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This approach will allow Zoho to optimise the right model for the right user context, the company claimed. “Our LLM foundational models are optimised for specific business use cases, and because these are trained on fewer parameters, the inference cost is greatly reduced, passing on the value to the customer. We are also training 32 billion, 70 billion, and 100 billion models,” Ramamoorthy said. “Right-sizing is a common strategy among model developers, who are releasing LLMs in multiple sizes to suit diverse use cases and on-device constraints. Zoho’s strategy of creating “right-sized” and efficient AI models will allow the company to make cost and compute-efficient offerings a key part of its value proposition,” said Mohit Agrawal, research director of AI & IoT at Counterpoint Research. Zoho’s full-stack AI bet Zoho’s approach with Zia LLM differs from enterprise AI rivals like Microsoft’s Copilot, Salesforce’s Einstein, and Google’s Gemini as the company owns the full AI stack. While most competitors integrate third-party foundation models, Zoho’s models are trained, deployed, and run entirely on its own infrastructure and cloud. source

Core means to efficiency Like many large enterprises, Accenture has a highly complex digital core that contains a variety of IT solutions ranging from office architectures and multi-cloud, to data fabric and security platforms. The digital core is essential to run the business and enable quick onboarding of emerging technology, but the complex service chains and multiple technology stacks require a significant amount of human support. That, in turn, has made the rapid adoption of new technology difficult to integrate throughout the business. To smooth that process, AATA is an agnostic, open system with agentic architecture that enables IT teams and end users to interact with the core to resolve issues or deliver customer solutions without having to connect to an agent or file a single ticket. Accenture started working on AATA in 2023, starting with a conceptual architectural model. “Then we started to think about how people would consume the technology to derive value, so we wanted it to be largely democratized,” Courtney says. “You could have an open standards orchestration layer and a consistent prompt layer, but then enable teams to be able to either consume natively available agents, plug in existing automation or gen AI processes, or actually create custom agents if that was what required.” source

Irrespective of industry, the rise of gen AI has reignited boardroom discussions about cloud strategies. While the potential is big, so are the complexities — especially for CIOs suddenly facing budget overruns, security risks, and tangled hybrid environments. “Companies are trying everything, which leads to enormous costs,” says Juan Orlandini, CTO North America at Insight. “If you’re running gen AI in the public cloud, the costs add up quickly. You get charged for everything — compute, storage, and all the network traffic.” Juan Orlandini, CTO North America, Insight Insight Those surging expenses reflect a broader reality. Gen AI workloads are unpredictable, data-intensive, and often experimental, according to Bastien Aerni, VP at GTT, a networking and security as a service provider. “CIOs often don’t know how successful a given initiative will be,” he says. “Overinvesting is risky, and underinvesting limits scalability and user experience.” This cost is often amplified by data gravity in that once a large amount of data accumulates in one place, it becomes inefficient — both technically and financially — to move it elsewhere for processing. At the same time, cloud environments can unintentionally create data swamps through redundancy and uncontrolled sprawl. Orlandini warns of hidden costs when separating compute and data. “If your data is on prem and you use a cloud-based AI service, you either need high-speed connections or you need to duplicate the data in the cloud. Both are costly.” source

Overview In this episode of DEMO, host Keith Shaw sits down with Erik Costlow, Senior Director of Product Management at Azul, to explore how the company’s Intelligence Cloud platform is transforming Java application management for enterprises. Learn how Azul helps organizations:* Automatically identify and eliminate unused legacy Java code* Prioritize real security vulnerabilities instead of chasing false alarms* Reduce software maintenance burdens and technical debt* Gain full visibility into Java licensing, inventory, and compliance Whether you’re a VP of Engineering, software architect, DevOps lead, or CIO, this conversation is packed with insights on how to streamline Java-based infrastructures and reduce risk—while freeing up engineering time for innovation. 📽️ Watch the full demo above and read the full transcript below for easy reference or accessibility. Register Now source

Worldwide IT spend will reach $5.43 trillion this year, an increase of 7.9% over 2024, and it comes at a time when CIOs appear to be pausing their net-new spending as a result of political uncertainty, according to Gartner’s latest forecast, released Tuesday. Despite this, ongoing AI and generative AI (genAI) digitization initiatives are not being affected. “[While] both software and services spending growth in 2025 are expected to slow down due to this ‘uncertainty pause,’ spending in AI-related infrastructure, such as data center systems, continues to surge,” said John-David Lovelock, distinguished VP analyst with the research firm. The forecast is segmented into five areas with wildly varying growth predictions: data center systems, expected to soar with 42.4% growth, devices, with predicted 5.4% growth, software, with growth expected to hit 10.5%, IT services, with 4.4% growth over last year, and communication services, predicted to grow by 2.1%. source

SAP and Siemens call for new AI Act Siemens CEO Roland Busch and SAP CEO Christian Klein were absent, feeling the criticism didn’t go far enough. In an interview with the Frankfurter Allgemeine Zeitung (FAZ), they called for a fundamental revision of the EU AI Act, seeking a new framework that promotes innovation rather than hinders it. For Busch, the AI Act, in its current form, is “toxic to the development of digital business models.” For Siemens CEO Roland Busch, the AI Act in its current form is toxic for digital business models. Siemens AG An NGO perspective The Future Society, an NGO that sees itself as a representative of civil society, also has criticism for the new guidelines. The NGO is particularly concerned that US tech providers managed to weaken and water down key points in a closed session. Nick Moës, executive director of The Future Society, says: “This weakened code puts European citizens and businesses at a disadvantage and misses opportunities to strengthen security and accountability worldwide. It also undermines all other stakeholders whose commitment and efforts for the common good have remained overshadowed by the influence of US Big Tech.” source

In explaining BDC’s technical features and differentiating factors, Khan described a “flywheel effect,” SAP’s strategy to create a circular engine that leads to data generation, trust-based AI implementation, AI and data integration, and business value creation. Launched in February, BDC is a SaaS-based data platform that embodies this strategy, said Khan, who directly led its development. BDC integrates and organizes SAP and non-SAP data based on meaning, and is designed to accommodate not only SAP but also third-party data, he stressed. Data collected and integrated by BDC can be used to fuel AI agent functions or SAP’s digital assistant, Joule. “There are few products that have received as much response as BDC,” Khan said. According to Khan, the strength of BDC is that it can automatically align and synchronize various data sources without ETL or data pipeline management. This will allow customers to reduce the collection, refinement, and quality control tasks that typically account for more than 80% of the overall data management function, and instead focus more time on AI model training and application, he said. source

Then, all your human resources need widespread change management to ensure they know how to effectively collaborate and pull in the same direction. This means more than simply technical upskilling. They must also fully understand the reasons for the transformation, as well as the benefits –– to them and the organization –– of the new technology.  We have an ongoing program of associate training and support for our 6,000-strong tech workforce. As a result, the percentage of our people who can articulate how our tech transformation creates value has increased in the last year from 69% to 82%. This percentage has been steadily rising due largely to our dedicated change management practices.  Embrace the unexpected Even the best-planned journeys to new frontiers will run into unexpected challenges. For instance, while we had extensively planned for customer migration during our tech transformation, the effort required to make it go as quickly and smoothly as possible was greater than expected. After all, we provide mission-critical solutions, so customers didn’t simply want to know we had validated a new product. They wanted reassurance we had validated their specific use cases. In response, we doubled down on resources to give them enhanced confidence.  source

Kamal also says the unique attraction of IT has been the driving force behind his long career since, for him, the true appeal of it lies in the joy of problem solving. As he puts it, the IT department often goes unnoticed when everything runs smoothly, but the moment something goes wrong, it becomes the center of attention. In such an environment, someone who becomes intimidated whenever problems arise will find it difficult to adapt. But those with an open mindset and a ‘let’s solve this’ attitude will feel that IT is a true calling. “The advantage of the IT industry is its transparency,” he says. “Ultimately, all challenges in the IT department come down to whether the technology works or doesn’t, and problems always occur in this process. And while total prevention is impossible, we can build systems to ensure the same trial and error isn’t repeated.” Harmonizing centralization and localization Mercedes-Benz’s global IT organization includes around 10,000 experts driving infrastructure, cloud services, software-defined vehicle platforms, and AI technology development, and much more. The company also places a CIO at the group level at its headquarters while assigning regional CIOs to key markets, and Korea is the fifth-largest market in terms of sales volume. There, Kamal leads a Korean IT team, which serves as the core driving force behind digital innovation, as well as a shared service center in the Philippines. source