Latest news with #AgentOS
Geeky Gadgets
01-08-2025
- Geeky Gadgets
Agent OS : AI Operating System That Adapts to Your Coding Style
What if your software development process could think, adapt, and evolve alongside you? Imagine an operating system not for your computer, but for your AI agents—one that understands your coding style, integrates seamlessly with your tools, and automates the tedious parts of development. Bold claim? Perhaps. But the Agent OS framework is making this a reality, redefining how developers interact with AI. By bridging the gap between human creativity and machine precision, it offers a dynamic, customizable environment that transforms the way we approach coding, project management, and workflow optimization. AI Labs uncovers how Agent OS enables developers to work smarter, not harder. From its AI adaptation capabilities to its robust project management tools, this framework is designed to align with your unique coding practices while maintaining consistency and precision. You'll discover how it simplifies feature implementation, minimizes errors, and even integrates with existing codebases—all while enhancing productivity. Whether you're curious about its hybrid tool integration or intrigued by its ability to automate repetitive tasks, Agent OS promises to reshape your development experience in ways you might not expect. So, what does it mean for an AI to truly collaborate with you? Let's find out. Agent OS Overview Core Features of Agent OS Agent OS is engineered to address the diverse needs of developers, offering a suite of features that enhance productivity, adaptability, and consistency. At its foundation, the framework emphasizes AI adaptation, allowing agents to learn and align with your coding standards and preferences. This ensures seamless collaboration between developers and AI, creating a cohesive development environment. Key features include: AI Adaptation: Agents dynamically learn and align with your coding practices, making sure smooth integration into your workflow. Agents dynamically learn and align with your coding practices, making sure smooth integration into your workflow. Customizable Base Rules: Define coding standards and tech stack preferences to maintain consistency across projects. Define coding standards and tech stack preferences to maintain consistency across projects. Hybrid Tool Integration: Use the strengths of platforms like Claude Code and Cursor to create a more efficient and unified workflow. This adaptability ensures that Agent OS can seamlessly integrate into your unique development environment, regardless of the tools, methodologies, or coding practices you prefer. Streamlined Installation and Setup Agent OS simplifies the onboarding process with an efficient two-step installation system. First, you install the base framework, which serves as the foundation for the operating system. Next, you configure tool-specific settings to tailor the system to your specific needs. This streamlined approach minimizes setup time, allowing you to focus on development rather than troubleshooting configurations. The framework's intuitive commands make installation and customization straightforward. Even semi-technical users can quickly get up and running without unnecessary delays. By reducing the complexity of setup, Agent OS ensures that developers can immediately begin using its capabilities. Agent OS Framework Replaces 95% of AI Coding Watch this video on YouTube. Browse through more resources below from our in-depth content covering more areas on AI coding. Customization to Match Your Workflow Customization is a cornerstone of Agent OS, allowing developers to align the framework with their preferred tools, practices, and methodologies. By defining base rules that reflect your coding style and tech stack, you can ensure consistency across all projects. Additionally, project-specific configurations allow for tailored adjustments to meet unique requirements, making the framework highly versatile. Key customization features include: Project-Specific Configurations: Adjust settings to meet the unique demands of individual projects. Adjust settings to meet the unique demands of individual projects. Streamlined Commands: Use intuitive commands like `plan product` and `create spec` to simplify project setup and execution. Use intuitive commands like `plan product` and `create spec` to simplify project setup and execution. Workflow Automation: Automate repetitive tasks, freeing up time for higher-level development and problem-solving. Whether you are starting a new project or resuming an existing one, Agent OS ensures a smooth and efficient workflow tailored to your specific needs. Enhanced Project Management Tools Agent OS excels in project management by providing tools that help developers stay organized, track progress, and maintain alignment with project goals. The framework generates structured project files that include roadmaps, missions, and tech stack details, offering a clear and actionable overview of your development process. Highlights of its project management capabilities include: Roadmap Generation: Create detailed, actionable plans to guide your projects from start to finish. Create detailed, actionable plans to guide your projects from start to finish. Progress Tracking: Monitor milestones and ensure alignment with your objectives. Monitor milestones and ensure alignment with your objectives. Standards Enforcement: Maintain consistent application of coding preferences and best practices across all stages of development. This structured approach ensures that your projects remain on track, organized, and aligned with your coding standards, reducing the risk of errors or mismanagement. Seamless Feature Implementation Agent OS simplifies the process of adding or modifying features within your projects. The framework supports both step-by-step and one-shot implementations, giving you the flexibility to choose the method that best suits your workflow. Commands are designed to efficiently apply themes and styling, reducing the likelihood of errors and making sure consistency across your codebase. This flexibility allows developers to adapt their approach based on the complexity of the task at hand, making sure that feature implementation is both efficient and precise. Integration with Existing Codebases Agent OS is not limited to new projects; it is equally effective when integrated with pre-existing codebases. Using the `analyze product` command, the framework evaluates your current project, identifying its development phase and adapting accordingly. This ensures that you can use the benefits of Agent OS without disrupting ongoing work or requiring extensive reconfiguration. By seamlessly integrating with existing projects, Agent OS provides a versatile solution for developers looking to enhance their workflows without starting from scratch. Minimizing Errors and Maximizing Productivity Error reduction is a central focus of Agent OS, with features designed to maintain high-quality standards throughout the development process. By efficiently applying coding themes and styles, the framework minimizes the likelihood of mistakes, helping you deliver reliable and polished software. Additionally, tools for task resumption allow you to pick up where you left off, making sure continuity and reducing downtime. Key benefits include: Error Reduction: Consistent coding practices help maintain high-quality standards and reduce the risk of mistakes. Consistent coding practices help maintain high-quality standards and reduce the risk of mistakes. Task Resumption: Seamlessly continue workflows without losing momentum, enhancing overall productivity. These features ensure that your development process remains efficient, reliable, and focused on delivering high-quality results. Optimizing Development with Agent OS Agent OS represents a significant advancement in AI-driven software development. By combining AI adaptation, customizable coding standards, and seamless tool integration, it simplifies complex tasks while maintaining precision and efficiency. Whether you are starting a new project or integrating with an existing one, Agent OS provides the tools and flexibility needed to optimize your development process. With its emphasis on adaptability, productivity, and error minimization, Agent OS is a valuable asset for developers seeking to streamline their workflows and deliver high-quality software. Its innovative approach to project management, feature implementation, and customization ensures that developers can focus on what matters most: creating exceptional software solutions. Media Credit: AI LABS Filed Under: AI, Top News Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Yahoo
30-07-2025
- Automotive
- Yahoo
Accelerating the Evolution of Automotive Embodied Intelligence, Geely Auto Group Teams Up with StepFun for a Joint Showcase at the 2025 World Artificial Intelligence Conference
Hangzhou, China, July 30, 2025 (GLOBE NEWSWIRE) -- On July 26, Geely Auto Group partnered with its strategic tech ecosystem partner, StepFun, to jointly exhibit at the 2025 World Artificial Intelligence Conference (WAIC 2025). Geely showcased a suite of new products, including the Zeekr 9X, LYNK & CO 10 EM-P, Geely Galaxy A7, and Geely Galaxy M9. Also on display were the fruits of Geely's 'Full-Domain AI' technology system, such as the Qianli Haohan intelligent driver-assistance system, the Geely Future Mobility Constellation, and AI-powered wearable devices. Highlighting the showcase was the Geely Galaxy M9, featuring the industry's first Human-like AI agent for Vehicles. This agent leverages StepFun's end-to-end AI voice large model, marking a significant revolution in human-machine interaction. Furthermore, Geely's Zeekr 009, serving as the official vehicle partner for this year's WAIC, garnered widespread acclaim and enthusiastic praise from conference the event, StepFun revealed its latest foundational large model, Step 3. Additionally, together with Qianli Technology and Geely Auto Group, StepFun launched the next-generation smart cockpit Agent OS (Preview Version). Tailored for AI Agent-native applications, this innovation promises users a cockpit interaction experience that feels more natural, human-like, and emotionally engaging. Switch Auto Insurance and Save Today! Affordable Auto Insurance, Customized for You Great Rates and Award-Winning Service The Insurance Savings You Expect Partnering with StepFun to Revolutionize Intelligent Interaction Experiences, Geely Galaxy M9 Debuted the world's first Human-like AI agent for Vehicles StepFun is a strategic tech ecosystem partner of Geely Auto Group and one of its five AI ecosystem partners. Together, they have achieved a series of breakthroughs in multimodal large models, intelligent driving, and cockpit technologies. Back in February, StepFun and Geely Auto Group jointly announced the open-sourcing of two co-developed Step series multimodal large models for global developers. Now, the Geely Galaxy M9, Geely's all-new 'AI Tech Grand Six-Seater Flagship SUV,' has globally debuted an Human-like AI agent for Vehicles. This agent is equipped with StepFun's 'end-to-end AI voice large model,' enabling groundbreaking, ultra-natural emotional voice interactions. Powered by human-like emotional computing, it delivers more natural voice performance and speech segmentation. Its conversational emotions and spoken style are richer, and it can dynamically adjust its tone and manner based on the user's emotional state and semantic intent. It can also provide proactive care and companionship. During the WAIC 2025, Qianli Technology partnered with StepFun and Geely Auto Group to jointly launch the next-generation intelligent cockpit operating system, Agent OS (Preview Version), specifically designed for native AI Agent applications. Powered by StepFun's industry-leading multimodal large models and end-to-end voice large models, it features key capabilities such as multimodal fusion for ultra-natural interaction, integrated cloud-edge memory, human-machine co-piloting based on fully integrated maps, and a third living space. This promises users a more natural, human-like, and emotionally engaging cockpit interaction experience. Furthermore, just before the opening of the 2025 WAIC, StepFun also unveiled its latest foundational large model, Step 3. Based on Step 3, StepFun and Geely are set to deepen their partnership, jointly propelling a comprehensive upgrade in automotive intelligence experiences. The World's Only Automaker with Full-domain AI Coverage, Geely is Leading the Development of Cars Towards Embodied Intelligence The era of embodied intelligence is dawning swiftly, driven by the rapid advancement of AI technology. Leveraging a robust technological foundation and an intelligent ecosystem, Geely is leading the development of cars towards embodied intelligence. Looking ahead, it even aspires to become the world's largest robotics entered the AI field early and has achieved rapid development. As early as 2021, the company unveiled its 'Intelligent Geely 2025' strategy, aiming to build an 'intelligent technology ecosystem network' by leveraging cutting-edge infrastructure like high computing power, big data, large models, and satellite constellations, thereby establishing a solid technological foundation. Building on this, in January 2025, Geely officially launched the industry's first 'Full-domain AI for Intelligent Vehicles' technology system. This system not only widely applies AI across the entire vehicle domain including architecture, powertrain, chassis, and cockpit, but also integrates it deeply into the full value chain, encompassing product R&D, manufacturing, and after-sales service. This milestone positions Geely as the only automaker globally to have completed this comprehensive 'Full-domain AI' layout. As competition in the automotive industry shifts from 'breakthroughs in single technologies' to 'ecosystem synergy and efficiency,' Geely is collaborating with technological ecosystem partners like StepFun and Qianli Technology to create a benchmark for 'AI + Car' technological cooperation. They are engaging in comprehensive collaboration in areas such as model optimization, product definition, and software and hardware development, building a full-chain, all-encompassing collaborative innovation system. Computing power, algorithms, and data are the 'three core engines' of AI, and Geely has achieved comprehensive leadership in all these areas. In terms of computing power, Geely, together with its technological ecosystem partners like StepFun, Qianli Technology, DreamSmart, and Geespace, has established the world's only 'Intelligent Vehicle Compute Alliance'—the Xingrui Intelligent Data Center 2.0. With a combined computing power of 23.5 EFLOPS, it firmly holds the top spot among Chinese automakers. On the algorithm front, Geely's Xingrui AI large model system has achieved deep integration with multimodal large models like StepFun's. In terms of data, Geely has accumulated 10 trillion tokenized data points and 40 billion pieces of vertical automotive data, providing the core 'fuel' for large model training and significantly raising the upper limit of their 'cognitive capabilities.'Powered by the strong impetus from these three core AI engines, Geely has harnessed AI technologies like end-to-end learning, VLA (Vehicle Learning Architecture), and world models to launch the Qianli Haohan intelligent driver-assistance system. This system delivers a fully-scenario-safe intelligent mobility experience to users. According to CHEN Qi, Chief Scientist of Autonomous Driving at Geely Holding Group and Vice President of Zeekr Technology Group, in the fourth quarter of this year, Qianli Haohan will implement a brand-new L3-oriented technical architecture, a cloud-based WM+ foundational large model, and an in-vehicle VLA+ end-to-end adversarial safety model. These advancements will enable AI to train AI and AI to verify AI. Currently, Geely has become the automaker with the widest adoption of AI agents integrated into vehicles and the pioneer automaker in AI-powered vehicle manufacturing. The technological achievements of Geely's all-domain AI technologies, such as the Qianli Haohan intelligent driver-assistance system in the driving domain, the Thunderbolt AI Hybrid 2.0 in the powertrain domain, the AI Digital Chassis in the chassis domain, and the AI Intelligent Architecture in the platform domain, are all in mass production. These innovations deliver an unprecedented intelligent and safe mobility experience to users. LI Chuanhai, Vice President of Geely Auto Group and Director of the Geely Automotive Research Institute, stated, 'Geely entered the AI field early, developed rapidly. Our AI technologies have been widely applied and undergone significant transformation. We are not only the fastest company to transition traditional cars towards embodied intelligence but are also committed to guiding AI to become a powerful tool for human progress. In the next phase, Geely will build a technical architecture focused on 'interaction faster + thinking deeper,' evolving AI from a mere execution tool into an intelligent assistant capable of handling complex tasks. At that point, every Geely vehicle will become a physical connection point, helping users tap into the vast AI universe. Geely also aspires to transform from an automaker into China's, and potentially the world's, largest robotics company.' CONTACT: Mengjia Lv in to access your portfolio
Business Upturn
30-07-2025
- Automotive
- Business Upturn
Accelerating the Evolution of Automotive Embodied Intelligence, Geely Auto Group Teams Up with StepFun for a Joint Showcase at the 2025 World Artificial Intelligence Conference
Hangzhou, China, July 30, 2025 (GLOBE NEWSWIRE) — On July 26, Geely Auto Group partnered with its strategic tech ecosystem partner, StepFun, to jointly exhibit at the 2025 World Artificial Intelligence Conference (WAIC 2025). Geely showcased a suite of new products, including the Zeekr 9X, LYNK & CO 10 EM-P, Geely Galaxy A7, and Geely Galaxy M9. Also on display were the fruits of Geely's 'Full-Domain AI' technology system, such as the Qianli Haohan intelligent driver-assistance system, the Geely Future Mobility Constellation, and AI-powered wearable devices. Highlighting the showcase was the Geely Galaxy M9, featuring the industry's first Human-like AI agent for Vehicles. This agent leverages StepFun's end-to-end AI voice large model, marking a significant revolution in human-machine interaction. Furthermore, Geely's Zeekr 009, serving as the official vehicle partner for this year's WAIC, garnered widespread acclaim and enthusiastic praise from conference attendees. During the event, StepFun revealed its latest foundational large model, Step 3. Additionally, together with Qianli Technology and Geely Auto Group, StepFun launched the next-generation smart cockpit Agent OS (Preview Version). Tailored for AI Agent-native applications, this innovation promises users a cockpit interaction experience that feels more natural, human-like, and emotionally engaging. Partnering with StepFun to Revolutionize Intelligent Interaction Experiences, Geely Galaxy M9 Debuted the world's first Human-like AI agent for Vehicles StepFun is a strategic tech ecosystem partner of Geely Auto Group and one of its five AI ecosystem partners. Together, they have achieved a series of breakthroughs in multimodal large models, intelligent driving, and cockpit technologies. Back in February, StepFun and Geely Auto Group jointly announced the open-sourcing of two co-developed Step series multimodal large models for global developers. Now, the Geely Galaxy M9, Geely's all-new 'AI Tech Grand Six-Seater Flagship SUV,' has globally debuted an Human-like AI agent for Vehicles. This agent is equipped with StepFun's 'end-to-end AI voice large model,' enabling groundbreaking, ultra-natural emotional voice interactions. Powered by human-like emotional computing, it delivers more natural voice performance and speech segmentation. Its conversational emotions and spoken style are richer, and it can dynamically adjust its tone and manner based on the user's emotional state and semantic intent. It can also provide proactive care and companionship. During the WAIC 2025, Qianli Technology partnered with StepFun and Geely Auto Group to jointly launch the next-generation intelligent cockpit operating system, Agent OS (Preview Version), specifically designed for native AI Agent applications. Powered by StepFun's industry-leading multimodal large models and end-to-end voice large models, it features key capabilities such as multimodal fusion for ultra-natural interaction, integrated cloud-edge memory, human-machine co-piloting based on fully integrated maps, and a third living space. This promises users a more natural, human-like, and emotionally engaging cockpit interaction experience. Furthermore, just before the opening of the 2025 WAIC, StepFun also unveiled its latest foundational large model, Step 3. Based on Step 3, StepFun and Geely are set to deepen their partnership, jointly propelling a comprehensive upgrade in automotive intelligence experiences. The World's Only Automaker with Full-domain AI Coverage, Geely is Leading the Development of Cars Towards Embodied Intelligence The era of embodied intelligence is dawning swiftly, driven by the rapid advancement of AI technology. Leveraging a robust technological foundation and an intelligent ecosystem, Geely is leading the development of cars towards embodied intelligence. Looking ahead, it even aspires to become the world's largest robotics company. Geely entered the AI field early and has achieved rapid development. As early as 2021, the company unveiled its 'Intelligent Geely 2025' strategy, aiming to build an 'intelligent technology ecosystem network' by leveraging cutting-edge infrastructure like high computing power, big data, large models, and satellite constellations, thereby establishing a solid technological foundation. Building on this, in January 2025, Geely officially launched the industry's first 'Full-domain AI for Intelligent Vehicles' technology system. This system not only widely applies AI across the entire vehicle domain including architecture, powertrain, chassis, and cockpit, but also integrates it deeply into the full value chain, encompassing product R&D, manufacturing, and after-sales service. This milestone positions Geely as the only automaker globally to have completed this comprehensive 'Full-domain AI' layout. As competition in the automotive industry shifts from 'breakthroughs in single technologies' to 'ecosystem synergy and efficiency,' Geely is collaborating with technological ecosystem partners like StepFun and Qianli Technology to create a benchmark for 'AI + Car' technological cooperation. They are engaging in comprehensive collaboration in areas such as model optimization, product definition, and software and hardware development, building a full-chain, all-encompassing collaborative innovation system. Computing power, algorithms, and data are the 'three core engines' of AI, and Geely has achieved comprehensive leadership in all these areas. In terms of computing power, Geely, together with its technological ecosystem partners like StepFun, Qianli Technology, DreamSmart, and Geespace, has established the world's only 'Intelligent Vehicle Compute Alliance'—the Xingrui Intelligent Data Center 2.0. With a combined computing power of 23.5 EFLOPS, it firmly holds the top spot among Chinese automakers. On the algorithm front, Geely's Xingrui AI large model system has achieved deep integration with multimodal large models like StepFun's. In terms of data, Geely has accumulated 10 trillion tokenized data points and 40 billion pieces of vertical automotive data, providing the core 'fuel' for large model training and significantly raising the upper limit of their 'cognitive capabilities.' Powered by the strong impetus from these three core AI engines, Geely has harnessed AI technologies like end-to-end learning, VLA (Vehicle Learning Architecture), and world models to launch the Qianli Haohan intelligent driver-assistance system. This system delivers a fully-scenario-safe intelligent mobility experience to users. According to CHEN Qi, Chief Scientist of Autonomous Driving at Geely Holding Group and Vice President of Zeekr Technology Group, in the fourth quarter of this year, Qianli Haohan will implement a brand-new L3-oriented technical architecture, a cloud-based WM+ foundational large model, and an in-vehicle VLA+ end-to-end adversarial safety model. These advancements will enable AI to train AI and AI to verify AI. Currently, Geely has become the automaker with the widest adoption of AI agents integrated into vehicles and the pioneer automaker in AI-powered vehicle manufacturing. The technological achievements of Geely's all-domain AI technologies, such as the Qianli Haohan intelligent driver-assistance system in the driving domain, the Thunderbolt AI Hybrid 2.0 in the powertrain domain, the AI Digital Chassis in the chassis domain, and the AI Intelligent Architecture in the platform domain, are all in mass production. These innovations deliver an unprecedented intelligent and safe mobility experience to users. LI Chuanhai, Vice President of Geely Auto Group and Director of the Geely Automotive Research Institute, stated, 'Geely entered the AI field early, developed rapidly. Our AI technologies have been widely applied and undergone significant transformation. We are not only the fastest company to transition traditional cars towards embodied intelligence but are also committed to guiding AI to become a powerful tool for human progress. In the next phase, Geely will build a technical architecture focused on 'interaction faster + thinking deeper,' evolving AI from a mere execution tool into an intelligent assistant capable of handling complex tasks. At that point, every Geely vehicle will become a physical connection point, helping users tap into the vast AI universe. Geely also aspires to transform from an automaker into China's, and potentially the world's, largest robotics company.' Disclaimer: The above press release comes to you under an arrangement with GlobeNewswire. Business Upturn takes no editorial responsibility for the same. Ahmedabad Plane Crash
Yahoo
10-06-2025
- Business
- Yahoo
Meet 10 AI trailblazers who are steering their companies into tech's new age
The corporate rush to adopt AI is shifting into high gear. As of July 2024, 78% of companies reported using AI for at least one business task, up from 55% since late 2023, according to a report from McKinsey & Company. From IT automation to personalized marketing, businesses are betting on AI to cut costs and drive growth. But AI adoption isn't without risks, including cybersecurity threats, data leaks, unreliable or biased model outputs, and a rising carbon footprint. For Business Insider's "AI in Action" series, we profiled 10 executives driving AI adoption at companies like JPMorgan Chase, PwC, and BMW. From chief AI officers to HR leaders, they're helping their organizations stay competitive — and safe — in the age of AI. At JPMorgan Chase, Teresa Heitsenrether leads the rollout of the bank's proprietary LLM Suite. The suite has given over 220,000 employees access to AI tools that can summarize internal data. The platform integrates capabilities from multiple leading AI providers and has already saved employees several hours of work a week, Heitsenrether said. "LLM Suite's widespread adoption is driving a cultural transformation across the bank," Heitsenrether told Business Insider. This rollout isn't just about experimentation — it's about execution. JPMorgan tracks every AI use case from ideation to production, ensuring each AI initiative drives business value. That includes cost savings, revenue generation, and risk reduction, Heitsenrether said. Working under this framework helps the bank prioritize projects with the highest potential impact. Additionally, employees across the bank are trained through a mix of in-person and online courses to use AI effectively and responsibly. Joe Atkinson is embedding AI across the firm's operations and services. He led the launch of an internal AI chatbot deployed to 270,000 employees to help them generate reports and assist in project delivery. Under his leadership, PwC also rolled out tools like Code Intelligence, which helps organizations modernize legacy systems through generative AI-powered code conversion, and Agent OS, which was designed to streamline AI-driven workflows. Additionally, Atkinson said he launched a global AI Academy, which has trained 90% of staff in prompt design and responsible AI use. "We're seeing a ton of growth and capability from our people," Atkinson said, pointing to rising usage and more complex tasks handled by AI. He emphasized the importance of trust, governance, and accountability, adding that virtually every function at PwC is expected to be AI-powered in the near future. Bala Subramanian is leading UPS's digital transformation with a focus on integrating AI across operations. Under his leadership, UPS has implemented the Message Response Automation system, which uses large language models to automate responses to customer inquiries and reduce agent handling time. "By alleviating the burden on our human agents, it enables them to focus on more complex and nuanced customer needs," Subramanian told Beyond customer service, Subramanian is overseeing the rollout of AI and automation technologies — like pick-and-place systems and autonomous guided vehicles — across shipment operations. Bloomberg reported that as of April, UPS is exploring a potential partnership with Figure AI, a robotics startup, to implement humanoid robots into its operations for tasks like sorting parcels. UPS is also investing in AI infrastructure, signing a decade-long deal with NTT Data in late March to modernize its data centers — part of a broader strategy to update its logistics network and improve service delivery. UPS didn't respond to BI's request for comment. Johan Gerber is helping Mastercard use AI to strengthen fraud detection across its global payment network. His team oversees cybersecurity, digital identity, and dispute resolution in an effort to protect businesses and card users from scams. With Gerber at the helm, Mastercard launched tools like Decision Intelligence and Safety Net, which use generative AI, machine learning, and data scanning to analyze transaction patterns, improve fraud detection rates, and flag suspicious activity. LLMs have also been integrated into MasterCard's Recorded Future tool, which allows analysts to quickly sift through its threat-intelligence database with queries like, "Tell me about the new malware families you found yesterday." Gerber told BI that combining generative and traditional AI has improved detection accuracy, but he also stressed the importance of rigorous testing and data governance before deploying models into production. He also recommended a method called "silent scoring," which runs new AI models alongside active models before they go live; this helps assess the new model's soundness and vulnerabilities. Suresh Kumar is leading Walmart's AI transformation to boost efficiency and personalize retail experiences. He helped launch "My Assistant," a generative AI tool that helps over 50,000 corporate employees summarize documents, draft content, and streamline onboarding. The company has also invested in developing proprietary LLMs like "Wallaby," trained on decades of internal data, to power customer-facing assistants and personalized homepages. In supply chain operations, Walmart uses AI for product placement, inventory management, and robotic automation. The Wall Street Journal reported that the company is testing autonomous shopping agents that can purchase items for customers. "A standard search bar is no longer the fastest path to purchase, rather we must use technology to adapt to customers' individual preferences and needs," Kumar said in an October press release. Walmart didn't respond to BI's request for comment. Marco Görgmaier is leading BMW's AI integration across production, engineering, and marketing. He said the company's generative AI strategy centers on three pillars: adopting third-party tools, building proprietary applications, and providing in-house tools like the BMW Group AI Assistant, which lets staff create custom software without code. Görgmaier said training programs, development guidelines, and hands-on support further ensure teams are equipped to navigate the AI shift. "While conventional AI has driven efficiencies in targeted areas like predictive maintenance and quality assurance, generative AI expands the horizon, enabling automation, creativity, and innovation across the entire organization," Görgmaier told BI. He said it's important to start every AI project with a clear business need and ensure cross-functional collaboration and compliance. A key to scaling AI, he added, is a centralized, flexible data platform that supports rapid adoption of new technologies while ensuring cost efficiency and regulatory compliance. Bhavesh Dayalji is guiding efforts to boost productivity through internal generative AI tools at S&P and Kensho, S&P's AI and innovation research division. Spark Assist, for example, is an internal chatbot that helps more than 40,000 employees draft reports, synthesize data, and streamline workflows. Unlike public tools like OpenAI's ChatGPT, these are built on proprietary data and include agentic features for task automation. Another tool is Chat IQ, a chatbot where employees can query S&P's financial datasets with questions like, "What is the price of a certain stock?" To ensure widespread AI adoption, Dayalji introduced S&P's workforce to mandatory training, which included online videos and workshops, designed to upskill leaders and employees. "This is a transformation journey," Dayalji told BI. "We want people to have hands-on experience and understand how it's going to help them." Dayalji said S&P will continue placing big bets on AI: Kensho, for instance, is developing a Grounding Agent for autonomous research and analysis using the firm's proprietary datasets. While AI is still in its "early days," Dayalji called the current moment an "amazing time to be involved" in adopting and advancing the technology. Ulrika Biesèrt is helping Ingka Group equip IKEA's global workforce — over 160,000 employees across 31 countries — with AI skills. Since launching AI literacy programs in April 2024, the retailer has trained over 4,000 employees in areas like responsible, ethical AI usage, Biesèrt said. The goal, she added, was to train 30,000 employees and 500 leaders. "At IKEA, we've always believed that change should start with people," Biesèrt told BI. One tool employees are taught to use is Hej Copilot, an internal generative AI assistant that helps with everyday tasks like creating presentations and brainstorming ideas. To inspire their colleagues, early adopters shared use cases for the tool at workshops. Implementing such a vast program isn't easy. Technological change comes with uncertainty, Biesèrt said. To address this, nearly 650 senior leaders were trained, exceeding IKEA's initial goal, to ensure a "structured, cohesive approach" to AI across the organization, Biesèrt told BI. Arnab Chakraborty oversees Accenture's internal responsible AI compliance program to ensure AI is developed, deployed, and scaled sensibly across Accenture and its roster of more than 9,000 global clients. According to the company, Accenture has committed $3 billion over three years to expand its Data & AI practice and double its AI talent to 80,000 professionals. "We have to ensure that AI solutions have fairness, transparency, and accountability embedded from the start," Chakraborty said. He's also co-leading a $700 million partnership with Telstra. The goal is to help the Australian telecommunications company integrate AI into its workflow processes, including identifying fiber cable defects and faster customer service, AFR reported. Chakraborty told BI the partnership also involves advancing responsible AI capabilities like real-time model monitoring so that Telstra's AI systems are compliant with its internal policies and community guidelines. Building and maintaining the right data infrastructure to scale AI remains a barrier to adoption, Chakraborty added. To address this, Accenture has partnered with the Center for Advanced AI in Mountain View, California, gaining access to research labs at academic institutions like UC Berkeley and Stanford to study data privacy and develop AI training programs for companies. Chakraborty said by year's end, Accenture plans to launch over 100 agentic AI tools designed to detect and correct algorithmic issues, such as biases or hallucinations, before they impact business operations. Boris Gamazaychikov leads Salesforce's push to decarbonize the company's AI systems. Recognizing the significant energy demands of training large AI models, Gamazaychikov's sustainability strategy emphasizes the importance of developing efficient, domain-specific models. Salesforce's AI Research team has created xGen, designed for customer relationship management, orCRM, tasks like generating call summaries. These models consume less power and emit fewer emissions than general-purpose ones, according to Salesforce. Under Gamazaychikov's leadership, the CRM provider has introduced AI tools that help customers decarbonize, including AI agents for sustainability measurement and a nature-focused accelerator for climate-focused nonprofits supporting forest conservation, regenerative agriculture, and other efforts. "It is important that software and AI companies are also part of the solution to reduce emissions, and provide tools that help others reduce their emissions," Gamazaychikov said in an interview for Autonomy's "The Decarbonists" newsletter. Salesforce didn't respond to BI's request for comment. Read the original article on Business Insider
Business Insider
10-06-2025
- Business
- Business Insider
Meet 10 AI trailblazers who are steering their companies into tech's new age
The corporate rush to adopt AI is shifting into high gear. As of July 2024, 78% of companies reported using AI for at least one business task, up from 55% since late 2023, according to a report from McKinsey & Company. From IT automation to personalized marketing, businesses are betting on AI to cut costs and drive growth. But AI adoption isn't without risks, including cybersecurity threats, data leaks, unreliable or biased model outputs, and a rising carbon footprint. For Business Insider's "AI in Action" series, we profiled 10 executives driving AI adoption at companies like JPMorgan Chase, PwC, and BMW. From chief AI officers to HR leaders, they're helping their organizations stay competitive — and safe — in the age of AI. Teresa Heitsenrether, the chief data and analytics officer at JPMorgan Chase At JPMorgan Chase, Teresa Heitsenrether leads the rollout of the bank's proprietary LLM Suite. The suite has given over 220,000 employees access to AI tools that can summarize internal data. The platform integrates capabilities from multiple leading AI providers and has already saved employees several hours of work a week, Heitsenrether said. "LLM Suite's widespread adoption is driving a cultural transformation across the bank," Heitsenrether told Business Insider. This rollout isn't just about experimentation — it's about execution. JPMorgan tracks every AI use case from ideation to production, ensuring each AI initiative drives business value. That includes cost savings, revenue generation, and risk reduction, Heitsenrether said. Working under this framework helps the bank prioritize projects with the highest potential impact. Additionally, employees across the bank are trained through a mix of in-person and online courses to use AI effectively and responsibly. Joe Atkinson, the global chief AI officer at PwC Joe Atkinson is embedding AI across the firm's operations and services. He led the launch of an internal AI chatbot deployed to 270,000 employees to help them generate reports and assist in project delivery. Under his leadership, PwC also rolled out tools like Code Intelligence, which helps organizations modernize legacy systems through generative AI-powered code conversion, and Agent OS, which was designed to streamline AI-driven workflows. Additionally, Atkinson said he launched a global AI Academy, which has trained 90% of staff in prompt design and responsible AI use. "We're seeing a ton of growth and capability from our people," Atkinson said, pointing to rising usage and more complex tasks handled by AI. He emphasized the importance of trust, governance, and accountability, adding that virtually every function at PwC is expected to be AI-powered in the near future. Bala Subramanian, the executive vice president and chief digital and technology officer at UPS Bala Subramanian is leading UPS's digital transformation with a focus on integrating AI across operations. Under his leadership, UPS has implemented the Message Response Automation system, which uses large language models to automate responses to customer inquiries and reduce agent handling time. "By alleviating the burden on our human agents, it enables them to focus on more complex and nuanced customer needs," Subramanian told Beyond customer service, Subramanian is overseeing the rollout of AI and automation technologies — like pick-and-place systems and autonomous guided vehicles — across shipment operations. Bloomberg reported that as of April, UPS is exploring a potential partnership with Figure AI, a robotics startup, to implement humanoid robots into its operations for tasks like sorting parcels. UPS is also investing in AI infrastructure, signing a decade-long deal with NTT Data in late March to modernize its data centers — part of a broader strategy to update its logistics network and improve service delivery. UPS didn't respond to BI's request for comment. Johan Gerber, the executive vice president and head of security solutions at Mastercard Johan Gerber is helping Mastercard use AI to strengthen fraud detection across its global payment network. His team oversees cybersecurity, digital identity, and dispute resolution in an effort to protect businesses and card users from scams. With Gerber at the helm, Mastercard launched tools like Decision Intelligence and Safety Net, which use generative AI, machine learning, and data scanning to analyze transaction patterns, improve fraud detection rates, and flag suspicious activity. LLMs have also been integrated into MasterCard's Recorded Future tool, which allows analysts to quickly sift through its threat-intelligence database with queries like, "Tell me about the new malware families you found yesterday." Gerber told BI that combining generative and traditional AI has improved detection accuracy, but he also stressed the importance of rigorous testing and data governance before deploying models into production. He also recommended a method called "silent scoring," which runs new AI models alongside active models before they go live; this helps assess the new model's soundness and vulnerabilities. Suresh Kumar, the global chief technology officer and chief development officer at Walmart Suresh Kumar is leading Walmart's AI transformation to boost efficiency and personalize retail experiences. He helped launch "My Assistant," a generative AI tool that helps over 50,000 corporate employees summarize documents, draft content, and streamline onboarding. The company has also invested in developing proprietary LLMs like "Wallaby," trained on decades of internal data, to power customer-facing assistants and personalized homepages. In supply chain operations, Walmart uses AI for product placement, inventory management, and robotic automation. The Wall Street Journal reported that the company is testing autonomous shopping agents that can purchase items for customers. "A standard search bar is no longer the fastest path to purchase, rather we must use technology to adapt to customers' individual preferences and needs," Kumar said in an October press release. Walmart didn't respond to BI's request for comment. Marco Görgmaier, the vice president of enterprise platforms and services, data, and artificial intelligence at BMW Group Marco Görgmaier is leading BMW's AI integration across production, engineering, and marketing. He said the company's generative AI strategy centers on three pillars: adopting third-party tools, building proprietary applications, and providing in-house tools like the BMW Group AI Assistant, which lets staff create custom software without code. Görgmaier said training programs, development guidelines, and hands-on support further ensure teams are equipped to navigate the AI shift. "While conventional AI has driven efficiencies in targeted areas like predictive maintenance and quality assurance, generative AI expands the horizon, enabling automation, creativity, and innovation across the entire organization," Görgmaier told BI. He said it's important to start every AI project with a clear business need and ensure cross-functional collaboration and compliance. A key to scaling AI, he added, is a centralized, flexible data platform that supports rapid adoption of new technologies while ensuring cost efficiency and regulatory compliance. Bhavesh Dayalji, the chief AI officer at S&P Global and the CEO of Kensho Bhavesh Dayalji is guiding efforts to boost productivity through internal generative AI tools at S&P and Kensho, S&P's AI and innovation research division. Spark Assist, for example, is an internal chatbot that helps more than 40,000 employees draft reports, synthesize data, and streamline workflows. Unlike public tools like OpenAI's ChatGPT, these are built on proprietary data and include agentic features for task automation. Another tool is Chat IQ, a chatbot where employees can query S&P's financial datasets with questions like, "What is the price of a certain stock?" To ensure widespread AI adoption, Dayalji introduced S&P's workforce to mandatory training, which included online videos and workshops, designed to upskill leaders and employees. "This is a transformation journey," Dayalji told BI. "We want people to have hands-on experience and understand how it's going to help them." Dayalji said S&P will continue placing big bets on AI: Kensho, for instance, is developing a Grounding Agent for autonomous research and analysis using the firm's proprietary datasets. While AI is still in its "early days," Dayalji called the current moment an "amazing time to be involved" in adopting and advancing the technology. Ulrika Biesèrt, the global people and culture manager at Ingka Group (IKEA) Ulrika Biesèrt is helping Ingka Group equip IKEA's global workforce — over 160,000 employees across 31 countries — with AI skills. Since launching AI literacy programs in April 2024, the retailer has trained over 4,000 employees in areas like responsible, ethical AI usage, Biesèrt said. The goal, she added, was to train 30,000 employees and 500 leaders. "At IKEA, we've always believed that change should start with people," Biesèrt told BI. One tool employees are taught to use is Hej Copilot, an internal generative AI assistant that helps with everyday tasks like creating presentations and brainstorming ideas. To inspire their colleagues, early adopters shared use cases for the tool at workshops. Implementing such a vast program isn't easy. Technological change comes with uncertainty, Biesèrt said. To address this, nearly 650 senior leaders were trained, exceeding IKEA's initial goal, to ensure a "structured, cohesive approach" to AI across the organization, Biesèrt told BI. Arnab Chakraborty, the chief responsible AI officer at Accenture Arnab Chakraborty oversees Accenture's internal responsible AI compliance program to ensure AI is developed, deployed, and scaled sensibly across Accenture and its roster of more than 9,000 global clients. According to the company, Accenture has committed $3 billion over three years to expand its Data & AI practice and double its AI talent to 80,000 professionals. "We have to ensure that AI solutions have fairness, transparency, and accountability embedded from the start," Chakraborty said. He's also co-leading a $700 million partnership with Telstra. The goal is to help the Australian telecommunications company integrate AI into its workflow processes, including identifying fiber cable defects and faster customer service, AFR reported. Chakraborty told BI the partnership also involves advancing responsible AI capabilities like real-time model monitoring so that Telstra's AI systems are compliant with its internal policies and community guidelines. Building and maintaining the right data infrastructure to scale AI remains a barrier to adoption, Chakraborty added. To address this, Accenture has partnered with the Center for Advanced AI in Mountain View, California, gaining access to research labs at academic institutions like UC Berkeley and Stanford to study data privacy and develop AI training programs for companies. Chakraborty said by year's end, Accenture plans to launch over 100 agentic AI tools designed to detect and correct algorithmic issues, such as biases or hallucinations, before they impact business operations. Boris Gamazaychikov, the head of AI sustainability at Salesforce Boris Gamazaychikov leads Salesforce's push to decarbonize the company's AI systems. Recognizing the significant energy demands of training large AI models, Gamazaychikov's sustainability strategy emphasizes the importance of developing efficient, domain-specific models. Salesforce's AI Research team has created xGen, designed for customer relationship management, orCRM, tasks like generating call summaries. These models consume less power and emit fewer emissions than general-purpose ones, according to Salesforce. Under Gamazaychikov's leadership, the CRM provider has introduced AI tools that help customers decarbonize, including AI agents for sustainability measurement and a nature-focused accelerator for climate-focused nonprofits supporting forest conservation, regenerative agriculture, and other efforts. "It is important that software and AI companies are also part of the solution to reduce emissions, and provide tools that help others reduce their emissions," Gamazaychikov said in an interview for Autonomy's " The Decarbonists" newsletter.
