Importance of Technology Integration

Today, Google introduced its new Agent2Agent protocol —a key step toward a future of AI Agent interoperability— and Box is announcing support for it. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

CTO: Can we skip code documentation for this sprint? We’re tight on deadlines. Software Developer: Skip documentation? How will the next dev understand what we built? CTO: We’ll figure it out later. Code is self-explanatory, right? Software Developer: Code explains what it does. Documentation explains why it does it. Without context, even clean code becomes a puzzle. CTO: But we need to move fast. Software Developer: Move fast today, stall tomorrow. Good docs are how teams scale and survive turnover. Write for the next developer — even if that's you in six months. Lesson: 🔘 Code is for computers. Documentation is for humans. 🔘 Undocumented systems rot faster than badly written ones. 🔘 Speed without clarity is just deferred confusion.

A.I. is a Survival Kit for Telcos Telecom operators are in survival mode. That’s the hard truth. Over the last decade, their financials have deteriorated despite massive investments in network infrastructure. Revenues are stagnating. Margins are shrinking. Costs are rising. The math doesn’t add up. Most telcos today are running below their cost of capital, making them unattractive investments. The numbers tell a brutal story. Global telecom revenue growth has been stuck at low single digits, barely keeping up with inflation. The industry spends over $300 billion annually on CAPEX by laying fiber, expanding 5G, and modernizing networks, yet monetization remains a challenge. Meanwhile, OPEX is eating up 65-70% of total revenue, with network operations alone projected to consume 50% of total OPEX by 2027. Energy costs have surged, with telecom networks consuming 2-3% of global electricity and growing. The cost of serving customers has skyrocketed, as call centers, support teams, and maintenance operations strain under the weight of increasing complexity. It is an economic equation that no longer works. Investors have noticed. Since 2018, telcos’ market capitalization has only grown by 7%, while digital platforms have surged by 230% and the S&P 500 by 172%. Debt levels are climbing, return on investment is shrinking, and competition from "Techno" players has further eroded traditional revenue streams. Customers are paying less, expecting more, and are more willing than ever to switch providers for better deals. The industry is stuck in a loop: spending more every year just to maintain the same level of service while profitability continues to decline. The harsh reality is that no amount of cost-cutting, restructuring, or incremental efficiency gains will fix this. The only viable survival strategy is AI. This is not an AI initiative. Not AI in pockets of the business. But AI as a platform. AI should be embedded into every layer of the telco value chain: from sales and marketing to customer support, from network operations to predictive maintenance, from fraud detection to revenue assurance. AI is not an enhancement. This is the way forward. The impact is not just theory. AI-driven automation is already proving it can reduce network operations costs by up to 30% by enabling self-optimizing networks, predictive maintenance, and real-time anomaly detection. AI-powered customer interactions are slashing workload by as much as 50%, resolving inquiries without human intervention. AI-led marketing and recommendation engines are increasing conversion rates by 25%, driving upsell opportunities and reducing churn. AI-driven fraud detection is saving telcos billions annually by identifying and stopping threats in real time. Survival depends on scale. AI must be adopted across every process, every function, every department. The transformation required is radical, but so is the alternative...irrelevance.

All risk is enterprise risk. Cybersecurity Risk Management (CSRM) must be part of Enterprise Risk Management (ERM). Many companies think managing cyber risks is: ╳ Just an IT problem. ╳ Isolated from other risks. ╳ A low-priority task. But in reality, it is: ☑ A key part of the entire risk strategy. Here are the key steps to integrate cybersecurity risk into enterprise risk management: 1. Unified Risk Management ↳ Integrating CSRM into ERM helps handle all enterprise risks effectively. 2. Top-Level Involvement ↳ Top management must be involved in managing cyber risks along with other risks. 3. Contextual Consideration ↳ Cyber risks should be considered in the context of the enterprise's mission, financial, reputational, and technical risks. 4. Aligned Risk Appetite ↳ Align risk appetite and tolerance between enterprise management levels and cybersecurity systems. 5. Holistic Approach ↳ Adopt a holistic approach to identify, prioritize, and treat risks across the organization. 6. Common Risk Language ↳ Establish a common language around risk that permeates all levels of the organization. 7. Continuous Improvement ↳ Monitor, evaluate, and adjust risk management strategies continuously. 8. Clear Governance ↳ Ensure clear governance structures to support proactive risk management. 9. Digital Dependency ↳ Understand how cybersecurity risks affect business continuity, customer trust, and regulatory compliance. 10. Strategic Enabler ↳ Prioritize risk management as both a strategic business enabler and a protective measure. 11. Risk Register ↳ Use a unified risk register to consolidate and communicate risks effectively. 12. Organizational Culture ↳ Foster a culture that values risk management as important for achieving strategic goals. Integrating cybersecurity risk into enterprise risk management isn't just a technical task. It's a strategic necessity. 💬 Leave a comment — how does your company handle cyber risk? ➕ Follow Andrey Gubarev for more posts like this

DevOps fosters a 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗼𝗳 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿𝗲𝗻𝗰𝘆, 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝘀𝗵𝗮𝗿𝗲𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 across the entire software delivery lifecycle. Here's why understanding DevOps is crucial for each key player: 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: Faster feedback: DevOps promotes 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 (𝗖𝗜/𝗖𝗗), enabling developers to receive feedback on their code 𝗺𝗼𝗿𝗲 𝗿𝗮𝗽𝗶𝗱𝗹𝘆, leading to higher quality and fewer bugs. Infrastructure as code: By understanding infrastructure as code (IaC), developers can 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗽𝗿𝗼𝘃𝗶𝘀𝗶𝗼𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗶𝗼𝗻, reducing manual effort and ensuring consistency across environments. Enhanced ownership: DevOps encourages developers to 𝘁𝗮𝗸𝗲 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗼𝗳 𝘁𝗵𝗲𝗶𝗿 𝗰𝗼𝗱𝗲 𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗼𝘂𝘁 𝗶𝘁𝘀 𝗲𝗻𝘁𝗶𝗿𝗲 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲, from development to production, fostering a sense of responsibility and accountability. 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗔𝘀𝘀𝘂𝗿𝗮𝗻𝗰𝗲 (𝗤𝗔): Shift-left testing: DevOps enables QA to 𝗺𝗼𝘃𝗲 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 𝗲𝗮𝗿𝗹𝗶𝗲𝗿 in the development process, catching issues sooner and preventing them from reaching production. Automated testing: Leveraging automation tools in DevOps allows QA to perform 𝗺𝗼𝗿𝗲 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗮𝗻𝗱 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝘁𝗲𝘀𝘁𝗶𝗻𝗴, freeing up time for exploratory and manual testing. Continuous monitoring: DevOps promotes continuous monitoring throughout the pipeline, giving QA deeper insights into application performance and potential issues. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗢𝘄𝗻𝗲𝗿𝘀: Faster time-to-market: DevOps accelerates the delivery cycle, enabling product owners to 𝗴𝗲𝘁 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝘂𝗽𝗱𝗮𝘁𝗲𝘀 𝗶𝗻𝘁𝗼 𝘂𝘀𝗲𝗿𝘀' 𝗵𝗮𝗻𝗱𝘀 𝘀𝗼𝗼𝗻𝗲𝗿, leading to faster feedback and iteration. Data-driven decision-making:*DevOps provides valuable data and metrics, giving product owners 𝗯𝗲𝘁𝘁𝗲𝗿 𝘃𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 into feature performance and user behavior, informing future product decisions. Improved collaboration: DevOps fosters closer collaboration between product owners and development teams, ensuring alignment on priorities and delivering products that truly meet user needs. 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀: Increased ROI Enhanced responsiveness Better communication and transparency 𝗕𝗲𝘆𝗼𝗻𝗱 𝟮𝟬𝟮𝟰: 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗗𝗲𝘃𝗢𝗽𝘀 As technology evolves, DevOps will continue to adapt and grow. Key trends to watch include: Artificial intelligence and machine learning (AI/ML): Automating tasks, predicting failures, and optimizing performance. Greater security integration: Securing the entire delivery pipeline. Focus on developer experience: Making development more efficient and enjoyable. Cloud-native everything: Leveraging the benefits of cloud infrastructure and services.

Is AR finally ready for the masses? With Apple’s Object Capture and similar innovations gaining momentum, we may finally be witnessing the democratisation of AR—no longer the domain of few experts, but a tool now slipping quietly into everyone’s pocket. The technology isn’t new—it's pretty old. But in recent times, I’ve started noticing something different—a rise in AR-driven experiences that feel tangible, creative, and purposeful. It’s not just potential anymore; it’s a serious progress. Picture this: you’re on vacation, wandering through a quaint alley or pausing beside a weathered sculpture. Instead of snapping a photo, you capture the object in full 3D—turning it into a living memory capsule that you can revisit, share, or even 3D print. Now imagine brands tapping into the same instinct. A parked bike, a street mural, a pop-up kiosk—each becomes an AR trigger. One scan unlocks a geo-personalized, time-sensitive experience tailored to that moment, that location, that individual. Personal storytelling meets hyperlocal advertising—merging memory, media, and marketing. What we’re seeing isn’t just a tech upgrade—it’s a shift in how experiences are designed, delivered, and felt. Let’s be realistic: I don’t see this replacing high-end 3D production anytime soon. But that’s not the point. What excites me isn’t what this disrupts—it’s what it enables. —Video Credit: AR Code #Helveticans #ObjectCapture #CreativeTech #3DDesign #ARMarketing #SpatialDesign #AugmentedReality #DesignInnovation #DigitalPossibilities #MarketingTech

🗞️ Just out! Latest from our NATO Strategic Communications Centre of Excellence ! “Democratising Data Integration” 🔹Examines the need for standardised data integration and communication protocols in NATO’s strategic information environment. 🔹 Core argument : while advanced data processing tools exist, the lack of standardised integration protocols limits efficiency, security, and rapid decision-making. 🔹Highlights the challenges of fragmented data systems, interoperability issues, and inconsistent data-sharing methodologies across allied organisations. Key Challenges 1. Metadata Standardisation – Inconsistencies in metadata structures lead to misinterpretations and operational inefficiencies. 2. Security Classifications – Differing classification methods create access restrictions, limiting data-sharing effectiveness. 3. Institutional Divergence – NATO allies use various data-sharing protocols, impeding interoperability. 4. Technical Expertise Gaps – The shortage of skilled personnel slows the adoption of modern integration frameworks. 5. Resource Constraints – Budgetary limitations restrict the transition to scalable and secure data systems. 6. Privacy and Compliance Issues – Conflicting regulations (e.g., GDPR) create legal and operational barriers. Proposed Solutions 🔹The report proposes adopting standardised communication protocols to ensure seamless interoperability. Frameworks like Federated Mission Networking (FMN) and VAULTIS are highlighted as potential models for structured data sharing. AI-driven solutions, automated classification systems, and improved governance mechanisms are recommended to enhance operational efficiency. Standardisation would lead to: 🔹Improved Strategic Communications – Faster, more reliable data-driven decision-making. 🔹Operational Efficiency – Reduced manual processing, better crisis response. 🔹Cost-Effectiveness – Lower integration costs through streamlined interoperability.

Three weeks ago I watched a young couple “move into” a condo that won’t exist for another 24 months. We were in the sales gallery—hard hats stacked in the corner, espresso machine hissing. Instead of glossy renderings, the team rolled out a digital twin on a big screen. The couple wandered through their future kitchen, nudged the island a foot, and checked how the sunset would hit the balcony in July. Ten minutes later they left a deposit. Here’s why developers are leaning on digital twins for pre-sales: Instant emotional hook – Buyers feel the space. “Unit 19B” becomes their living room, complete with the dog bed in the corner. Emotion closes deposits faster than any brochure. Customization without chaos – Swap cabinet finishes or stretch a closet in real time and see the price impact before drawings are locked. Global reach, local story – Overseas investors can tour the building from a phone at 2 a.m., while the sales rep narrates the neighborhood vibe live. Confidence for the lender – A living dashboard of reserved units, energy projections, and clash-free MEP layouts gives financiers fewer reasons to stall. Pre-sales used to rely on imagination and a leap of faith. Now we hand buyers a digital key and let them walk inside—turning that leap into a single, confident step. (And yes, we’re building these twins every day at Atlas Space.) Check it out the example here: https://lnkd.in/e7h33bQ6 #DigitalTwin #RealEstate #PreSales #PropTech #BuildSmarter

Legacy on-premise IT systems have a stranglehold on telco innovation. The AI-first future demands speed and agility that traditional software systems simply can't deliver. In the latest Telco in 20 podcast episode, Vodafone's Dr. Lester Thomas and I dive into how a radical new approach to IT is breaking down the barriers that have stalled telecom progress. While most operators debate whether cloud-native transformation is realistic, Vodafone is demonstrating not only is it doable — it's absolutely critical. We cover: • How Vodafone moved 17 petabytes of data from 600 Hadoop servers into Google Cloud to create their foundation for AI adoption • The company’s strict "cloud native" definitions have resulted in 80-90% of digital workloads being truly cloud native • The three principles Vodafone's Open Digital Architecture is based on: machine-readable standards, open-source collaboration, and proof-of-concept testing • Why AI is forcing complete software redesign at Vodafone, and how their AI Booster platform democratizes access while maintaining governance The operators who thrive won't be the ones doing IT the way it’s been done over the last 20 years. They'll be the ones bold enough to do the heavy lifting of truly becoming cloud-native and work to create a data platform that’s usable by AI so they are able to push the boundaries of what's possible in telecom. This is THE conversation to watch before you head to TM Forum’s DTW Ignite event in Copenhagen! If you missed the LinkedIn Live event you can watch the conversation on demand or listen to the audio only version on your favorite podcast player! Links in the comments. #Vodafone #telecommunications #cloudnative #AI #digitaltransformation

In today’s fast-evolving digital landscape, the convergence of Information Technology (IT) and Operational Technology (OT) is essential. From my experience working across industries like automotive and manufacturing, I see how integrating IT and OT can transform operations, boost security, and drive innovation. Here’s why this matters: 🔹 Unified Governance: Strong leadership and clear roles help align IT and OT efforts toward shared business goals. 🔹 Enhanced Security: OT systems benefit from IT’s cybersecurity expertise through standardised policies, regular updates, and centralised user controls, closing gaps that were once vulnerabilities. 🔹 Data-Driven Innovation: Seamless data flow across IT and OT enables new digital products and services, unlocking value and creating competitive advantage. Leading companies are already capitalising on this. 🔹 Empowered Teams: Bringing IT and OT professionals together fosters knowledge exchange and agility, which accelerates decision-making and drives business success. As we move deeper into Industry 4.0, embracing IT-OT convergence is a strategic imperative. India’s industries stand to gain massively by accelerating this integration, positioning us as global innovation leaders. Would love to hear your experiences with IT-OT convergence in your organisation. #DigitalTransformation #ITOTConvergence #Industry40