01AI EconomicsAI FinOps in 2027: Managing Inference Costs at Scale
A practical framework for measuring cost per AI outcome, routing work across model tiers, and keeping production AI economically sustainable.
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Ideas for putting AI to work.
Practical perspectives on designing, building, and scaling AI for real business operations.
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12 ARTICLES01AI Economics
02AI GovernanceEnterprise AI Governance in 2027: Runtime Controls That Scale
Move beyond policy documents with practical identity, permission, monitoring, and human-approval controls for AI in production.
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03AI ArchitectureSmall Language Models in 2027: An Enterprise Adoption Guide
Learn where small language models fit, how to combine them with larger models, and what to test before bringing inference closer to your data.
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04Agentic AIAgentic AI in 2027: Start with the Workflow
A useful agent begins with a bounded business job, trusted tools, measurable outcomes, and a clear route to human judgment.
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05EnglishA practical architecture for enterprise AI-driven workflows
How CTOs can connect GenAI applications, AI orchestrators, agents, data, and human controls into measurable AI-driven processes.
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06DeutschKI-gestützte Workflows im Unternehmen: eine praxistaugliche Architektur
Ein Leitfaden für CTOs: Wie GenAI-Anwendungen, KI-Orchestrierung, Agenten und menschliche Kontrolle zu messbaren Geschäftsprozessen werden.
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07Norsk (bokmål)AI-drevne arbeidsflyter i virksomheten: en praktisk arkitektur
En guide for teknologiledere: Slik kobles generativ AI, orkestrering, agenter og menneskelig kontroll til målbare arbeidsprosesser.
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08Model Context ProtocolModel Context Protocol (MCP): An Enterprise Implementation Guide for 2027
A practical MCP implementation guide for connecting LLMs to local data and enterprise tools with explicit identity, authorization, and operational controls.
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09AI Digital CoworkersAI Digital Coworkers in 2027: An Enterprise Guide
Design virtual workforce automation around clear roles, approved tools, human decision rights, and measurable operational outcomes.
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10AI OperationsAI Observability for GenAI: A Production Guide
A practical framework for monitoring LLM quality, traces, latency, cost, errors, and drift across production AI applications and agents.
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11Data foundationsAI Data Foundations for Useful Enterprise AI
Connected, governed, well-understood information is the foundation for reliable retrieval, analytics, and AI products.
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12Delivery and adoptionAI Pilot to Production: Design for Adoption
Evaluation, ownership, security, and the daily user experience determine whether a promising pilot becomes durable business capability.
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