Use Cases & Insights

AI That Actually
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Real-world AI applications across sales, operations, finance, and HR — with concrete outcomes and implementation detail, not hype.

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AI regulations in Europe: what every Business must do before August 2026

The EU AI Act is already in force. Italian Law 132/2025 is live. GDPR now explicitly covers automated decisions. If you deploy AI in your business and haven't reviewed your compliance posture, the clock is running.

Italian business executives in a conference room discussing AI adoption strategy
AI adoption in Italian SMBs: what the data actually shows

Italy's AI market grew 58% in 2024. The share of Italian SMBs that have actually started an AI project sits at 15% for mid-sized companies and 7% for smaller ones — against more than 50% for large enterprises. That gap isn't explained by scepticism: 84% of Italian business leaders agree AI positively impacts productivity. Here's what actually explains the gap, and what successful adopters do differently.

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AI-powered chat interface integrated with an eCommerce shopping platform
OpenAI and Shopify  might transform ChatGPT into a Commerce platform

The boundaries between conversation and commerce are about to disappear. In a groundbreaking partnership, OpenAI and Shopify are developing a native checkout system that will allow ChatGPT users to discover, compare, and purchase products without ever leaving their chat interface. This isn't just another tech integration—it's a fundamental shift that could reshape how we shop online.

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Analyst examining investment documents with AI-assisted due diligence tools
AI for due diligence: what it reads, what it flags, what it misses

Due diligence is fundamentally a document problem. A typical M&A or investment process generates hundreds of documents spread across a data room that analysts need to read, extract from, cross-reference, and flag within a compressed timeline. AI addresses the document problem directly — and doesn't replace the judgement layer that sits on top of it.

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Business analyst reviewing competitive intelligence report generated by AI
AI for competitive analysis: monitoring and synthesis at scale

Competitive intelligence has a freshness problem. A thorough manual analysis of three or four competitors takes two to four days to produce — and by the time it reaches the people who need it, some of it is already out of date. AI doesn't solve the interpretation problem in competitive analysis. It solves the monitoring and aggregation problem, which is what makes the interpretation possible in the first place.

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