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Based on this new strategy, JRFU has a business co-creation partner framework with J Sports to produce official videos for League One, and since last year, it also covers the men’s 15-man national rugby union matches. Partnering with AWS Amazon Web Services plays an important role in Japan’s rugby media strategy, including AWS Elemental Live, which encodes live video from the matches and uploads it to the cloud, and AWS Elemental MediaLive, a live video processing service that encodes streaming video. Video content is then stored in Amazon S3, and indexing is possible to preview and search. Agility and better economics are common incentives for organizations to move to the cloud. But the overall appeal of the ecosystem is popular, too, and the fact the services they want to use, such as the remote comment system Spalk, are provided on AWS is another unique feature. This has the advantage of making video transfer smoother. And by realizing an end-to-end system on AWS, JRFU is able to reduce development man hours, such as compatibility testing, and use managed services to reduce the management burden. In addition, the video and photo archive system built in collaboration with AWS allows media exposure during and immediately after matches. Real-time match footage can be distributed on official SNS accounts and provided to other media. In the 2023-24 season, for example, one match was live-streamed per week on the League One official website. Although the foundation for using video was set, only a few teams used it at first and there were other promotion challenges to overcome. source

China is pushing the boundaries of its own AI development every few weeks, and its results are already a serious threat to Western technology. While in the West AI was an exclusive and lucrative resource available only to select companies, China, thanks to its open approach, bypasses sanctions, decentralizes development, and uses available resources for mass AI development. And thanks to the development of AI in the open-source model, hardware availability is no longer a problem, because models are voluntarily tested and improved by their users, e.g., from Europe. If open-source AI becomes as powerful as US proprietary models, the ability to monetize AI as an exclusive product will collapse, which is a key consideration for China. The opening of AI models from China is a surprising move that may also disrupt the foundations of OpenAI’s classic AI model development — based on a small group of companies capitalizing on the latest technological advances. China may be the country that proves that it doesn’t always pay to be first. Its approach could change the balance of power in the development of artificial intelligence. AI will also be an important weapon in the US-China technological war. The coming months will be extremely turbulent in the context of AI development, in addition to the traditional facets of US-China geopolitical and economic friction. source

For IT and support teams, a well-maintained knowledge base is the foundation of efficient service management. An extensive knowledge repository enables employees to quickly find answers to issues, thereby reducing downtime and improving productivity. When current, accurate knowledge is stored, categorized, and easily accessible, IT and support teams can avoid reinventing the wheel, ensuring that best practices and proven solutions are reused instead of being rediscovered repeatedly and inefficiently. However, maintaining a high-quality knowledge base is a challenge for many organizations. As information constantly evolves, support teams struggle to keep articles up to date, eliminate redundant or conflicting content, and ensure knowledge remains relevant and validated. When knowledge bases are poorly managed, employees are more likely to abandon self-service options and escalate issues to service teams, increasing workloads and driving up support costs. Generative and agentic AI are set to transform these processes by automating knowledge creation, curation, and maintenance. By leveraging advanced AI technologies, organizations can enhance self-service adoption, improve support team efficiency, and reduce operational costs. Generative and agentic AI transform knowledge management Building and maintaining a high-quality knowledge base has long been a challenge for IT and support teams. Without consistent updates, articles quickly become outdated or redundant, leading to inefficiencies and frustration for employees searching for answers. Traditional knowledge management requires significant manual effort — from documenting best practices to curating and validating content — which puts a strain on time and resources. This is where generative and agentic AI can transform processes, automating routine tasks and ensuring knowledge remains accurate, accessible, and actionable. There are several ways AI-powered solutions like BMC HelixGPT Knowledge Curator are transforming knowledge management: Automating knowledge creationGenerative AI can draft new knowledge articles by analyzing resolved incidents, support interactions, and historical data. AI can suggest structured, easy-to-understand articles that support teams can review and publish, significantly reducing the time required to document best practices and solutions. Enhancing knowledge curationAgentic AI can continuously monitor knowledge usage, identifying which articles are most helpful and which need updates. The technology can also recommend archiving or consolidating outdated or underutilized articles, ensuring that only the most relevant and effective content remains accessible. Deduplicating and consolidating contentAI can scan the knowledge base to detect duplicate or conflicting articles and merge them into a single, authoritative source, making reliable answers easier to find. Automating knowledge validationAI-driven validation processes can cross-check articles against the latest policies and best practices. Automated validation reduces the risk of incorrect information persisting in the knowledge base, ensuring employees always have access to accurate guidance. Delivering actionable, summarized answersInstead of requiring employees to browse lengthy documents, AI can provide concise, actionable summaries based on validated knowledge articles, enabling faster decision-making and minimizing the time employees spend searching for information. The benefits to support teams, employees, and the organization The adoption of generative and agentic AI in knowledge management benefits support teams, employees, and the organization. For IT and other support teams, AI automates knowledge creation and maintenance, reducing manual workloads, improving response times, and minimizing escalations. Employees gain faster self-service resolutions through AI-driven interfaces, accessing up-to-date knowledge without sifting through outdated information. Organizations see lower operational costs as AI reduces manual efforts, increases self-service adoption, and decreases ticket volume. With AI enabling employees to quickly find and act on information, businesses improve agility, ensuring IT and support teams can focus more on strategic initiatives rather than repetitive, routine support tasks. The future of knowledge and service management is AI-driven As AI capabilities continue to evolve, the role of generative and agentic AI in service management will expand. The integration of AI into knowledge management is not just an enhancement, it is also a transformation enabler. Generative and agentic AI provide the automation and intelligence needed to overcome traditional knowledge management challenges, delivering precise, actionable answers that empower employees and optimize support operations. By adopting AI-driven knowledge management, organizations can achieve higher productivity, lower costs, and better experiences that benefit everyone. For IT executives seeking to future-proof their organizations, BMC HelixGPT offers a glimpse into the potential of agentic AI. The question is no longer whether enterprises should adopt AI-driven service management, but how quickly can organizations embrace this transformative technology? To see how BMC Helix can help you transform enterprise IT work with agentic AI, visit here for more information or contact BMC. source

At Nvidia GTC 2025 in San Jose today, Deloitte announced Zora AI, a new agentic AI platform that offers a portfolio of AI agents for finance, human capital, supply chain, procurement, sales and marketing, and customer service. The platform draws on Deloitte’s experience from its technology, risk, tax, and audit businesses, and is integrated with all major enterprise software platforms. Deloitte also mentioned that Zora AI’s specialized digital agents can autonomously complete tasks and provide on-demand insights, analysis, reporting, workflow automation, decision support, and data sourcing. [ Related: Nvidia GTC 2025: News and insights ] According to IDC’s Worldwide C-Suite Tech Survey, 2024-2025, Deloitte is among the top 10 vendors that C-suite executives in North America and EMEA identify as strategic partners for gen AI initiatives, and ranks second among service providers. Now it’s seeking to parlay that trust and enterprises’ rapid adoption of agentic AI into a new role, helping organizations facilitate the collaboration between agents and human employees. PwC, in fact, estimates gen AI could contribute between $2.6 trillion and $4.4 trillion annually to global GDP across various industries by 2030. source

“It leverages all the best practices and our SAP application programming models, which have been specially designed to extend and build around business applications,” Sandhu said, adding that a developer who has never built on SAP can give Joule for Developers a prompt and it will build the back end system, the front end UX, and the data model, allowing them to get started, “literally in minutes,” with a full application that they can customize. And if one of the more than 400 prebuilt line-of-business applications matches the functionality requested by the developer, Joule will recommend it. He also pointed out that before the AI passes its output to the user, it runs it through internal checks to verify its accuracy and reduce the chance of hallucinations. Joule for Developers differs from other AI coding assistants, noted Arnal Dayaratna, research vice president, of software development at IDC, in that “its deep specialization in ABAP that is attributable to SAP’s enhanced access to ABAP-specific training data.” Its integration with ABAP and SAP Build, he said, gives it “a unique capability” to support both pro code and no code developers. source

The insights that can be derived from mainframe data represent a huge opportunity for businesses. It could be a retail store looking to rework outdated processes and improve the customer experience, or a healthcare network hoping to get a handle on its security posture with enhanced fraud detection. No matter the intended result, organizations that understand the potential of mainframe data and actively collect, analyze, and apply its insights at scale have a unique advantage. That advantage can instill confidence among decision-makers and leaders, ensuring they are equipped with the best real-time insights when looking to innovate. For leaders searching for ways to maximize the value of their mainframe data, a number of advances in areas including artificial intelligence (AI), cloud computing, and data management  can help make leveraging data easier. These tools and technologies give data and analytics leaders a powerful means to improve operations, boost efficiencies, and transform experiences.   The path to advanced analytics runs through mainframe data The hype behind AI is nothing new, and it has shown plenty of promise in its ability to transform operations end-to-end within IT systems and enhance customer experiences. In a survey conducted by Rocket Software, respondents identified several benefits that motivated them to pursue AI initiatives. These include improvements to operational efficiency (56%), bolstering risk management (53%), and elevating decision-making (51%). Of those top motivators, 85% of respondents said they were focused on business optimization, driven by a desire to boost operational efficiency or improve their risk management. And overall, 96% of respondents had one of these three factors in their top three motivations for investing in AI. But before businesses can reap the benefits of AI investments, they need to ensure they have access to reliable, accurate, and timely data. This is where mainframe data, an often-under-leveraged resource, comes into play. A majority of organizations have relied on mainframe systems in some form or another to house vast amounts of transactional data — many of which have been around for decades. That historical context and huge data set make mainframe data ripe for the picking when it comes to AI and analytics — two things that depend on data to feed models and generate insights. When considered within the context of AI initiatives, 42% of surveyed leaders said they considered mainframe data to be a viable option for enriching insights. So, what about putting mainframe data into practice? Those leaders identified the ability to build out new analytical capabilities as the top use case for this data. But successfully building those new capabilities and generating new opportunities means having an effective modernization strategy, as well as an experienced technology partner to support that transformation. Building the right strategy to maximize mainframe data Rocket Software’s survey found 56% of decision-makers identified security, compliance, and data privacy as a top obstacle to actually utilizing mainframe data. Getting past that hurdle is all about striking the right balance between leveraging data while also ensuring its use is in line with existing policies and guidelines. Achieving this requires a robust set of security and compliance solutions to help bridge the gap and enable consistently secure use of mainframe data in broader AI efforts. For example, the right data integration solutions, like those in the Rocket® DataEdge suite, provide a broad set of tools to help organizations ensure all their data can be easily accessed, managed, and interpreted while still adhering to crucial regulations like GDPR and HIPAA. Organizations should also include a comprehensive content management solution, like Rocket Mobius, as part of their portfolio to deliver stronger data governance. Beyond security, an effective strategy also needs to ensure that an organization’s data pipelines and the processes that exist across the mainframe and other infrastructures are easily scalable. Scalability, however, has proven to be a pain point for many leaders. Of those surveyed by Rocket Software, nearly a third (31%) identified scalability as an issue. As organizations look to establish strategies that include mainframe data, they need to incorporate solutions that help tap into the best of both cloud environments and the mainframe, like Rocket Software’s Hybrid Cloud Data Suite. Doing so gives organizations the ability to create a simplified view of data — structured and unstructured — spanning on-premises infrastructure and the cloud. Mainframe data is full of opportunity for growth, new opportunities, and more impactful AI and analytics. Properly leveraging mainframe data brings forth deeper analytical insights that can transform the way businesses leverage AI. But a number of challenges stand in the way as organizations look to access that data securely and use it at scale. With the right technology solutions and a trusted partner, leaders can bring mainframe data to their modernization strategy, improve operations, and effectively leverage AI and advanced analytics. Learn more about how your organization can tap into the power of mainframe data. source

Chief data officers: ESG data’s not a side quest. Your data’s green footprint — or lack thereof — defines your future. Lead now, or get left behind. source

A global telecom provider recognized that its traditional approach to delivering service and support to its employees was becoming a bottleneck. With a large workforce generating a high volume of IT, HR, and finance-related support requests and inquiries, the company faced increasing operational pressure and strain. To improve response times and reduce manual support efforts, the company adopted BMC HelixGPT. The agentic artificial intelligence (AI) platform multiplies productivity, elevates service team efficiency, and improves the employee experience. For the telecom provider, the results have been dramatic: Employees are resolving issues faster on their own. Support teams are focusing on higher-value tasks. The company has significantly reduced costs by shifting to more effective self-service support channels. Overcoming the challenges of high-volume support requests Before implementing BMC HelixGPT, the company relied heavily on manual support processes, leading to long wait times and inefficient workflows. With tens of thousands of employees and consultants requiring assistance, service teams were handling an overwhelming number of repetitive and routine inquiries, leaving little time for resolving more complex issues. The telecom provider needed a new approach that would enable employees to resolve common and routine issues through a self-service portal, while maintaining access to live support when necessary. The objective was not only to improve operational efficiency but also create a more responsive, employee-friendly support system better aligned with the organization’s long-term automation strategy. Shifting to AI-powered support To address these challenges, the company deployed the BMC Helix agentic AI solution that integrates self-service tools, intelligent chat capabilities, and knowledge management. Boosting its BMC Helix Service Management solution with BMC HelixGPT Employee Navigator delivered several key benefits: Improved self-service capabilities: Employees gained access to AI-generated knowledge summaries and articles, allowing them to find concise answers quickly without waiting for a support agent. Intelligent chatbot interactions: Generative AI-driven chat services now answer more than half of user inquiries for IT and other departments in more human-like, natural language engagements. Elimination of manual support: The company transitioned entirely to digital support channels, improving efficiency and reducing operational costs. Delivering real-world impact Since adopting BMC HelixGPT Employee Navigator, the company has achieved significant results that have helped its support operations, including: More effective support interactions AI-driven support has achieved over a 60% success rate, with the majority of employee inquiries resolved without human intervention. When live support is needed, chatbots transfer employees to the appropriate service agents with relevant context, eliminating employees repeating information or being delayed from agent mis-assignments. Higher employee satisfaction and productivity Faster resolutions mean employees spend less time waiting for support fulfillment and more time focusing on their work. Support teams are no longer overwhelmed by routine questions, allowing them to refocus on solving complex, high-priority issues. Higher staff productivity from reduced operational overhead is driving more transformation initiatives and business innovation. Significant time and cost savings Employees can now resolve issues independently, reducing the burden on IT, HR, and finance support teams. AI-generated knowledge summaries and articles alone have been estimated to save hundreds of support staff hours in the initial year by making information more concise, accessible, and usable. Overall, the company estimates several thousands of hours have been saved annually from current use cases that improved efficiency across multiple departments. Expanding AI across the enterprise With the success of agentic AI and BMC HelixGPT in its IT, HR, and finance service operations, the telecom provider is now exploring additional opportunities to expand AI-driven support. Future plans include: Rolling out AI-powered support across more business units, extending benefits to a wider range of employees. Testing new AI-driven use cases that integrate with additional enterprise workflows to further reduce manual efforts. Exploring BMC Helix AIOps and observability solutions to proactively monitor and prevent service disruptions before they affect users, increasing critical system uptime while reducing costs and risks. Delivering better outcomes with AI By embracing AI-powered service management, this telecom provider has redefined how enterprise support should work. Employees now experience faster, more efficient and effective resolutions, while the organization benefits from reduced costs and optimized resource allocation. As agentic AI-powered automation continues to improve, BMC HelixGPT will remain a key solution component of the company’s long-term strategy, helping the company adapt, scale, and deliver better support outcomes across all areas of the business. Ready to transform your service delivery experience? Explore the BMC Helix agentic AI solution today or contact BMC Helix to see how AI can elevate team performance and the user experience. source