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News articleCrunchbase News

Don’t Just Talk About AI. Measure Business Outputs. Here’s How.

View original at news.crunchbase.com
Crunchbase News - Funding Ma Title: Don’t Just Talk About AI. Measure Business Outputs. Here’s How…
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  • Results are best when choosing the output to improve, varying AI tools until one moves the dial, and measuring Time To Production

    60% confidence
  • Approach AI projects as mathematical optimization problems by defining a target measure, identifying influencing variables, and modeling the mechanism by which the target is moved

    60% confidence
  • Theory on why so many pilots fail is that companies pick an AI tool and pilot duration and qualitatively check in with users, rather than measuring outputs

    60% confidence
  • The theory on why so many pilots fail is that companies tend to pick an AI tool and pilot duration and qualitatively check in with users at the end rather than measuring outputs

    60% confidence
  • AI systems trusted with real decisions are what Peter Drucker would call executives

    60% confidence
  • Last year felt like the Year of the AI Pilot with widespread disappointment in the impact of AI pilots

    60% confidence
  • AI is an invention in the process of becoming an innovation; an invention is a new capability that is not an innovation until it has a business model

    60% confidence
  • The form innovation takes will be AI systems trusted with real decisions, what Peter Drucker would call executives and are referred to as agentic AI

    60% confidence
  • Last year felt like the Year of the AI Pilot with widespread disappointment in the impact of AI pilots

    60% confidence
  • The idea is to approach AI projects as mathematical optimization problems: Define a target measure, ask what variables influence that metric, and model the mechanism

    60% confidence
  • Organizations must focus on outputs rather than activities, anecdotes and initiatives which are inputs

    60% confidence
  • Organizations must focus on outputs rather than activities, anecdotes and initiatives which are merely inputs

    60% confidence
  • AI is an invention in the process of becoming an innovation, not becoming an innovation until it has a business model

    60% confidence
  • 95 percent of generative AI pilots at companies are failing according to MIT report

    60% confidence

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What we're seeing
AI-Driven Drug Development Meets Biotech Deal-Making and Regulatory Catalysts
AI-designed therapeutics (Insilico's rentosertib showing biological-age reductions) are moving into the clinical mainstream. Large-cap biotech is simultaneously reallocating capital through M&A (Lilly–Merida, $2.9B) and government funding (BARDA–Basilea), while trial failures (ziltivekimab, a 9.4% Novo Nordisk share drop) and upcoming FDA catalysts (the ivonescimab PDUFA on 2026-11-14) drive volatility. The wider AI regulatory and legal climate (Tesla Cybercab probe, xAI's Minnesota loss, OpenAI suits) is tightening, though QAIAx's micro-cap trial claims are speculative and weakly connected.
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Satellite-Terrestrial Network Integration Acceleration
Increased investment and launches in hybrid satellite-cellular networks across telecom industry; competitive responses from other carriers; regulatory activity around satellite spectrum; expansion of emergency/rural connectivity use cases
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Where sources disagree
ING Group
Both facts record the same metric (shares_outstanding) for ING Group at the identical observation date (2025-12-31). FACT A states 2,902,437,688 shares; FACT B states 2,902 million shares (2,902,000,000). The difference is 437,688 shares (~0.015%). This is a genuine value conflict, though the discrepancy appears to result from FACT B rounding to the nearest million while FACT A provides the precise count.
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