
Ferrovial boosts efficiency & safety with DXC AI Workbench
DXC Technology has launched a generative AI platform aimed at helping businesses deploy and scale responsible artificial intelligence across their operations, with Ferrovial confirmed as the anchor client.
The Fortune 500 technology services provider introduced the DXC AI Workbench on Tuesday, describing it as a secure, enterprise-ready solution that blends consulting, engineering and enterprise services. The platform is already being used by infrastructure giant Ferrovial to support real-time decision-making across its 24,000-strong workforce.
"AI isn't a plug-and-play solution—leveraging GenAI securely and in compliance with regulations requires human due diligence, customisation, and the right skill sets," said Howard Boville, President of DXC Consulting & Engineering Services – Powered by AI. "We're helping clients, such as Ferrovial, build and implement AI solutions throughout their operations to drive outcomes at scale and unlock opportunities to innovate."
Ferrovial, which operates in over 15 countries, is using more than 30 AI agents deployed through the platform on Microsoft Azure. According to DXC, these agents are already improving productivity, increasing business agility, and enhancing safety standards.
"By working with DXC, we've unlocked new levels of operational efficiency and reduced risks," said Dimitris Bountolos, Chief Information and Innovation Officer (CIIO) of Ferrovial. "The ability to integrate AI into our core business processes has revolutionised how we reduce operational costs, manage knowledge, and make decisions, providing us with a competitive edge in the industry."
The DXC AI Workbench is designed to help companies navigate the challenges of integrating AI responsibly and at scale. It includes built-in governance mechanisms and security features to ensure compliance with evolving regulatory standards.
Ferrovial is deploying the platform across a broad range of business functions, including field operations, regulatory analysis, and competition tracking. The system has also been integrated with various back-office tools, including Workday, ServiceNow, Microsoft Teams, and several of Ferrovial's proprietary applications.
This integration, according to DXC, is already delivering accelerated automation and more robust data-driven decision-making throughout Ferrovial's global operations.
"DXC helps clients across industries find scalable solutions to meet their unique challenges, so they can move fast," the company said in a statement. "With its new AI Workbench offering, DXC is delivering a pre-built scalable solution with necessary safeguards and governance for secure deployment."
With this new offering, DXC is targeting enterprises seeking to adopt generative AI without compromising on compliance or control. The company claims its deep industry expertise allows it to tailor solutions to specific sector needs, making AI adoption more feasible for organisations facing complex operational environments.
Ferrovial, for its part, has expressed confidence that its collaboration with DXC will continue to deliver measurable benefits as AI integration deepens.
The platform's cloud-based architecture on Azure and its ability to interface with existing enterprise systems are central to its promise of seamless deployment and impact. Ferrovial's early use of the system suggests a practical application of generative AI in large-scale infrastructure operations—a potential benchmark for other firms in the sector.
With the release of DXC AI Workbench, the technology company is signalling a shift towards offering more comprehensive, embedded AI solutions for enterprises worldwide. While many businesses remain cautious about integrating artificial intelligence due to regulatory uncertainty or technical limitations, DXC is positioning its platform as a means to overcome those barriers through secure, scalable design.
The company has not yet disclosed further client rollouts, but the Ferrovial partnership is intended to serve as a reference implementation as it engages with additional organisations seeking enterprise-grade AI solutions.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Techday NZ
4 days ago
- Techday NZ
SOCRadar boosts MSSP support with free AI training, new tools
SOCRadar has announced an expansion of its Managed Security Service Provider (MSSP) programme designed to support partners in scaling operations, automating threat workflows, and improving service delivery. As part of the enhanced programme, SOCRadar will provide free AI Agent and Automation Training to its partners. This training aims to educate MSSPs on the use of AI agents and generative AI (GenAI) technologies to streamline security operations centre (SOC), threat intelligence, and vulnerability management processes. The training is described as platform-agnostic, equipping MSSP partners with hands-on experience to build their own AI-powered workflows, irrespective of the specific tools they currently deploy. Alongside the introduction of free training, SOCRadar has implemented several enhancements to its MSSP programme, including multi-tenant licensing, threat intelligence use cases designed specifically for MSSPs, a Multi-Tenant Management Console, and configurable External Threat Assessment Reports. "Our enhanced MSSP program enables partners to scale smartly and serve clients more effectively. By combining AI Agents with our extended threat intelligence capabilities, MSSPs can double their operational efficiency—automating routine workflows, accelerating incident response, and delivering tailored intelligence without adding headcount. We believe AI Agents and GenAI will be foundational to the future of MSSPs, and we're committed to helping our partners lead that transformation," Huzeyfe Onal, Chief Executive Officer of SOCRadar, said. According to SOCRadar, its AI agents are intelligent automation components embedded within the company's Extended Threat Intelligence (XTI) platform. These agents utilise Large Language Models (LLMs) and automation scripts with the ability to execute complex, multi-stage cybersecurity workflows. Unlike traditional scripts or static rules, SOCRadar's AI agents can analyse contextual information, make decisions based on data, and take actions across multiple IT systems. This approach is intended to reduce the manual workload for analysts, while increasing both the speed and accuracy of threat detection and response. MSSPs can create what SOCRadar refers to as "smart workflows" by establishing specific goals and operational boundaries for each AI agent. The agents then apply planning, reasoning, and learning methods to support tasks such as identifying threats, enriching data, correlating alerts, or prioritising vulnerabilities for remediation. The company listed several key benefits of its framework for MSSPs, including the automation of threat intelligence, SOC, and vulnerability management tasks; reduction in analyst workload while accelerating detection and response times; improvement in decision accuracy with a reduction in false positives; enablement of continuous monitoring across multiple clients without increasing staffing; and the potential to increase both scalability and profitability whilst preserving service quality. SOCRadar reports that it serves over 800 customers in 70 countries. Its Extended Threat Intelligence Platform makes use of artificial intelligence and machine learning for threat detection and to deliver actionable intelligence against cyber threats. The suite of offerings includes Cyber Threat Intelligence, External Attack Surface Management, Brand Protection, Dark Web Monitoring, and Supply Chain Threat Intelligence.


Techday NZ
4 days ago
- Techday NZ
Snowflake launches AI agents to ease enterprise data access
Snowflake has introduced new agentic AI features and expanded its enterprise-grade AI capabilities, aiming to enhance data analysis and machine learning (ML) workflows for businesses in Canada and worldwide. Snowflake Intelligence, set to enter public preview soon, provides business users and data professionals with a unified conversational interface driven by intelligent data agents. This development enables users to pose natural language questions and quickly access actionable insights from both structured and unstructured data. The company has also announced Data Science Agent, currently in private preview, which acts as an agentic companion designed to assist data scientists by automating routine ML model development tasks. These additions are intended to streamline AI and ML workflows, widen access to data within enterprises, and remove the technical barriers that traditionally slow business decision-making through natural language interactions within Snowflake. "AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents. Snowflake Intelligence breaks down these barriers by democratizing the ability to extract meaningful intelligence from an organization's entire enterprise data estate — structured and unstructured data alike. This isn't just about accessing data, it's about empowering every employee to make faster, smarter decisions with all of their business context at their fingertips," Baris Gultekin, Head of AI at Snowflake, said, commenting on the evolution of AI agents. Organisations frequently face difficulties in decision-making due to fragmented data governance, separate data formats, and a lack of technical analysts. Snowflake Intelligence addresses these issues by enabling business teams and non-technical users to interact conversationally with their enterprise data, all without needing to write code. Snowflake Intelligence operates within the user's existing Snowflake environment, inheriting all established security controls, data masking, and governance policies. It consolidates data from multiple sources, including Snowflake, Box, Google Drive, Workday, and Zendesk, via Snowflake Openflow, allowing users to retrieve insights from spreadsheets, documents, images, and databases simultaneously. Data agents can create visualisations and help users act on insights through natural language prompts. The platform also provides access to external knowledge via Cortex Knowledge Extensions available on Snowflake Marketplace, with content provided by sources such as CB Insights, Packt, Stack Overflow, The Associated Press, and USA TODAY, to add further depth and context to responses. The system is powered by large language models from Anthropic and OpenAI and is built on Cortex Agents, currently in public preview. All are presented through a no-code interface that seeks to ensure transparency and explainability in the use of AI. "By integrating Claude's reasoning capabilities directly into Snowflake's platform, we're further eliminating the traditional barriers between data and insights. Business users can now have natural conversations with their enterprise data, while data scientists can automate complex ML workflows — all through simple natural language interactions. This demonstrates how Claude's advanced reasoning can democratize AI while maintaining the enterprise-grade security and governance that organizations require," Michael Gerstenhaber, VP of Product Management at Anthropic, said, highlighting the integration's potential. Snowflake Intelligence is aimed at moving organisations away from reliance on analytics teams for insights, enabling broader employee access to data. "At WHOOP, our mission is to unlock human performance and healthspan, and data is central to everything we do. Snowflake Intelligence marks a big step forward in our ability to be a data-first organisation, ensuring that all employees can access insights without relying on analytics teams as the intermediary. By eliminating the technical barriers to gleaning the insights we need for decision-making, our analytics teams can now shift from manual data retrieval tasks to more strategic, predictive, and value-generating work," Matt Luizzi, Sr. Director of Business Analytics at WHOOP, said. To support data scientists, Snowflake's Data Science Agent automates time-consuming tasks linked to ML workflows. The agent, also using Anthropic's Claude, segments ML workflow challenges into separate steps such as data analysis, preparation, feature engineering, and training. It leverages advanced reasoning, contextual understanding, and action execution to generate validated ML pipelines that can be run from a Snowflake Notebook. Users can iterate with suggested improvements or follow-ups, helping to reduce time spent on experimentation or debugging. Currently, more than 5,200 customers, including companies such as BlackRock, Luminate, and Penske Logistics, are using Snowflake Cortex AI as part of their business operations. Snowflake is introducing several new AI features, such as enhanced document processing, batch semantic search, and the new Cortex AISQL, now available in public preview, aiming to facilitate analysis of multi-modal data at scale and assist teams that may lack extensive AI engineering skills.


Techday NZ
30-05-2025
- Techday NZ
APJ region accelerates AI adoption as Dell rolls out new innovations
Artificial intelligence is moving at an incredibly fast speed in the Asia Pacific and Japan (APJ) region, according to senior Dell Technologies executives who spoke at a media roundtable during the Dell Tech World conference in Las Vegas. As AI use cases proliferate and investment ramps up, the region is fast emerging as a global leader, both in adoption and ambition. "Asia Pacific is leading the way in generative AI spending, with 38% of AI investment in the region now focused on Gen AI, compared to just 33% in the rest of the world," said Peter Marrs, President of Asia Pacific, Japan and Greater China at Dell. "Even North America sits at 29%," he added, highlighting the region's rapid pace. Dell is positioning itself at the heart of this growth through its AI Factory and a growing ecosystem of technology partners, universities and governments. "There's not an industry that's untouched by AI, but financial services, healthcare, energy, retail and manufacturing really stand out. We're at the forefront of helping customers across these sectors," he added. Transforming business through AI factories The Dell AI Factory, a framework designed to help organisations scale AI, has quickly gained traction. "It's been a year since we announced it, and we've moved from having tens or hundreds of customers globally to thousands," said Chris Kelly, Senior Vice President of Data Center Solutions APJC at Dell. "Not only are more customers deploying it, but they're achieving real, tangible ROI." According to Danny Elmarji, Vice President of Presales APJC at Dell, the AI Factory has resonated because it provides a practical pathway for organisations to adopt AI at scale. "CIOs are trying to understand how to tackle AI inside their business. Unlike past technology shifts, this is fundamentally a business-driven initiative," he explained. Elmarji pointed to significant momentum in financial services, where generative AI is being used to recommend customer actions, automate fraud detection and transform digital banking experiences. In manufacturing, AI is powering digital twin capabilities and revolutionising fault detection, while in healthcare, early detection tools and enhanced electronic medical records are improving patient outcomes. AI is also driving change in retail, with computer vision enabling smarter inventory management, and in education, where Dell is working with universities to personalise learning and foster innovation. "We're building connections between the IT world, research and industry," Kelly noted. "It's about moving beyond pilot projects and making AI meaningful for everyday users." From modular data centres to sovereign AI The roundtable also showcased a unique customer partnership with South Korean AI education platform Elice. CEO Jae Won Kim described how Elice faced soaring costs when trying to provide deep learning environments for students and businesses. "We had to reduce GPU cloud fees by more than 90%," he said. The solution was a portable modular data centre powered by Dell servers, now used for everything from AI digital textbooks for five million students to sovereign AI workloads that comply with government requirements. "There's very limited data centre capacity in Korea for high-density AI workloads," Kim explained. "The modular data centre lets us host hundreds of GPUs, with liquid cooling for the latest chips. It's not just about education anymore – we're talking about a hybrid solution that could be deployed in Japan, Australia or anywhere data centre construction lags demand." Marrs praised the partnership, saying, "You really thought big, and you went and made it happen." Kim's advice for others: "AI is not going away. It's better to start early. If you're worried about investment, modular is the best way to start small and start fast." Innovation and ecosystem challenges Dell's announcements at the conference included a raft of new infrastructure solutions designed to cut energy costs, boost data centre efficiency and accelerate AI deployments of any size. The company's latest cooling technology can reduce energy costs by up to 60%, while new servers with AMD and NVIDIA chips promise up to 35 times greater AI inferencing performance than previous generations. Yet, challenges remain. "The biggest hurdles are people and ecosystem," Marrs acknowledged. "We need to educate the next generation of AI talent and work with governments to create the right regulatory and compliance frameworks." Kelly added, "Access to data centre space, power and cooling is going to be crucial. Requirements are moving so fast that what seemed high density a year ago now looks standard." To address these gaps, Dell is nurturing partnerships with universities, local ISVs and industry bodies, running hundreds of AI innovation days and investing in hands-on labs. "We're enabling partners to experiment in safe environments and bring AI to life," said Elmarji. Dell executives are optimistic but realistic about the scale of change. "We're delivering AI at scale in the largest and most complex use cases, but also helping small startups get started," Kelly said. "You don't have to spend a fortune – start small and grow. If you don't act now, you're falling behind." For Kim, the journey with Dell is just beginning. "It was a huge investment for us, basically a startup. We poured all our money into GPUs. But I think it will be a good journey," he said.