CIO CIO

I’ll start with a high-level architecture of what an agentic system might look like. You might be building your own agents, or using off-the-shelf ones like copilots or coding agents. We have an open-source project called KAgent that allows you to build agents quickly on top of Kubernetes. The important part is these agents communicate with AI models or LLMs, with other agents, and with backend APIs—called tools. But those protocols like MCP or A2A don’t natively provide security. When you give an agent access to APIs and workflows inside your enterprise, you want authentication, fine-grained authorization, and auditability. You want to know the path the agent took. These things communicate over the network, and that’s why we built a new open-source project at Solo called Agent Gateway. It understands MCP and A2A protocols and can enforce security, collect metrics, provide tracing, and more. So the demo I’m showing is about Agent Gateway. If we go to GitHub and look up Agent Gateway, you’ll see the project. It’s built in Rust, which is important for performance and resource usage. The proxy is configured via a JSON file—or optionally using an XDS-type protocol, which I won’t demo today. With the JSON file, we can define a single endpoint that clients can connect to, which then routes to multiple backend MCP servers. Each of those servers can expose its own tools, and now you can apply governance and policy on top. Agent Gateway has a UI. We can see the exposed listeners, the target MCP servers, and tools available. For example, you might see tools like Everything Echo or Everything Else Add. It’s helpful to visualize the tools available. Now, what if you have RESTful APIs and want to expose them over the MCP protocol? Let’s take a look at OpenAPI. We’ll run the proxy in OpenAPI mode. If you check out the config, you’ll see we’re now proxying not just MCP servers, but an OpenAPI REST service as well. When I refresh and look at our targets, we see that the Pet Store backend is a RESTful API—exposed to MCP clients, making it available in agents or LLMs. When we connect to the playground, we can see both the Everything Server tools and Pet Store tools. If I call something via MCP, Agent Gateway performs the transformation between MCP and REST automatically. Lastly, let’s look at authentication, authorization, and policies around MCP. The JSON file specifies that a JWT token must be included in the HTTP request. The policy says: “Yes, you can access this, but only the Echo tool.” So if I try to connect without the token—no luck. I’ll go find the right token (hopefully it’s in the README). Got it. I’ll paste that in, connect… and we’re in. Now, remember—our policy only allows the Echo service. If I try to use the Add tool (say, 1 + 2), nothing happens, because I’m not authorized. But if I call the Echo tool—say “Hello, Agent Gateway”—it works successfully. Agent Gateway is just one piece of the agentic puzzle. It enforces security, observability, and guardrails between agents and LLMs, between agents and other agents, and between agents and backend MCP tools. We also include a registration portal for governance—approval workflows, agent registration, and tool management. This is what we’re calling Agent Mesh, and I believe Solo.io is leading the cloud-native community in building these tools. source

What makes a customer experience truly effective? What drives a smarter business decision or a more impactful AI initiative? Answering questions like these increasingly comes down to one core thing: data. As enterprise operations evolve and organizations embrace cloud platforms to power AI and advanced analytics, the ability to fully harness data has become more complex, but it has also never been more critical. For many companies, the most valuable data still resides in long-standing core transactional systems – systems that were never designed with modern analytics or AI in mind. These core systems sometimes hold decades of insights, yet poor visibility, fragmented governance, and entrenched data silos often prevent that data from being fully utilized. Adopting and translating AI and advanced analytics into favorable business outcomes starts with addressing common barriers to adoption while building trust and transparency into the framework. Roadblocks on the path to AI and advanced analytics Among the roadblocks to AI and advanced analytics success is data access. As organizations lean into multiple IT environments, across on-premises and cloud, data silos scattered enterprise-wide can mean an AI model, application, or analytics tool runs with faulty information. This is particularly true when attempting to bridge the gap between mainframe systems – a place where often the most sensitive and crucial transactional information is stored – and cloud environments. In fact, Rocket Software research found that 76% of IT leaders reported difficulty accessing mainframe data and contextual metadata. Even if an enterprise gets past that first data access hurdle, the question then turns to, “Can this data be trusted?” When dealing with multiple environments, data can move frequently from one place to another. That activity presents a data lineage challenge. What data is your AI initiative tapping into? Where did it come from? Has it been manipulated? Is it maintained in line with data governance best practices? Without an answer to questions like these, any resulting business decisions may be unreliable. Then there’s the complex web of security and regulatory compliance that comes with effectively managing that data. These applications and tools leverage data that is often highly sensitive. As a result, organizations need to be prepared for what has become a rapidly shifting regulatory landscape—from DORA to PCI DSS 4.0. Bringing blind spots into the light Addressing these roadblocks boils down to how well enterprises can bridge the divide between on-premises systems and hybrid cloud environments. Integrating the right tools can help break through these blockers. With data intelligence capabilities, like those in the Rocket DataEdge suite, IT leaders gain a powerful means to map data across their entire IT landscape, discover data more effectively, and build trust. The solution suite is purpose-built to integrate and optimize data operations across diverse environments, including mainframe, distributed, and cloud. Solutions like this help eliminate blind spots by enabling key functionality such as real-time data streaming, transformation, and movement across systems to ensure data is accessible, trusted, and actionable wherever it’s needed. They also add automated lineage tracking and metadata management, offering a much clearer picture of how data flows through an organization, increasing trust in analytics outputs and ensuring regulatory compliance. No matter what, AI integration can’t come at the cost of data protection. With the right data management solutions, enterprises can take advantage of embedded access controls, audit logging, and compliance frameworks, bringing each directly into their data workflows. At a time when AI initiatives are expanding rapidly, this builds a strong foundation to maintain trust and security at scale. Elevating AI and advanced analytics By confronting these blind spots head-on and adopting integrated solutions that work across a mix of on-premises and cloud systems, enterprises can fully unlock the value of their data. Learn more about how Rocket Software can help break down some of the most common challenges with AI and advanced analytics. source

Westcon-Comstor will be hosting its Imagine Series event, themed Resilient Futures: Harnessing Cloud Power in Shifting Economies. Back for its 18th year, attendees of this event will have exclusive opportunities to explore industry-relevant topics on how innovative cloud solutions can transform the way businesses achieve resilience and growth in an ever-evolving economic landscape. Over the years, the Imagine Series event has become a benchmark for innovation, collaboration, and thought leadership in the IT industry, making it a must-attend for professionals and organisations alike. “Our Imagine Series 2025 event is designed to empower our local IT industry with the knowledge and tools they need to navigate the rapidly evolving market landscape,” said Dave Rosenberg, Managing Director, New Zealand at Westcon-Comstor. “By embracing cloud technology, we can drive significant growth and productivity gains for our partners and their customers.” New Zealand’s growing technology sector meant the need for effective cloud adoption. This aligns with Westcon-Comstor’s Mastering the Maze report, which showed that 91% of New Zealand-based respondents see developing a cloud practice as a priority. “This event is a unique opportunity to delve into the transformative power of cloud solutions and understand how they can be harnessed to foster resilience and growth in our businesses,” added Rosenberg. He will be sharing key business updates, insights, and observations on the market and how the Imagine Series 2025 will propel enterprises to make future-ready decisions. During the event, attendees will get deep insights from key industry leaders and explore the latest cloud insights and solutions through various exhibitions, learning ways to navigate current product, industry, business, and market trends. Westcon-Comstor is incredibly fortunate to have Shaun Quincey, CEO and Co-Founder of Simfuni, as the keynote speaker for the event. Shaun brings a truly inspiring story of resilience as the only individual to have rowed solo across the Tasman. He will share insights from this remarkable journey and how it continues to shape his innovative leadership at Simfuni, which has been recognised as the Insurtech Start-up of the Year in 2023. Guiding the conversation during the panel discussion will be Cathy O’Sullivan, Foundry’s ANZ Editorial Director, drawing on her deep industry knowledge and sharp editorial acumen. With a proven track record of uncovering key trends and fostering meaningful dialogue, Cathy aims to extract actionable insights from industry leaders. She’ll be joined by an exceptional panel featuring Lisa Postlewaight, New Zealand Country Director at Equifax, and Kenny Thein, IT Director at Restaurant Brands. Together, they’ll explore timely topics such as innovative strategies for managing IT budgets, offering attendees a rich blend of expert perspectives and practical takeaways. Vendor sponsors include Amazon Web Services (AWS), Cisco, VMware, Symantec, Palo Alto Networks, Splunk, F5, Cohesity, Ericsson, and Pure Storage solutions. “We are thrilled to have Amazon Web Services (AWS) as our Diamond sponsor for this highly anticipated industry event and are looking forward to coming together to demonstrate innovation and excellence together with all our local industry leaders. Both AWS Cloud Services and procuring ISV solutions from the AWS Marketplace have the potential to unlock growth opportunities for channel partners and we look forward to showcasing how it can further empower the channel in the cloud marketplace economy”, said Jacquie Young, Managing Director, Cloud, APAC at Westcon-Comstor. The Imagine Series 2025 event will be held on Wednesday, 18th June 2025, at the Pullman Hotel in Auckland. For those unable to attend in person, the event will also be live-streamed into Wellington and Christchurch, with an option to participate virtually. For registration details, please visit: Imagine Series 2025 – Resilient Futures. source

What Google and Microsoft have in mind is something completely different, not just superficially but fundamentally, writes CS editor-in-chief Marcus Jerräng in a column. source

Target audience: Customers in the broader Google ecosystem. Notable features: Looker is known for its composability, with a modular architecture that enables headless BI integration with other analytics and BI platforms. Pricing: By request; pricing has two main components: platform pricing and user pricing. Microsoft Fabric Microsoft Fabric is Microsoft’s unified, AI-powered data analytics platform, supporting both data management and analytics. It consolidates data movement, processing, storage, analysis, and visualization into a single stack. Microsoft has incorporated Power BI into Fabric to support data preparation, visual-based discovery, interactive dashboards, and augmented analytics. And Fabric has augmented Power BI’s capabilities with advanced analytics and ML functions. These capabilities enable Fabric to generate insights, automate tasks, and build predictive models. Target audience: Microsoft shops. Notable features: Integration with Power BI, Azure, and Microsoft 365; Copilot for Power BI. Pricing: Pay-as-you-go or capacity reservation. Oracle Analytics Oracle has spent the past several years bulking out its Oracle Analytics offering, launched in 2014 as an outgrowth of its flagship Business Intelligence Enterprise Edition suite. In 2020, it added a Cloud HCM offering to provide self-service workforce analytics to HR executives, analysts, and LOB leaders. Oracle has also focused on making its cloud offering intuitive and user-friendly, with powerful reporting and ML features. Other key features include data preparation, data connectors, visualizations, predictive analytics, a native mobile app, and support for embedded analytics. Regarding AI, Oracle has added document understanding to its existing vision, text, and language capabilities, enabling the use of gen AI to create data stories. Additionally, Fusion Data Intelligence, Oracle’s cloud-based analytics warehouse platform can be associated with Oracle Analytics to enable these features by embedding analytics and AI into business applications and workflows. Target audience: Users in midsize to large enterprises. Notable features: Conversational analytics support natural language queries; can automatically generate natural language explanations to explain visualizations and trends. Pricing: Enterprise: $80 per user, per month; Professional: $16 per user; Professional – Bring Your Own License (BYOL): $0.3226 Oracle compute unit (OCPU) per hour; Enterprise – BYOL: $0.3226 OCPU per hour. Pyramid Analytics Pyramid Analytics is a business and decision intelligence platform built from the ground up on ML-based data preparation and data wrangling. Its multi-LLM strategy offers customers flexibility, and the platform is deployment-agnostic, enabling customers to host it in AWS, Microsoft Azure, Google Cloud Platform, Oracle Cloud, Alibaba, or on-premises. Users can leverage Pyramid’s own internal portable language model or third-party LLMs with the platform’s NLQ interface for text and speech input and output. source

“They want their brand to be seen as AI-first but often apply it to non-urgent problems — like experimenting with content generation, for example, instead of identifying a core business issue to fix,” he says. “It’s not about simply jumping on the AI train. It’s about being sure that you’re riding it in the right direction and that you even need it in the first place.” Not enough expertise Many IT and business leaders have rushed into AI adoption without considering internal expertise or the need to sell the technology to internal users, prompted in part by a fear of missing out, Navodnyy contends. “When leaders feel the pressure to move fast just to stay competitive, they can sometimes skip critical steps, prioritizing deployment speed over product quality,” he explains. “That’s a very reckless approach, and an easy way to end up with wasted resources and damaged reputation.” source

“Increasingly, the CIO is expected to help drive a difference at the front end as the lines blur between products, services, and technology, improving the customer experience, and supporting revenue and growth,” says White, adding that the forthcoming Nash Squared Digital Leadership Report suggests two-thirds of CIOs believe their CEOs need technology to make rather than save money. The trend, suggests Eric Johnson, CIO at technology specialist PagerDuty, is a shift to a new type of digital leader who works in concert with senior colleagues to deliver what he refers to as high-impact results across a range of areas. “CIOs have gone from making sure the phones and networks are working, which is critical, to driving digital transformation, with a focus on leveraging data in generative AI, automation, and proactive cybersecurity projects to deliver tangible business benefits,” he says. “This proactive stance toward business alignment is crucial for modern CIOs.” source

SAP (NYSE:SAP) and Amazon Web Services (AWS) have launched an AI Co-Innovation Program, offering dedicated technical resources and cloud credits to help enterprises embed AWS generative AI tools into their ERP systems. The first to profit from the program, unveiled at SAP’s Sapphire customer conference, are IT services companies building domain-specific AI agents for their customers to streamline core functions such as financial forecasting, delivery planning, and supply chain optimization. “There isn’t a distinct technical framework for the program, but rather it’s the combined expertise, resources, and selection of models through Amazon Bedrock that will help accelerate the development of industry and use case-specific generative AI agents and applications,” said an AWS representative. source

“For Salesforce customers, this represents a major advancement. They can now seamlessly access and leverage all types of customer data—whether housed within Salesforce or external systems—in real time. This enhanced capability establishes a unified customer data fabric, delivering actionable insights across every channel and touchpoint,” Yuhanna said. “Critically, it accelerates Salesforce’s ability to deploy agentic AI, enabling low-code, low-maintenance AI that reduces complexity and dramatically shortens time to value.” For Informatica customers, Yuhanna said, “the opportunity is equally appealing. This acquisition unlocks a faster path to agentic AI workloads, backed by the reach and power of the Salesforce ecosystem. As data management evolves, intelligent agents will automate core functions, turning traditionally time-consuming processes like data ingestion, integration, and pipeline orchestration into self-operating data workflows.” “Tasks that once took days—or even weeks— will be executed with little to no human intervention,” Yuhanna said. “With a unified data, AI, and analytics platform, Informatica customers will benefit from accelerated innovation, greater operational agility, and significantly enhanced returns on their data investments.” source

Every day, thousands of people are diagnosed with cancer around the world. Each case is unique, with hundreds of distinct tumor subtypes that require treatment protocols involving new drugs, clinical trials, and device-based therapies. Leading cancer centers, therefore, rely heavily on multidisciplinary tumor boards, or specialized sessions where radiologists, pathologists, surgeons, oncologists, genetic counselors, and other specialists perform sophisticated analyses of vast amounts of patient data and parameters to develop personalized care plans.   A recent study by the American Society of Clinical Oncology (ASCO) found physicians spend between 1.5 and 2.5 hours per patient meticulously reviewing images, pathology slides, clinical notes, and genomic data. In this context, agentic AI has extraordinary potential to reduce admin friction and transform how medical services are delivered. [ Related: Agentic AI – Ongoing news and insights ] At Microsoft Build 2025 earlier this month, Nigam Shah, CDO for Stanford Health Care, discussed agentic AI’s ability to redefine healthcare, especially in oncology, as physicians get overloaded with the administrative tasks of medicine, he said, which lead to burnout. “Add to this that medical knowledge doubles every 60 or 70 days, so it’s very difficult to keep up with the medical literature,” he added. source