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AI & Enterprise

Most companies use AI but cannot make money; problem is people and jobs

Companies are rapidly adopting AI, but improving returns on investment requires more than deploying tools, a report said. Adam Field (애덤 필드), chief AI officer at Tungsten Automation, wrote that AI results depend on the people who use it and work structures. Surveys cited show widespread AI use but limited profit conversion, skill gaps among employees and data trapped in unstructured formats such as email and PDFs. He called for job redesign, retraining and data cleanup.

AI & Enterprise

Tech Insight: Why companies slowly die in the AI era

Many companies buy AI licences and run pilot projects but keep the same way of working, leaving them at risk of falling behind, Limestone Digital founder Mark Eisenstadt (마크 아이젠슈타트) wrote. He cited surveys showing many firms adopting AI do not see clear financial results. He compared it to early factories that swapped in electric motors without redesigning layouts. Eisenstadt said high-performing firms rebuild workflows and advised starting small and proving impact quickly.

AI & Enterprise

AI infrastructure boom fallout: data centre e-waste could pile up to 617 million tonnes by 2050

The spread of artificial intelligence could fuel a new electronic waste problem, with AI-related retirements of servers, GPUs and supporting power, cooling and networking equipment adding up to 395 million to 617 million tonnes by 2050, Basel Action Network estimates. The group says broader infrastructure should be counted, not just servers. It also highlights limited global recycling capacity and risks from informal processing, and notes the United States has not ratified the Basel Convention.