The global AI software market is forecast to reach $210 billion within two years. In manufacturing, where 75% of firms expect to adopt AI within three years, this technology can reduce energy consumption in industrial processes by up to 10%.
Key Takeaways
- 2.3% compound annual growth rate for the global artificial intelligence (AI) software market in 2023–2027
- AI software market is forecast to reach $142.0 billion in 2026
- AI software market is forecast to reach $210.0 billion in 2028
- Global electricity generation was about 28,000 TWh in 2022
- Global industrial electricity consumption was about 7,000 TWh in 2021
- Aluminum sector can reduce GHG emissions by 60% by 2050 via deep decarbonization pathways (scenario estimate)
- Total energy consumption for producing primary aluminum is about 14–15 MWh per ton (typical industry range including electricity)
- World primary aluminum production required approximately 0.5% of global electricity generation (estimation commonly cited around 4–5% of global electricity devoted to aluminum)
- Aluminum production process waste includes dross; dross generation is typically ~3–7% of produced aluminum (industry typical)
- In a Frost & Sullivan survey, 75% of manufacturing firms expect to adopt AI within 3 years (industry adoption expectation benchmark)
- In IBM’s survey, 57% of organizations are using or planning to use AI in the next 12 months
- In Forrester’s report, 73% of manufacturing organizations are implementing AI/ML in at least one area (benchmark)
AI software growth is surging while aluminum makers cut energy and defects with manufacturing AI.
Related reading
01 · Category
Market Size30 stats
01
2.3% compound annual growth rate for the global artificial intelligence (AI) software market in 2023–2027
02
AI software market is forecast to reach $142.0 billion in 2026
03
AI software market is forecast to reach $210.0 billion in 2028
04
AI software market revenue is forecast to grow 19.0% in 2024
05
AI software market revenue is forecast to grow 19.5% in 2025
06
AI software market revenue is forecast to grow 18.9% in 2026
07
AI software market revenue is forecast to grow 17.5% in 2027
08
AI software market revenue is forecast to grow 16.6% in 2028
09
AI software revenue is forecast to total $297.2 billion by 2029
10
AI in manufacturing market expected to reach $21.2 billion by 2026
11
AI in manufacturing market expected to grow at a CAGR of 28.2% from 2021 to 2026
12
AI in manufacturing market size projected to reach $59.2 billion by 2030
13
AI market is projected to reach $1.8 trillion by 2030
14
Global primary aluminum production reached 66.9 million metric tons in 2022
15
Global secondary aluminum production reached 31.3 million metric tons in 2022
16
Aluminum industry generated about $160.0 billion in revenue in 2023
17
Global aluminum recycling rate was about 66% in 2022
18
The global aluminum extrusion market valued at $100.0 billion in 2021
19
The global aluminum flat-rolled products market was valued at $120.0 billion in 2023
20
Global industrial AI market expected to reach $19.0 billion in 2024
21
Industrial AI market is expected to grow at a CAGR of 28.2% from 2024 to 2032
22
Predictive maintenance market size projected to reach $19.7 billion by 2026
23
Predictive maintenance market forecast CAGR of 24.7% from 2019 to 2026
24
Industrial IoT market expected to reach $158.1 billion by 2024
25
AI in energy and utilities market expected to reach $6.7 billion by 2025
26
AI in energy and utilities market projected to grow at CAGR of 33.2% from 2019 to 2025
27
Computer vision market in manufacturing expected to reach $14.3 billion by 2027
28
Computer vision market projected CAGR of 9.2% from 2020 to 2027
29
The global AI chip market is forecast to reach $29.8 billion in 2024
30
The global AI chip market is forecast to reach $60.1 billion by 2028
Interpretation
Market Size Interpretation
With AI software projected to grow from about $142.0 billion in 2026 to $210.0 billion by 2028, and AI in manufacturing expanding even faster toward $59.2 billion by 2030 on a 28.2% CAGR from 2021 to 2026, the aluminium value chain is clearly entering a period of rapid, AI led scaling.
02 · Category
Industry Trends6 stats
01
Global electricity generation was about 28,000 TWh in 2022
02
Global industrial electricity consumption was about 7,000 TWh in 2021
03
Aluminum sector can reduce GHG emissions by 60% by 2050 via deep decarbonization pathways (scenario estimate)
04
IEA estimates the aluminium sector accounts for around 1% of global direct CO2 emissions (contextual estimate)
05
Alumina refining (Bayer process) requires about 10–25% of total aluminum LCA energy and produces significant tailings (process energy context)
06
Aluminum-related industry is covered by World Aluminum’s statistics program for annual production and recycling rates
Interpretation
Industry Trends Interpretation
With aluminum able to cut greenhouse gas emissions by up to 60% by 2050, its impact is especially notable given that the sector is estimated at about 1% of global direct CO2 emissions while using energy for processes like alumina refining that can account for 10 to 25% of aluminum lifecycle energy.
More related reading
03 · Category
Performance Metrics8 stats
01
Total energy consumption for producing primary aluminum is about 14–15 MWh per ton (typical industry range including electricity)
02
World primary aluminum production required approximately 0.5% of global electricity generation (estimation commonly cited around 4–5% of global electricity devoted to aluminum)
03
Aluminum production process waste includes dross; dross generation is typically ~3–7% of produced aluminum (industry typical)
04
In a control study, using machine learning reduced energy consumption of an industrial process by up to 10% (case study result)
05
Condition-based maintenance adoption can reduce failures by 20–50% (benchmark range)
06
Computer vision-based inspection can improve defect detection accuracy by up to 20 percentage points versus manual inspection (reported case results)
07
In steel and metalworking defect detection, deep learning can achieve up to 97% classification accuracy (case results)
08
Bauxite mining produces red mud; red mud generation is typically around 1–1.5 tons per ton of alumina (process stoichiometry context)
Interpretation
Performance Metrics Interpretation
AI and related digital approaches are already showing measurable impact in aluminum, with machine learning cutting energy use by up to 10% in control studies and computer vision improving defect detection by about 20 percentage points, even as the sector still accounts for roughly 4 to 5% of global electricity and faces material waste such as dross at about 3 to 7% of produced aluminum.
04 · Category
User Adoption4 stats
01
In a Frost & Sullivan survey, 75% of manufacturing firms expect to adopt AI within 3 years (industry adoption expectation benchmark)
02
In IBM’s survey, 57% of organizations are using or planning to use AI in the next 12 months
03
In Forrester’s report, 73% of manufacturing organizations are implementing AI/ML in at least one area (benchmark)
04
In a Gartner survey, 60% of manufacturing organizations will use AI to improve operations by 2025
Interpretation
User Adoption Interpretation
Across manufacturing in the aluminum industry, AI momentum is strong, with 75% of firms expecting to adopt it within 3 years and 60% planning to use it to improve operations by 2025.
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Megan Gallagher. (2026, February 13). AI In The Aluminum Industry Statistics. Gitnux. https://gitnux.org/ai-in-the-aluminum-industry-statistics
MLA
Megan Gallagher. "AI In The Aluminum Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/ai-in-the-aluminum-industry-statistics.
Chicago
Megan Gallagher. 2026. "AI In The Aluminum Industry Statistics." Gitnux. https://gitnux.org/ai-in-the-aluminum-industry-statistics.
Sources & references
31 datasets cited across this report · attribution is report-level
+18 additional datasets cited (not shown individually)