+ THREE INSIGHTS FOR THE WEEK |
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Assess AI’s impact across an industry. Apollo Global Management evaluates how AI is transforming entire industries, which helps the firm avoid high-risk scenarios and ensures that innovation happens at the right time in portfolio companies.
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Find AI’s value at proof of concept. Michelin’s chief data and AI officer focuses on quantifying potential value early and assesses the actual value delivered post-deployment. Improved productivity from AI projects now generates more than 50 million euros in ROI per year, with a growth rate increase approaching 40% annually.
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Empower leaders to pose questions to datasets. The conversational approach of “vibe analytics” finds leaders engaging with data through AI-powered dialogue. One Southeast Asian telecom surfaced more financially relevant insights in 90 minutes than it typically generated in 90 days.
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Help robots and workers get along. New research identifies four modes of warehouse collaboration, with the most advanced involving the use of AI to help robots better match human speed and strength while forecasting and managing disruptions.
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2. Carbon border adjustment mechanisms are designed to discourage companies from shifting their pollution to countries with looser emissions regulations, but right now they’re a fragmented effort.
Ahead of the COP30 climate conference in Brazil next month, the moment is ripe for countries to adopt a cooperative framework that advances climate, trade, and development together, said MIT Sloan energy economist Catherine Wolfram, co-author of a new report from the Global Climate Policy Project at Harvard and MIT.
The report indicates that more than 80% of emissions in the steel, cement, aluminum, and fertilizer industries are already covered by existing or planned carbon pricing systems — and that these industries account for more than 20% of global carbon emissions.
Analysis shows that:
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A climate coalition could cut emissions seven times more than current policies — an amount equal to Canada’s annual emissions.
- A coalition could raise nearly $200 billion per year in revenues, mostly from domestic carbon pricing.
- Price impacts on key materials would be modest, with minimal consumer effects.
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A graduated approach would allow low- and middle-income countries to join the effort, backed by technology transfer, finance, and capacity-building.
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Should publicly traded companies abandon quarterly earnings reports and switch to a six-month cycle?
Securities and Exchange Commission chair Paul Atkins is fast-tracking the idea, which was proposed by President Trump on social media last month, but market watchers have reservations. New York Times columnist Jeff Sommer argues that the switch might be reasonable under different circumstances — Britain and the EU have made similar shifts without economic disaster — but that the timing is worrisome, given reduced access to government economic data and weakened financial regulation.
Sommer cites a 2017 study by MIT Sloan senior lecturer Robert Pozen that examined Britain’s shift to semiannual reporting. The findings contradict the promised benefits: Companies showed no evidence of longer-term thinking and failed to increase capital investment or R&D spending.
Meanwhile, stock market volatility increased, likely because long gaps without company data caused markets to react more sharply when information finally appeared. “That’s a real cost for investors,” Pozen told Sommer.
In today’s environment, Pozen sees an even greater concern: “We’re already looking at a black hole for data. This would make it much worse.”
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How to boost your organization’s AI maturity level
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New research highlights four areas leaders must address as they embed AI across their business.
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Last year, researchers at the MIT Center for Information Systems Research introduced an enterprise AI maturity framework to help leaders create value from AI.
In a recent update, they report that organizations see the greatest financial impact in moving from piloting and experimentation to embedding AI use and scaling AI across the business.
Based on interviews with senior executives, the researchers identified four areas that enterprises need to address to move successfully from piloting to scale:
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- Strategy: Align AI investments with strategic goals and offer measurable, scalable value.
- Systems: Architect modular, interoperable platforms and data ecosystems to enable enterprisewide intelligence.
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Synchronization: Create AI-ready people, roles, and teams while redesigning work around AI capabilities.
- Stewardship: Embed and monitor compliant, human-centered, and transparent AI practices by design.
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