Simor Consulting
Category: Trends
The traditional BI dashboard — a grid of charts that a business user opens every morning to check KPIs — is losing its grip on how organizations consume data. The decline is not dramatic. No one decla
LinkedIn's latest workforce report shows "AI engineer" as the fastest-growing job title for the third consecutive quarter. Job postings containing the title increased 280% year-over-year. The growth r
The regulatory focus on AI is narrowing from the models themselves to the data that trains them. The EU AI Act requires documentation of training data provenance and composition. The US Copyright Offi
OpenAI shipped GPT-5. Anthropic shipped Claude 4. Google shipped Gemini Ultra 2. Within six weeks of each other, the three leading model providers released frontier models that are, by most benchmarks
Enterprise AI spending increased roughly 300% year-over-year according to multiple industry surveys released this quarter. The headline number gets attention, but the breakdown is where the actionable
Data Council 2026 wrapped in Austin last week, and the signal-to-noise ratio was higher than in recent years. The conference has historically been the venue where data infrastructure practitioners — n
Google published the Agent-to-Agent (A2A) protocol specification in late 2025 and, as of this quarter, has secured endorsement from over fifty technology companies including Salesforce, SAP, ServiceNo
AWS announced Bedrock Studio. Google shipped Vertex AI Platform as a unified surface. Azure consolidated its AI offerings under a single "AI Foundry" brand. Databricks, Snowflake, and even Cloudflare
Three releases in the last six weeks have redrawn the open-source LLM map. Meta shipped Llama 4 with a mixture-of-experts architecture that narrows the gap with proprietary frontier models. Mistral re
The first enforcement window of the EU AI Act opened in February 2026, and the grace periods that protected early movers are expiring on a rolling schedule through 2027. This is no longer a policy dis
2025 was the year AI moved from experimentation to industrialization. While 2024 saw the explosion of generative AI capabilities, 2025 was about making those capabilities production-ready, cost-effect