Here's a quick snapshot of si technology right now in 2026Here’s a quick snapshot of AI technology right now in 2026: *1. Where AI is being used today* - *Adoption is mainstream*: 72% of organizations globally now use AI in at least one business function, up from ∼50% for the past 6 years. 65% specifically use generative AI regularly, nearly double vs 10 months prior. - *But scaling is still hard*: Nearly 2/3 of orgs haven’t begun scaling AI across the enterprise yet — most are still experimenting or piloting. - *Value shows up in pieces*: Companies see cost decreases and revenue jumps in units deploying gen AI, but only 39% report enterprise-level EBIT impact so far. 4fdb4459 *2. Big technology shifts happening now* *Agentic AI* This is the move from chatbots to autonomous AI “agents” that can plan and act. Microsoft just rolled out “Copilot Cowork” to early-access customers, and multi-agent workflows are trending. Deloitte predicts 2026 will be when pilots scale to production and companies build “agent ops” teams. Adoption is still early: most orgs are piloting or haven’t deployed agents at all. d5f7f4a5 *Next-gen multimodal models* Early 2025 saw a race of giant models: Google’s Gemma 3, OpenAI’s GPT-4.5 “Chonky Orion” with ∼5T parameters, Anthropic’s Claude 3.7 Sonnet with “thinking” features. Smaller models like QwQ-32B are also matching much larger systems through better architecture. 1c64 *Multi-model workflows* Microsoft’s new “Critique” feature has GPT generate a response and Claude review it for accuracy before showing it to you. “Model Council” lets users compare outputs side-by-side. Goal: reduce hallucinations and boost reliability. d5f7 *Edge AI + TinyML* AI is moving onto devices to cut latency, bandwidth, and power use. Chips like Hailo-10H, Kinara Ara-2, and NXP http://i.MX 95 bring AI to robotics, wearables, phones. The edge AI market is projected to jump from $24B in 2024 to $357B by 2035. df08 *Math & reasoning breakthroughs* Models like Qwen2-Math hit 84% on MATH dataset; rStar-Math let a 7B model solve 53% of AIME 2024. Gemini Deep Think got gold-medal results at IMO 2025 using natural language prompts. 3657 *3. What companies are figuring out* - *Governance & risk*: Inaccuracy is still the #1 risk orgs try to mitigate. For agentic AI, companies will need new compliance frameworks. - *Workforce impact*: 32% expect AI to decrease workforce size next year, 43% expect no change, 13% expect increases. Reskilling is a major theme. - *Redesigning workflows*: High performers don’t just plug in AI — they redesign processes and use AI for growth/innovation, not just efficiency. ce2af4a54459 *4. Research frontiers* - *Generative AI techniques*: Diffusion models, non-autoregressive transformers, flow-based models are advancing for more reliable generation. - *Quantum ML*: Still emerging, but big players like IBM, Microsoft, Amazon are investing to tackle problems classical computers can’t. - *AGI paths*: Research focuses on hierarchical RL, meta-learning, and self-supervised learning. d35eda7f Want me to go deeper on any of these — like how agentic AI works, edge AI chips, or which industries are adopting fastest?