomous driving AI model primarily intended for privately owned passenger vehicles. Built on a convolutional neural network (CNN) architecture, it uses a bird’s-eye-view (BEV) representation to perform everything from perception of the surrounding environment to driving trajectory generation within a single neural network, without relying on high-definition maps. It supports configurations using images from one to eight cameras and can also incorporate LiDAR and radar sensor data. With 16 million parameters, it is even lighter than AutoE2E and supports operation across different semiconductor platforms, including NVIDIA and Renesas. TIER IV also uses CoMET, the automated labeling platform within Co-MLOps, together with agentic AI to automate data labeling and model training, evaluation, and improvement, eliminating the need for manual coding and labeling. Automakers and component suppliers can optimize the open-source model to meet their own vehicle specifications and performance requirements.

GitHub (source code): https://github.com/tier4/METEORHugging Face (AI model): https://huggingface.co/AutowareFoundation/meteor

OnePlanner

OnePlanner is an E2E autonomous driving AI model that integrates perception of the surrounding environment with motion planning. It currently uses BEVFusion, which generates a BEV representation from LiDAR point-cloud data, with a planned transition to PTv3. Its flexible architecture allows the perception model to be replaced while directly using features extracted during perception for motion planning. Conventional autonomous driving systems convert perception results into information such as object positions and velocities before passing them to the planner. OnePlanner reduces these intermediate conversions, enabling richer use of information about the surrounding environment. It also incorporates HD maps, route information, traffic-signal states, and vehicle motion states to generate driving trajectories for the next six seconds. Integration with Autoware has been achieved.

GitHub (source code): https://github.com/autowarefoundation/autoware_oneplannerHugging Face (AI model): https://huggingface.co/AutowareFoundation/oneplanner

LatentDrive

LatentDrive is an E2E autonomous driving AI model that uses a world model to integrate predictions of the surrounding environment with motion planning. Using V-JEPA, a self-supervised learning approach, it represents features of the surrounding environment extracted from camera video in a latent space and uses these features to generate vehicle trajectories. Its distinguishing feature is that it directly leverages information from video for motion planning without intermediate processes such as object detection and tracking. It does not require HD maps and generates trajectories for the next four seconds using camera video, route information, and vehicle motion states. It supports configurations with either one or three cameras, and work is underway on integration with Autoware and validation in an in-vehicle environment.

GitHub (source code): https://github.com/autowarefoundation/autoware_latent_driveHugging Face (AI model): https://huggingface.co/AutowareFoundation/latent_drive

“Advances in E2E autonomous driving are fundamentally changing how autonomous driving systems are developed.” said Shinpei Kato, founder and CEO of TIER IV. “For automakers and component suppliers to incorporate AI technology into their own products, however, it is essential that they be able to internalize technologies according to their applications and performance requirements, without depending on a particular AI model or semiconductor platform. By releasing multiple AI models developed under the leadership of TIER IV and the Autoware Foundation, alongside the results of our collaboration with NVIDIA, we have significantly expanded those choices. We will continue to advance the open-source ecosystem centered on Autoware and work with partners around the world to democratize autonomous driving.”

“Advancing autonomous driving requires AI that can reason through complex situations and run efficiently in the car.” said Ali Kani, vice president of automotive at NVIDIA. “TIER IV’s integration of NVIDIA Alpamayo 2 Edge with Autoware gives developers an open foundation to bring that intelligence from research into their own vehicles.”

“The advancement of autonomous driving technology depends on an ecosystem in which diverse AI models can be developed and evaluated openly, then applied according to their respective use cases.” said Muhammad Zain Khawaja, President of the Autoware Foundation. “The AI models released today are an important demonstration of how Autoware is evolving into a flexible development platform that is not tied to any particular technology or hardware. We welcome TIER IV’s continued technology development and its collaboration with partners including NVIDIA. The Autoware Foundation will continue working with the global open-source community to make advanced autonomous driving technology accessible to everyone.”

Next Steps

TIER IV will continue improving the performance of the AI models released today and optimizing them for in-vehicle environments, while promoting the development and commercialization of E2E autonomous driving technology by automakers and partners through Autoware. TIER IV will also strengthen collaboration with the global open-source community and work to expand the adoption of autonomous driving systems across diverse vehicle types and applications.

About TIER IV

TIER IV stands at the forefront of deep tech innovation, pioneering Autoware, open-source software for autonomous driving. With a comprehensive suite of platforms and services built around Autoware, TIER IV provides everything from software development and vehicle procurement to operational support. Through the Autoware ecosystem, TIER IV works with partners worldwide to shape the future of intelligent vehicles with open-source software, aiming to create mobility that is safer, more sustainable, and accessible to all.

The word marks and logos of TIER IV are trademarks or registered trademarks of TIER IV, Inc. in Japan and other countries. All other company names, product names, service names, and logos referenced herein are trademarks or registered trademarks of their respective owners.

Autoware is a registered trademark of the Autoware Foundation.

Media contact
pr@tier4.jp 

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Dingdong to Report Third Quarter 2026 Financial Results on November 12, 2026

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SHANGHAI, Nov. 10, 2026 /PRNewswire/ — Dingdong (Cayman) Limited (“Dingdong” or the “Company”) (NYSE: DDL), a leading fresh grocery e-commerce company in China, with advanced supply chain capabilities, today announced that it will report its unaudited financial results for the third quarter ended September 30, 2026, before U.S. markets open on November 12, 2026.

About Dingdong (Cayman) Limited

Dingdong is the leading fresh grocery e-commerce company in mainland China, with sustainable long-term growth. The Company directly provides users and households with fresh groceries, prepared food, and other food products through delivering a convenient and excellent shopping experience supported by an extensive self-operated frontline fulfillment grid. Leveraging its deep insights into consumers’ evolving needs and its strong food innovation capabilities, Dingdong has successfully launched a series of private label products spanning a variety of food categories. Many of Dingdong’s private label products are produced at its own production plants, allowing it to more efficiently produce and offer safe and high-quality food products. Dingdong aims to be the first choice for fresh and food shopping.

For more information, please visit: https://ir.100.me.

 

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