Tech

AI’s productivity impact: measuring time savings versus costs

Measuring AI’s productivity impact is challenging without better data on time savings versus time taxes.

Published

10 months ago

March 20, 2025

Ahron Young

Measuring AI’s productivity impact is challenging without better data on time savings versus time taxes.

In Short

Measuring AI’s impact on productivity is difficult due to data scarcity and varying adoption rates among companies. Focusing on how AI saves time can clarify its productivity effects, necessitating improved data collection methods to relate time use to economic outcomes.

Measuring the impact of AI on productivity is challenging due to a lack of data.

The phrase “time is money” resonates in the context of AI, as time savings are vital for assessing technology investments.

AI’s effect on total factor productivity, which reflects value generation from resources, is a concern for both business leaders and policymakers amid stagnant productivity growth.

While new AI models emerge regularly, evidence of efficiency gains in economic statistics remains elusive. Surveys indicate that many companies are experimenting with AI, but adoption rates vary significantly across regions.

New technologies

Historically, the productivity benefits of new technologies can take time to appear in national statistics, illustrated by the example of electrification in American manufacturing.

Furthermore, measuring productivity is complex in sectors that do not produce standardised goods, making it difficult to quantify output quality in areas like legal or consulting services.

Focusing on time spent by workers and its implications can provide a clearer picture of AI’s productivity effects. Historical improvements in productivity stem from workers accomplishing tasks more swiftly.

AI has the potential to streamline time-consuming processes, prompting businesses to examine how employees currently use their time and identify areas of inefficiency.

Economists should develop better methods for data collection, such as tracking technology usage, to better understand how daily time allocation correlates with productivity value and AI’s economic impact.

Tech

Apple’s AI wearable push: Cameras, speakers and a 2027 vision

Apple is developing an AI-powered wearable device, aiming for a launch of 20 million units in the growing AI market.

Published

4 hours ago

January 22, 2026

Harvey Vargas

Apple is developing an AI-powered wearable device, aiming for a launch of 20 million units in the growing AI market.

Apple is reportedly developing an AI-powered wearable device equipped with cameras and speakers, signalling its next major move into artificial intelligence-driven hardware.

While still in early development, the company is said to be planning a launch scale of up to 20 million units.

This move places Apple squarely into the fast-growing AI wearable market, where tech giants are racing to define what hands-free, AI-first devices will look like. Rather than rushing to market, Apple appears to be taking a measured approach by embedding AI capabilities into its existing ecosystem.

Reports suggest Apple is also experimenting with camera-equipped AirPods and smart glasses, with a potential launch timeline around 2027. If successful, these devices could reshape how users interact with AI in everyday life.

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Tech

AI spending in 2026: Why investment is compounding, not just cyclical

As 2026 begins, AI investment debates rise; real revenue growth signals pivotal changes for tech adoption and future trends.

Published

1 day ago

January 21, 2026

Harvey Vargas

As 2026 begins, AI investment debates rise; real revenue growth signals pivotal changes for tech adoption and future trends.

As we kick off 2026, the debate around AI spending is heating up. Skeptics warn of cyclical hype, but new evidence suggests that AI investment is delivering real revenue and gaining traction across enterprises. Brad Gastwirth from Circular Technologies breaks down why this year could be pivotal for AI adoption.

We dive into how AI spending today compares to previous tech booms, the impact of circular funding models, and why enterprise and sovereign demand are driving durable growth. Brad explains the compounding effect of AI investment and what it means for future technological development.

Finally, we explore the race toward AGI and ASI and the broader implications for the tech landscape. From skeptics to believers, understanding these trends is key for investors, businesses, and tech enthusiasts alike.

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#AIInvestment #TechTrends2026 #ArtificialIntelligence #EnterpriseAI #FutureTech #AGI #TechBoom #CircularFunding

Tech

TSMC posts record profits on AI chip boom

TSMC posts record Q4 profit, driven by strong chip demand, exceeding predictions and signaling market dominance.

Published

6 days ago

January 16, 2026

Harvey Vargas

TSMC posts record Q4 profit, driven by strong chip demand, exceeding predictions and signaling market dominance.

Taiwan Semiconductor Manufacturing Company (TSMC) has posted a record net profit for the fourth quarter, driven by strong demand for advanced chips.

Net profit surged 35% year-on-year, exceeding analyst expectations and signalling a dominant position in the semiconductor market.

Quarterly revenue also rose 20.5% compared to last year, supported by robust sales in AI and high-performance computing segments. The company’s success reflects the growing global appetite for cutting-edge semiconductor technology.

Looking ahead, TSMC plans to ramp up capital expenditure, projecting investments of up to $56 billion in 2026. The positive results have sparked an upbeat reaction across global markets, highlighting TSMC’s influence in the tech sector.

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