AI adoption is moving faster than most data suggests, but the returns still aren't keeping up. This edition we look at why individual productivity gains aren't translating to organizational value, how the world's biggest retailers are betting on AI to transform their supply chains, and what it really takes to build enterprise AI infrastructure you can trust.
The trend: AI usage is far larger than usually reported, accounting for 56% of global search traffic.
The details: A new study by Graphite.io found that monthly AI sessions are 4-5x larger than previous reports that only included web data and not mobile apps (where 83% of AI usage occurs). AI now receives 45B monthly sessions worldwide, but traditional search usage has remained steady, with total search growing 26% since ChatGPT launched.
Why it matters: The assumption that AI and traditional search are zero-sum is wrong, as AI is not replacing search behavior but adding to it. This means growing demand for faster, more interconnected data systems that can serve users across more platforms and use cases than ever before.
The trend: Individual AI is making people more productive, but companies are not seeing the returns. Value will come from 'Institutional AI' - systems designed to make entire organizations smarter, not just individual employees faster.
The details: George Sivulka argues that productive individuals don't make productive firms, at least not yet. In the industrial revolution, factories that simply swapped steam motors for electric ones saw almost no productivity gains for 30 years. It was only when they redesigned the entire factory floor with assembly lines and new roles that productivity grew, and the same pattern is playing out with AI today.
Why it matters: Most organizations today are layering AI onto existing workflows and wondering why the needle isn't moving. The real competitive advantage will go to those who redesign around AI at the institutional level.
Jefferies reports that major US retailers are doubling down on AI, with Target's stock jumping 6.7% after announcing a strategic growth plan centered on AI adoption and supply chain investment, backed by $5 billion in capital expenditures - despite a tough year financially. The market reaction reflects growing investor sentiment that AI-driven supply chain intelligence, from demand forecasting to inventory optimization, is now a primary driver of long-term retail competitiveness.
We recently published a new article from our CTO, Harbinder Singh, on why we built KAI Assistant on Google Vertex AI and Gemini. If you've ever wondered what goes into the infrastructure decisions behind an enterprise AI product, it's worth a read. He covers how we approached security and data governance, why grounded retrieval matters for accuracy in live data workflows, and how the choice of Vertex AI sets us up for where KAI is heading next.
Last edition we asked you 'Where is AI genuinely saving your team time in 2026?'. Unsurprisingly, writing and content generation came in 1st place, followed closely by meeting summaries which save 66.7% of teams time.
Code generation and data analysis & reporting rounded out the top 3 in a tie. Interestingly the option of it isn't saving us any time yet received less than 10% of votes, suggesting that most teams are getting at least some use out of AI tools in 2026.
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