Intel Cash Flow from Investing Activities 2012-2026 | INTC

Intel annual/quarterly cash flow from investing activities history and growth rate from 2012 to 2026. Cash flow from investing activities can be defined as the total change in cash resulting from a companies investments
  • Intel cash flow from investing activities for the quarter ending March 31, 2026 was $-14.821B, a 18.82% decline year-over-year.
  • Intel cash flow from investing activities for the twelve months ending March 31, 2026 was $-25.000B, a 46.85% decline year-over-year.
  • Intel annual cash flow from investing activities for 2025 was $-14.821B, a 18.82% decline from 2024.
  • Intel annual cash flow from investing activities for 2024 was $-18.256B, a 24.06% decline from 2023.
  • Intel annual cash flow from investing activities for 2023 was $-24.041B, a 134.98% increase from 2022.
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Intel Annual Cash Flow Investing
(Millions of US $)
2025 $-14,821
2024 $-18,256
2023 $-24,041
2022 $-10,231
2021 $-24,283
2020 $-21,524
2019 $-14,405
2018 $-11,239
2017 $-15,762
2016 $-25,817
2015 $-8,183
2014 $-9,905
2013 $-18,073
2012 $-14,060
2011 $-10,301
Sector Industry Market Cap Revenue
Computer and Technology Semiconductor - General $311.588B $52.853B
Intel Corporation, one of the world's largest semiconductor company and primary supplier of microprocessors and chipsets, is gradually moving into data-centric businesses such as AI and autonomous driving. Intel is a dominant player for microprocessors in both consumer and enterprise markets. Data Center Group, Internet of Things Group, Mobileye, Non-Volatile memory solutions group and Programmable solutions Group and All Other business units form the crux of Intel's data-centric business model. DCG segment deals with servers, workstations and other products for cloud, enterprise, and communication infrastructure market. IOTG offers high-performance compute solutions and embedded applications. PSG segment offers programmable semiconductors, primarily FPGAs and structured ASICs. Mobileye is engaged in developing computer vision and machine learning-based sensing, data analysis, localization, mapping, and driving policy technology for ADAS and autonomous driving.
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