AWS re:Invent: Publicis Sapient and AWS on autonomous marketing systems

Think of the AI Growth ecosystem as five connected layers. If you understand these layers, you can lead the build confidently. Layer A — User Experience Where NAS users interact with agents. Layer B — Agent Orchestration (the “brain”) This is the real Agentic core An Orchestrator Agent that routes tasks to specialized agents and manages multi-step work. Microsoft provides baseline patterns for this type of architecture on Azure. Layer C — Retrieval / RAG (the “memory”) Agents are only useful if they can retrieve NAS truth (proposals, case studies, playbooks, client history). Layer D — Models Where the LLM reasoning happens. Layer E — Platform / Security / Ops

Discover how unifying transactional and analytical data lays the groundwork for dynamic decision-making and advanced AI. Dive into the practical implications of converged workloads, understand the reasons behind their rapid adoption, explore how providers are shaping solutions, and learn what should be at the forefront of your next database strategy phase. How will you harness this transformative approach?

Discover how unifying transactional and analytical data lays the groundwork for dynamic decision-making and advanced AI. Dive into the practical implications of converged workloads, understand the reasons behind their rapid adoption, explore how providers are shaping solutions, and learn what should be at the forefront of your next database strategy phase. How will you harness this transformative approach?

Discover how unifying transactional and analytical data lays the groundwork for dynamic decision-making and advanced AI. Dive into the practical implications of converged workloads, understand the reasons behind their rapid adoption, explore how providers are shaping solutions, and learn what should be at the forefront of your next database strategy phase. How will you harness this transformative approach?

Hear from Ali Ghodsi, CEO of Databricks, and Scott Guthrie, EVP of Cloud + AI at Microsoft, as they showcase how Azure Databricks is powering the next generation of data intelligence and AI across the Microsoft ecosystem. This conversation highlights how enterprises use Azure Databricks as the governed foundation for analytics and AI on Azure including: Zero-copy data access between Unity Catalog and Microsoft OneLake Deep, native integration with Microsoft Entra for secure identity and governance How Genie and Agent Bricks deliver governed, analyst-grade insights from structured and unstructured data Multi-agent orchestration with traceability, debugging, and live data How Databricks Agents integrate directly into Teams, Copilot Studio, and Agent 365 Azure Databricks is the unified platform that brings live data, governance, and AI Agents together so organizations can unlock real business value across the entire Microsoft ecosystem. Explore how Databricks and Microsoft are helping customers unify their data, modernize analytics, and operationalize AI at scale.

Azure just unveiled a “planet‑scale AI superfactory” - which is exciting and also forces a practical question: how centralized should your AI footprint be? A pattern I keep seeing in conversations with CTOs and architects is a push–pull between chasing scale and preserving locality. The core tradeoff is centralization versus regional control - speed and cost efficiency from dense, shared infrastructure versus latency, data residency, and operational independence. Leaders need to treat this as an architectural decision, not just a procurement win. Centralized superfactories cut unit costs and accelerate model iteration, but they can create single points of policy and latency that hurt customer-facing experiences and compliance boundaries. That means risk isn’t just technical - it’s regulatory, contractual, and cultural. If you’re evaluating consolidation this quarter, try this experiment next week: pick three workload types (latency‑sensitive, compliance‑bound, and batch training). Define success metrics for cost, latency, and compliance, then pilot moving only the batch training to centralized AI capacity while keeping latency‑sensitive services regional. Measure 30 days of telemetry and ops overhead before changing the next workload. Which are you optimizing for - centralized scale or regional control - and what did you trade away? #MicrosoftElevate #AIforGood #CloudInfrastructure Read more: https://lnkd.in/dVhnPV9m

Most AI agents fail because they forget context the moment the session ends. I broke down Google's new stack (ADK, MCP, Memory Bank) into a simple guide to help you build personalized systems that actually remember. Swipe through for the architecture breakdown and 5 production-ready GTM agent ideas you can deploy today. -- I'm Aimen. I help businesses harness AI to drive tangible business outcomes #AIAgents #GTM #GoogleCloud #SalesAutomation #AgenticAI

Top 10 SMB & Mid-Market Predictions for 2026 and Beyond: The Autonomous Business: Techaisle’s 2025 SMB predictions captured the critical first-wave adoption of AI-driven capabilities within the SMB and mid-market. Themes like Agentic AI, Embedded AI-aaS, and AI-First Workplaces set the stage for transformation.   It is important to note that the insights below are not merely current market trends; they are strategic predictions charting the future trajectory of the industry. These forecasts are forged from a rigorous global research engine, grounded in over 10,000 survey responses collected across 20 countries in local languages, and validated through hundreds of deep-dive discussions with SMB, midmarket, and channel partner decision-makers.   For 2026 and beyond, our analysis evolves from this foundation to focus on the inevitable consequences. The central strategic challenge for SMBs will no longer be whether to adopt AI, but how to manage the resulting complexity. This new landscape will be defined by the economic realities of AI ("AI-nomics"), the orchestration of autonomous AI workforces, and the critical need for sovereign data intelligence. The following 10 predictions detail this next wave of opportunity, organized into three strategic mega-trends. To illustrate this evolution, each 2026 prediction is accompanied by its corresponding foundational 2025 trend for context. https://lnkd.in/g_KT4fGh #SMB #Midmarket #Top10 #Predictions #GenAI #Cloud #Security #ArtificialIntelligence #FutureOfWork #TechnologyTrends #DigitalTransformation #BusinessStrategy #SMBPredictions #AgenticAI #AIWorkforce #AIgovernance #FinOps #HumanAITeaming #ChannelPartners #MSP #Automation #DataSovereignty #CEO #CIO #CTO #BusinessLeadership #Innovation

Are you modernizing… but not moving forward? If your org has rebuilt pipelines, migrated platforms, or consolidated warehouses, only to feel like your data still can’t keep up with the business or with AI, you’re not alone. In our article (and webinar with Microsoft + Magna Legal Services), we break down: - Why so many orgs are stuck in an endless cycle of upgrades - How AI raises the stakes and changes the rules - And how the Leapfrog model helps teams get AI-ready in months, not years Step off the treadmill. Leap into the future. #AIReadiness #DataStrategy #DigitalTransformation