CIO CIO

Why the CIO role should be split in two

This ‘hybrid’ architecture is a combination of best and bad practice. When there is an outage, the new digital platforms can invariably be restored to recover business process support. But because they do not operate in isolation, instead connecting with legacy technologies, business operations themselves may not fully recover if the legacy systems continue to be impacted by the outage. For most enterprises stuck in this hybrid state, the way forward is to be more discipline around architecture. As a CIO, I’ve experienced that many enterprises have strong architecture disciplines with great governance practices and a roadmap that closely aligns various IT strategies. Strong alignment of IT and cyber strategy, however, is often an exception rather than a rule. Keep IT simple Simplifying architecture at an enterprise level is something the CIO and CISO should work together concurrently as a shared goal. The benefits of doing so will accrue over time rather than immediately, hence there can be some reluctance to prioritize. source

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Salesforce bets big on Saudi Arabia with 500M USD AI investment

Salesforce has announced a $500 million USD investment in Saudi Arabia, signaling its commitment to fostering innovation and economic growth in the region. The investment, unveiled at LEAP 2025, aims to bolster workforce development through AI skilling initiatives and expand Salesforce’s local partner ecosystem. This move follows Salesforce’s pledge at Davos to establish a new regional headquarters in Riyadh. A key component of this expansion is the introduction of Hyperforce, Salesforce’s next-generation platform architecture, to Saudi Arabia. Delivered in partnership with Amazon Web Services (AWS), Hyperforce will enable Salesforce customers to run workloads locally while adhering to regulatory requirements. “We are entering a new era where autonomous AI agents working with humans are transforming workforces and businesses across the globe,” said Marc Benioff, Chair and CEO, Salesforce. “With Agentforce, Hyperforce, and our global partner ecosystem, we are empowering Saudi organizations to deliver unprecedented levels of productivity, growth, and customer success.” source

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SAP taps Splunk’s Simon Davies to lead reorg’d APAC region

SAP has announced the appointment of Simon Davies as president of the company’s newly reorganized Asia Pacific (APAC) region. Based in Singapore, Simon Davies will be responsible for SAP’s strategy, operations, people, sales, services, partnerships and profitability in the region, including the markets of Korea, Australia, New Zealand, India, Japan, Greater China, and Southeast Asia. As president, Davies will manage more than 31,000 employees across 78 offices. SAP currently serves major customers in the region, including Hyundai Motor Co., Kia Motors, NEC, Coles Group, Wipro, Fujitsu, Shiseido, Himalaya, Cochlear, and Japan Airlines. According to SAP, Mr. Davies has been instrumental in developing, selling, and implementing IT solutions in the Asia Pacific region for 25 years, working with leading software companies such as Microsoft, Salesforce, and Oracle. He most recently served as senior vice president and general manager for Asia Pacific and Japan at Splunk for over three years. source

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CIO Leadership Live Middle East with Syed F Albeez, Head of Information Technology Emaar at The Economic City

Overview Welcome to CIO Leadership Live Middle East, where today we are thrilled to have an insightful conversation with one of the region’s most prominent leaders in the world of technology. Joining us is Syed F. Albeez, the Head of Information Technology at Emaar, overseeing technology innovations within the prestigious Economic City. With years of experience at the forefront of IT leadership, Syed plays a crucial role in driving the digital transformation that is reshaping the future of smart cities and urban development. In this interview, we’ll explore his journey, leadership approach, and the pivotal role of technology in shaping the future of the Middle East. Let’s dive into this exciting conversation! Register Now source

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CIO Leadership Live ASEAN with Paulo Martin Santos, Converge ICT Solutions

Overview Paulo Martin Santos – Chief Network Transformation Officer at Converge ICT Solutions – shares how artificial intelligence (AI) is transforming their networks and allowing their employees to focus on more strategic work, how their investment in data centres is accelerating innovation in the Philippines, and more. Register Now source

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Prioritizing AI investments: Balancing short-term gains with long-term vision

In parallel, building the organizational constructs around data quality also requires addressing data governance in parallel and supporting roles for data custodians, stewards and a centralized or federated data governance model to support credible and consistent enterprise data catalogs and products. With an enterprise data platform in place that supports a business-ready zone for consumption as well as appropriate governance, a critical machine learning readiness step is also in place. This can address data anomalies, cleansing and data lineage validation with a deeper level of sophistication in terms of algorithms and training-ready models.  By focusing on building the right data platform with the right OEM channel partners, enterprises can not only position their foundational investment in data for success but extend capabilities on the same platform to include best-of-breed, native machine learning features. Enterprises that elect to implement on the Snowflake data cloud, for example, might pursue native machine learning platform options to leverage the strength of the investment they have as opposed to the ones they don’t. Open-source implementations for machine learning invite obvious and hidden costs if your organization is not prepared to manage them.  Assuming the data platform roadmap aligns with required technical capabilities, this may help address downstream issues related to organic competencies versus bigger investments in acquiring competencies. The same would be true for a host of other similar cloud data platforms (Databricks, Azure Data Factory, AWS Redshift). In all cases, the foundational data platform roadmap matters in terms of near-term gains and long-term vision.  source

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The people and AI that fuel Repsol’s digitalization

Finally, there’s the responsible AI group, and since the first stage of the digital program, mechanisms have been established to ensure responsible and safe AI models. “In the second digital wave, we’ve collaborated with other organizations by forming working groups to promote joint reports that ensure responsible AI,” Arroyo adds. “In addition, we set guiding principles in line with the European AI Act, and defined the governance model so AI is used legally, responsibly, and in an agile manner.”   Adding layers for better performance After a year of work, in addition to the lines already launched, the company created additional ones including systemized gen AI plans for each business unit; the Business and Productivity Impact Office to identify, measure, and monitor the impact generated by gen AI; structured training to facilitate the successful adoption of gen AI; and human-centered AI to define the interaction between users and applications.  The Generative AI Competence Center has also had a major impact on professionals and the corporate culture. Within the framework of new ways of working, the Copilot M365 pilot project has been carried out to help evaluate the impact of the gen AI tool, alongside active change management. The experiment lasted four months and resulted in an average time saving of 121 minutes per week, per person on routine tasks, which represents over 96 hours per year per employee. source

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Sonar analyzes code for quality, security metrics for developer teams

00:00 Hi, everybody. Welcome to DEMO, the show where companies come in and showcase their latest products and services. I’m joined today by Harry Wang. He is the Vice President of Growth and New Ventures at Sonar. Welcome to the show, Harry. 00:11Thank you for having me, Keith. 00:12So, tell us a little bit about Sonar and what you’re going to show us today. 00:15Yeah, absolutely. Sonar is the company behind a very well-known product, SonarQube, widely used in the developer and DevOps community. We serve over 7 million developers, 400,000 organizations, and more than 20,000 commercial customers. 00:34So, is this product designed for individual developers, teams, or entire IT departments? 00:42Both, actually. Our company was started by developers for developers, so we are very much a developer-first organization. Our goal is to help developers write better code, stay productive, and ultimately build better applications. For organizations and IT departments, it’s about coordination — ensuring software quality and code integrity. 1:06And if you had to narrow it down, what is the key problem you’re solving for developers? What challenges are they facing that Sonar can help with? 1:17In two words: code quality. As companies undergo digital transformations, software has become one of their most valuable assets. And behind every software product is its code. Code is, I would argue, the largest asset a company has as it moves into the digital future — especially with the rise of AI.Nowadays, it’s not just humans writing code; AI is generating code as well. So, maintaining high-quality code is critical because it underpins the entire application development process. 1:49Are companies typically checking their code quality after development, or are you seeing more teams integrate it into the development process? 2:03Excellent question. For our audience — many of whom are in leadership roles within organizations — the concept of “shift left” should be familiar. As a developer-first company, we’ve always focused on the left side of the development process. So for us, it’s about getting the code right from the beginning — solving and preventing problems early. The cost of fixing issues is much lower when caught early in development, and it’s even better if those issues never occur in the first place. 2:37So, if a company doesn’t have a platform like Sonar, how would they typically handle code quality? Would they be manually reviewing everything post-development, or would they be using other tools? 2:49Often, the traditional process involves defining requirements, writing code, and then passing it through various testing phases — unit tests, integration tests, usability tests. If everything goes well, it goes into production. But the feedback cycle for detecting issues — whether during testing or in production — can be very long, sometimes stretching for months. Developers in the field often experience delays due to these extended feedback loops. Our goal is to shorten that feedback cycle significantly. 3:25All right, so the idea is to speed up the entire process. 3:27Exactly. 3:28Let’s take a look at what you’ve got. Show us some cool stuff. 3:31Yeah, sure. I’m going to jump into the SonarQube UI. This is a self-hosted version, but we also offer a SaaS solution. This is the home view, where you can see multiple projects. For roles like Head of Engineering, Platform Engineering, or Developer Experience, managing many applications and projects is a daily task. We have a concept called portfolios, which helps different stakeholders organize projects they care about. These are self-defined — so, for example, a CIO might want visibility into all projects across the organization. Here, you can see different metrics that leadership cares about, organized by product. You get a high-level overview, but you can also drill down into individual projects. If you’re concerned about releasability, for example, this tells you if a project has issues preventing it from being built or deployed. Or, if you’re the CISO, security is your priority. You can see security metrics across different projects. Reliability is another key factor — things like race conditions between threads or memory leaks. So, we measure various aspects of the code depending on its state. Whether you’re a team lead or a senior leader, you can generate customized reports. 5:15And I see you’re giving letter grades. That reminds me of school. 5:20Exactly, same concept! 5:22If you go back to your projects or portfolio… you had a lot of Ds on one of them. 05:29Yes, if a project has a D (or worse, an E), that’s a major red flag. Let’s take an example. My favorite language is Java, so let’s pick one of those projects. You can see this project has an E rating — definitely something that requires attention. We also have something called a quality gate. This is a concept we introduced to help organizations define stopping criteria. Essentially, if a project doesn’t meet certain standards — whether due to security issues, maintainability concerns, or lack of unit test coverage — it fails the quality gate. That means it cannot move forward until the team resolves the issues. Let’s drill into that. You can see the product failed, but you also get insights into what’s happening with new code and the overall codebase. Development teams typically work on small portions of a codebase at a time. It might contain millions or even tens of millions of lines of code, but during a sprint, they may only be touching a few files. They can choose to focus on just the new code or take a broader view — paying off technical debt and refactoring where needed. If I know there are 18 issues, I can drill down into them and see what’s causing the failure. As a developer or technical lead, I can investigate each issue, assign tasks, and ensure they’re addressed early in the sprint. You can also categorize issues — whether they’re security vulnerabilities, readability concerns, or maintainability challenges. And of course, security is always a major concern. Here’s an example — this is a user-controlled code vulnerability, which could

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Synthetic data takes aim at AI training challenges

This blending process can create domain- or context-specific data that can be a huge benefit to users, Frankle adds. “It can be very powerful, because it can help you get exactly the right data you want, exactly the right, behaviors, properties, and shape of data you want,” he adds. One good use of synthetic data would be to train autonomous cars when they need to hit the brakes, Mostly AI’s Ebert says. Instead of filming millions of hours of video showing multiple weather conditions, obstacles, and other potential variables, car makers can use synthetically generated visuals to mimic real-world conditions. “We can use seed data, so some videos of rabbits or kids or whatever you want to train on, allowing us to create these millions of distinct examples which are still realistic,” she says. source

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