Improving visibility and control in digital trust

The Cloud Security Alliance's new AI Controls Matrix (AICM) is a game-changer for AI security—and identity governance is at its core. I’m proud to have contributed, especially to the 30+ controls focused on Data Security, Privacy, and Identity & Access Management. Why this matters: AI’s explosive growth demands modern identity security—real-time visibility, least privilege, and automated governance across human and non-human identities, clouds, and platforms. Legacy IAM simply can’t keep up with the dynamic, cross-platform access patterns of today’s AI environments. Two Guiding Principles for Modern Identity Security: • Access Control Is Fundamental: Effective data security for AI cannot exist without robust, dynamic access controls. Proper governance over who (or what) can access sensitive data, models, and infrastructure is now a non-negotiable requirement for safe AI adoption. • AI Demands a Modern Identity Paradigm: Today’s cloud-native and AI-driven environments introduce new access patterns—service accounts, cross-platform permissions, federated human and non-human identities, and indirect, inherited privileges. Legacy approaches are no longer sufficient. I anchored my contributions on two new control recommendations: • Access Intelligence: Real-time visibility into permission grants and active paths, supported by risk analytics—essential for staying ahead of evolving threats. • Dynamic Access Governance: Automated detection of toxic combinations and continuous monitoring for compliance gaps, providing a resilient framework as AI environments scale. Bottom line: As organizations adopt AI at scale, robust, real-time identity governance isn’t optional—it’s fundamental to digital trust. Kudos to CSA and all the contributors for raising the bar. Read more here: https://lnkd.in/eeXXyXdG #AIsecurity #IdentitySecurity #AICM #CloudSecurityAlliance #AccessControl

𝐎𝐧𝐞 𝐥𝐞𝐬𝐬𝐨𝐧 𝐦𝐲 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 𝐚 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐭𝐞𝐚𝐦 𝐭𝐚𝐮𝐠𝐡𝐭 𝐦𝐞 𝐚𝐛𝐨𝐮𝐭 𝐔𝐒 𝐜𝐨𝐧𝐬𝐮𝐦𝐞𝐫𝐬: Convenience sounds like a win… But in reality—control builds the trust that scales. We were working to improve product adoption for a US-based platform. Most founders instinctively look at cutting clicks, shortening steps, making the onboarding as fast as possible. We did too — until real user patterns told a different story. 𝐈𝐧𝐬𝐭𝐞𝐚𝐝 𝐨𝐟 𝐫𝐞𝐝𝐮𝐜𝐢𝐧𝐠 𝐭𝐡𝐞 𝐣𝐨𝐮𝐫𝐧𝐞𝐲, 𝐰𝐞 𝐭𝐫𝐢𝐞𝐝 𝐬𝐨𝐦𝐞𝐭𝐡𝐢𝐧𝐠 𝐜𝐨𝐮𝐧𝐭𝐞𝐫𝐢𝐧𝐭𝐮𝐢𝐭𝐢𝐯𝐞: -Added more decision points -Let users customize their flow -Gave options to manually pick settings -instead of forcing defaults -Conversions went up. -Engagement improved. Most importantly, user trust deepened. You can design a sleek two-click journey. But if the user doesn’t feel in control, they hesitate. Especially in the US, where data privacy and digital autonomy are non-negotiable — transparency and control win. Some moments that made this obvious: People disable auto-fill just to type things in manually. They skip quick recommendations to compare on their own. Features that auto-execute without explicit consent? Often uninstalled. It’s not inefficiency. It’s digital self-preservation. A mindset of: “Don’t decide for me. Let me drive.” I’ve seen this mistake cost real money. One client rolled out an automation that quietly activated in the background. Instead of delighting users, it alienated 20% of them. Because the perception was: “You took control without asking.” Meanwhile, platforms that use clear prompts — “Are you sure?” “Review before submitting” Easy toggles and edits — those build long-term trust. That’s the real game. What I now recommend to every tech founder building for the US market: Don’t just optimize for frictionless onboarding. Optimize for visible control. Add micro-trust signals like “No hidden fees,” “You can edit this later,” and toggles that show choice. Make the user feel in charge at every key step. Trust isn’t built by speed. It’s built by respecting the user’s right to decide. If you’re a tech founder or product owner, stop assuming speed is everything. Start building systems that say: “You’re in control.” 𝐓𝐡𝐚𝐭’𝐬 𝐰𝐡𝐚𝐭 𝐜𝐫𝐞𝐚𝐭𝐞𝐬 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧 𝐭𝐡𝐚𝐭 𝐬𝐭𝐢𝐜𝐤𝐬. 𝐖𝐡𝐚𝐭’𝐬 𝐲𝐨𝐮𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐰𝐢𝐭𝐡 𝐭𝐡𝐢𝐬? 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬. #UserExperience #ProductDesign #TrustByDesign #TechForUSMarket #businesscoach #coachishleenkaur LinkedIn News LinkedIn News India LinkedIn for Small Business

The Blueprint for Data Trust is Here Stop Governing. Start Enforcing.   The Provocation
 In today’s AI-driven enterprise, data quality is not a metric, it’s resilience itself. A recent dialogue revealed a core challenge:
   “These practices aren’t just about improving ‘data quality’… they’re about resilience.”
   This insight became our catalyst. If resilience is the true target, what does an actionable Blueprint look like? So we built it - driven by this very provocation.   Three Non-Negotiables for Data Trust 1.    Contracts Must Be Alive
 Metadata contracts, without active enforcement, are nothing but architectural theater. The strongest systems convert policy breaks into real-time alerts and automated tagging, creating closed accountability loops for both producers and consumers. 2.    Lineage Demands Context
 Visibility without accountability is risky. Lineage must be enriched with SLA tags, PII flags, and consumer priorities - transforming simple observability into enforceable governance. Omitting these tags leaves teams exposed to procedural and regulatory failures. 3.    Ingestion Is Security
 Ingestion is now a strategic security checkpoint. Deduplication and validation at this stage aren’t just best practices, they’re frontline breach detectors. In complex AI pipelines, a single corrupted upstream event can cascade undetected, causing system-wide impact.   The Blueprint The Data Trust Architecture Blueprint serves CDOs, CIOs, and platform leaders who demand real outcomes: ·     Enforce trust in real time: Move your approach from passive governance to active, policy-driven enforcement. ·     Automate resilience: Embed blast-radius-aware lineage and self-healing contracts into every pipeline, drastically reducing incident response times. ·     Secure AI & ML futures: Align your platforms with evolving standards for AI risk mitigation, explainability, and ethical oversight. ·     Eliminate fire-drills: Replace costly clean-ups with resilient-by-design operations for lasting business impact.   What’s Next This is Version 1.0, a living blueprint. It’s not just a framework; it’s an executive-led movement to redefine data trust for the age of AI. Your experience and feedback will shape its ongoing evolution and practical value.   Download the Data Trust Architecture Blueprint. Let’s build more than data platforms. Let’s build trust   Transform Partner – Your Strategic Champion for Digital Transformation

🔐 User-Centric Credentialing & Personal Data Sharing: Rethinking Data Ownership and Digital Trust I came across a powerful concept that’s redefining how we think about data and identity, while exploring Digital Public Infrastructure (DPI) and Government Digital Transformation. That is User-Centric Credentialing & Personal Data Sharing — a vision spearheaded by Centre for Digital Public Infrastructure - CDPI and already being adopted in countries like India, Brazil, and across the EU. 📄 You can read the full vision paper here: https://vc.cdpi.dev/ 🎯 The Problem: Most of our data—academic records, financial info, medical history—sits locked in institutional silos. Whenever we need to prove something, we must go back to those institutions, again and again. This system is inefficient, exclusive, and often inaccessible to those without digital privilege. 🔄 The Shift: Instead of relying on fragile paper documents or non-verifiable PDFs, Verifiable Credentials (VCs) allow individuals to receive cryptographically signed, tamper-proof data directly from the source—and hold it themselves. Your credentials live in a digital (or even printable) wallet, ready to be presented anywhere, anytime. 🧩 Why this matters: 🚫 No more redundant verification loops or complex API integrations 💸 Individuals and SMEs can unlock low-cost, high-trust access to loans and services 🌐 Cross-border, cross-sector data sharing becomes truly scalable 🔐 Privacy-preserving tech like selective disclosure and zero-knowledge proofs lets users control what they share 💼 Real-World Use Cases: 🚜 Farmers accessing government subsidies 🎓 Students applying for global jobs or education 🛒 Micro-entrepreneurs seeking credit 🌱 Green energy prosumers trading surplus power 🔧 How it works — The Technology: ✅ Verifiable Credentials (VCs) Issued by trusted institutions (banks, hospitals, universities) Tamper-evident and cryptographically signed Verifiable without contacting the issuer Works online, offline, and across borders 🌍 Decentralized Identifiers (DIDs) Globally unique, user-owned digital identifiers Enable selective disclosure and zero-knowledge proofs Not tied to any centralized registry or country 🧠 The Architecture: Trust Without Friction 🟩 Issuer → signs and issues the credential 🟦 User → stores it in a wallet (smartphone, cloud, or paper with QR) 🟨 Verifier → verifies it cryptographically, without needing the issuer again This model eliminates the need for bilateral system integrations. Just one connection: the user. It’s asynchronous, scalable, and privacy-respecting. 🌐 Why this matters for the future: 📲 Anyone, even without advanced tech access, can participate 🛠️ Institutions issue once and never worry about re-verification 🔐 Built on open standards, decentralized architecture, and zero-trust principles Ministry of Digital Economy - Sri Lanka Information Communication Technology Agency of Sri Lanka

Putting VCO & DNA principles into Practice: It’s governance with a human touch. Data platform admins often get a bad rap as the “Department of No,” those apparent villains who impose limits and wield red tape. But guess what? There is no right approach that can flip that script. By embracing a couple of core governance principles, admins conciously or subconsciously enable the business confidently. Two of my favorite guiding principles in modern data platforms are conveniently known as VCO and DNA (and no, not the kind from biology class!😉). Admins aren’t villains—they’re just the ones holding the seatbelt while everyone else floors the gas(data culture & health). 🦹♂️🦹♀️ Two core principles I keep seeing in well-architected platforms (thanks Snowflake for inspiring this!) are: #VCO → Visibility, Control, Optimize 🎚️ #DNA → Detect, Notify, Act 🧬 And they align beautifully.If VCO is the strategy, DNA is the action plan: 🔍 Visibility ↔ Detect – You can’t manage what you can’t see ⚙️ Control ↔ Notify – You can’t react to what you don’t hear 🚀 Optimize ↔ Act – You can’t improve what you don’t address Snowflake exemplifies these ideas through its platform capabilities in observability, alerts, monitoring, and cost control: - #Visibility: Offers rich observability tools and logs for full transparency. From usage dashboards to query history and data lineage, you get a clear window into what’s happening (no more dark corners or “mystery” spend). - #Control: It provides fine-grained guardrails to keep things on track – think role-based access controls and resource monitors that prevent runaway costs. You can even set policies like max query run time to stop those never-ending queries in their tracks . Governance by design means fewer nasty surprises. - #Optimize: It continuously tunes performance and cost-efficiency. Features like auto-suspend and auto-scale for warehouses, query optimization services, and usage analytics help ensure you’re getting the most bang for your buck. Optimization isn’t a one-time task, it’s an ongoing mindset (and Snowflake makes it feel almost automatic). - #Detect & #Notify: Built-in monitoring and alerting features constantly detect issues or threshold breaches and notify you in real time. Define custom alerts in SQL or use Snowflake’s system-defined alerts – if something deviates (e.g. sudden failure, unexpected cost spike), you can get an email, Slack, PagerDuty ping, you name it. The right folks get the right info at the right time. - #Act: Here’s where the magic comes in – Snowflake can often act automatically on what it finds. For example, a monitoring alert can trigger a warehouse to suspend before overspending , or you can set up tasks to run remediation SQL when an alert condition is met. In many cases, the platform takes immediate action (or equips you to do so with one click), closing the loop without drama🎭 #DataGovernance #DataTrust #Observability #Snowflake #AdminLife