AI & Data Insider

AI coding models in 2025 now control IDEs, run terminal commands, debug their own code, and ingest 10 million tokens (entire legacy codebases) in a single prompt. The question for CTOs is no longer "Should we use AI?" but "Which specialised brain do we need for this task?" We have analysed every major release in 2025. Here are the 6 models that redefined developer workflows: → Claude 4.5 Sonnet: The new gold standard with "Computer Use" capability → OpenAI o3-pro: The senior architect with deep reasoning → Llama 4 Scout: 10M token context window (kills RAG pipelines) → DeepSeek-V3.2: Open-source disruptor rivaling GPT-5 class → Gemini 2.5 Pro: Watches bug videos and fixes code → Qwen3-Coder: 358 programming languages supported Swipe through for benchmarks, use cases, and key capabilities → Which model is transforming your workflow? Drop your experience in the comments. Full analysis: [Link in Comments] Anthropic OpenAI Meta DeepSeek AI Google DeepMind Alibaba Group #AI #Coding #DeveloperTools #CTO #TechLeadership #Claude #Llama #Gemini

Cloud strategy has moved from a purely technical discussion to a question of national alignment, risk, and trust. Gartner's data tells the story: → 60% of Western European CIOs expect geopolitical factors to drive reliance on local cloud providers → 75% of non-US enterprises will implement data sovereignty strategies by 2030 → Up from less than 5% today This shift—termed "geopatriation"—is now a Gartner top technology trend for 2026. The challenge: How do you gain jurisdictional control without losing access to the innovation and scale that made global hyperscalers attractive? The approaches: Organisations are exploring hybrid sovereign models, federated architectures, and regional specialisation—each with distinct trade-offs between compliance certainty and operational agility. Dmitry P., CEO and founder at emma ❘ Cloud Management Platform, breaks down the drivers, dilemmas, and strategic paths forward in his analysis for AI & Data Insider. Read "Geopatriation for Cloud Sovereignty: Why 75% Are Moving Home by 2030": Link in comments 👇 Is sovereignty becoming a boardroom topic at your organisation? #CloudSovereignty #Geopatriation #CloudStrategy #EnterpriseCloud

€5.88 billion in GDPR fines. €35 million maximum AI Act penalties. Rs 250 crore for India DPDP violations. $60 billion Africa AI Fund. £2 billion UK AI investment. 2025 was the year AI and data governance shifted from policy development to enforcement reality globally. This comprehensive year-end overview maps 22 major regulatory developments across six continents that fundamentally reshaped how organisations develop, deploy, and govern intelligent systems: Read the complete analysis covering all 22 developments on AI & Data Insider. Link in comments 👇 Which regulatory development will have the biggest impact on your organisation in 2026? #AI #Policy #Governance #2025 #EU #Regulation

A great piece from our Chief People Officer Ella Fordham as she offers a clear view of what truly makes humans irreplaceable in the AI age. Her perspective on judgement, creativity, adaptability and the shift toward a “human experience economy” is exactly the kind of conversation we need to be having as work transforms around us. At Beyond ONE, we put this into practice every day, hiring for potential, building learning pathways, and giving teams room to grow alongside new tech.

What makes humans irreplaceable in the AI age? "The truly valuable skills are those that cannot be automated: good judgement, creativity, the ability to listen, and the capacity to adapt to change that has no precedent." As AI creates 170 million new jobs by 2030, technical fluency alone won't differentiate talent. The skills that matter most are the ones that remain distinctly human. Ella Fordham, Group Chief People Officer at Beyond ONE, argues that we're entering the "human experience economy"—where success depends not just on deploying the best tools, but on building workplaces designed around people. Her insights challenge conventional approaches: → Hire for potential, not pedigree → Focus on "slope" rather than static achievements → Treat AI as cultural transformation, not just a system upgrade → Cultivate judgement, creativity, and adaptability in teams → Build environments where learning is embedded, not added on The article explores how organisations can grow human potential while integrating AI—and what individuals should focus on as the nature of work fundamentally shifts. As Fordham writes: "We cannot delay the conversation about the future of work. It is already underway." Read the full analysis on AI & Data Insider 👉 [Link in Comments] What human skills do you believe will be most valuable in the next decade? #FutureOfWork #AI #Leadership

99% cost reduction. 55% faster development. The right enterprise AI initiative depends on what you're trying to solve. This guide organises enterprise AI by business need: → Need productivity gains? Microsoft Copilot, Google Gemini, SAP Joule → Building custom AI? Amazon Web Services (AWS) Bedrock, Oracle OCI, Microsoft Azure OpenAI → CRM/Industry-specific? Salesforce, IBM watsonx, Anthropic Claude → Developer acceleration? GitHub Copilot, Databricks, Hugging Face → Autonomous agents? AWS Quick, Google Vertex, Meta Llama Swipe for ROI data from real deployments (353% returns, 99% cost cuts, 55% faster development) → Full comprehensive analysis on AI & Data Insider. Link in comments 👇 #EnterpriseAI #AIStrategy #BigTech

"As a good manager wouldn't tolerate a mysterious employee who refuses to explain their choices, organisations shouldn't accept 'black box' AI agents." This isn't just a clever analogy—it's a fundamental shift in how we think about AI governance. Kevin Kline, Database Evangelist at SolarWinds, argues that the rise of agentic AI requires IT leaders to borrow from HR's playbook. Why? Because AI agents are no longer passive tools. They're: → Reviewing error messages and resolving issues autonomously → Drafting incident reports after network disruptions → Making decisions that previously required human judgment In other words, they're functioning like junior team members. And just like junior team members, they need: Structure – Clear task definitions and autonomy boundaries Access control – Appropriate permissions, not blanket admin rights Oversight – Human-in-the-loop for important decisions Transparency – Explainable logic that can be audited Evaluation – Ongoing monitoring and feedback Kline's article maps each of these needs to a specific AI by Design principle and its HR equivalent, from "background checks" (privacy & security) to "performance reviews" (accountability & fairness). The payoff? AI agents that become trusted colleagues instead of unpredictable variables. As organisations deploy more autonomous AI systems, the question isn't whether to manage them—it's how to manage them well. Read Kevin Kline's complete framework on AI & Data Insider. Link in comments 👇 Is your organisation prepared to manage AI agents as team members? #AIGovernance #AgenticAI #EnterpriseAI #TechLeadership #ResponsibleAI

Language diversity in AI: 2025 year-end overview. From Switzerland's 1,000-language Apertus to India's 350+ AI models, this was the year multilingual LLM development became a global priority. Swipe for highlights across: → Major tech companies (Meta, Google, Cohere, Alibaba) → Asia & Middle East initiatives → European collaborations → Latin American partnerships → African innovation Full comprehensive overview covering 50+ developers, 40+ countries, and key trends: Link in Comments. #AI #MultilingualAI #LLM #LanguageDiversity #YearInReview2025 --- 📊 Year-End Review 2025 Mentioned LLM Developers include: EPFL ETH Zürich Technology Innovation Institute AI Singapore Sea AI Lab (SAIL) Singapore University of Technology and Design (SUTD) PT. Indosat Tbk GoTo GreenNode Ministry of Electronics and Information Technology IIT Bombay Sarvam Karya Lelapa AI Orange Jacaranda Health NAVER Corp SK Telecom Upstage Kakao Corp NC AI SDAIA | سدايا Qatar Computing Research Institute MBZUAI (Mohamed bin Zayed University of Artificial Intelligence) Cohere Inception Cerebras Systems Baykar Technologies Mistral AI Aleph Alpha Sapienza NLP CINECA VELVET AI Unbabel Tilde ivrit.ai Sartify Co. Ltd 01.AI Stability AI Upstage

Thomas Cuvelier, Partner at RTP Global, and an angel backer for AI-powered app development platform Lovable, argues that AI is democratising technical capabilities, eroding the traditional technology moat. So where does competitive differentiation now lie? → User experience → Community engagement → Accessibility for non-technical users → Minimal migration pain The companies that become mission-critical infrastructure in their verticals won't just have great technology. They'll have users who can't imagine working without them. Read the full analysis: "UX Is the New Moat: Why AI Startups Win on Experience, Not Technology" Link in comments 👇 #AIStartups #UserExperience #VentureCapital #AI

Your one-page cheat sheet for the Data Lake vs. Data Warehouse debate is here. In the age of AI, this isn't just about storage. It's about choosing between: ➡️ Governed Reporting for your business analysts. ➡️ Flexible Innovation for your data scientists. Each serves a different purpose, user, and strategic goal. Understanding the trade-offs is essential for building a data foundation that supports your ambitions. This infographic gives you a clear, side-by-side comparison to help you make the right strategic choice. What's the biggest challenge you face with your current data infrastructure? 👇 Read the full article (Link in Comments) by Ashutosh Zutshi to explore the "Data Lakehouse" model.