Artificial Intelligence (AI) Statistics: Unveiling the Growth Drivers and Key Data

2023 -2030 Global AI Statistics: Unveiling the Key Insights and Trends Shaping Artificial Intelligence (AI)

Artificial intelligence (AI) has permeated nearly every aspect of our lives, revolutionizing industries from healthcare to agriculture.

Its transformative power has fueled a global market valued at around $187 billion, projected to reach a staggering $739 billion by 2030.

With such immense potential, AI has attracted substantial investor interest.

However, before diving into the AI investment landscape, it’s essential to grasp the underlying trends driving this exponential growth and the key data that shapes the sector.

To help you navigate the AI landscape, we’ve compiled a comprehensive collection of statistics that shed light on the current state and future trajectory of AI adoption and innovation.

Global AI Market Size and Growth Projections

The market size in the Artificial Intelligence market is projected to reach US$241.80bn in 2023.

Statista

The market size is expected to show an annual growth rate (CAGR 2023-2030) of 17.30%, resulting in a market volume of US$738.8obn by 2030.

Statista

In global comparison, the largest market size will be in the United States (US$87.18bn in 2023).

Statista

AI Market Size Worldwide

Artificial Intelligence Market Size Segment

AI Tools Users Worldwide 2023

Global Artificial Intelligence Market Size Comparison

Generative AI Market

The global generative AI market size is projected to grow from $43.87 billion in 2023 to $667.96 billion by 2030, at a CAGR of 47.5% during the forecast period.

Fortune Business Insights

With the influx of consumer generative AI programs like Google’s Bard and OpenAI’s ChatGPT, the generative AI market is poised to explode, growing to $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022, according to a new report by Bloomberg Intelligence (BI). Growth could expand at a CAGR of 42%, driven by training infrastructure in the near-term and gradually shifting to inference devices for large language models (LLMs), digital ads, specialized software and services in the medium to long term

Bloomberg

On the hardware side of this, revenue will be driven by AI servers ($132 billion), AI storage ($93 billion), computer vision AI products ($61 billion) and conversational AI devices ($108 billion).

Bloomberg

The largest drivers of incremental revenue will be generative AI infrastructure as a service ($247 billion by 2032) used for training LLMs, followed by digital ads driven by the technology ($192 billion) and specialized generative AI assistant software ($89 billion).

Bloomberg

Rising demand for generative AI products could add about $280 billion of new software revenue, driven by specialized assistants, new infrastructure products, and copilots that accelerate coding. Companies like Amazon WebServices, Microsoft, Google and Nvidia could be the biggest beneficiaries, as enterprises shift more workloads to the public cloud.

Bloomberg

McKinsey’s latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases analyzed by McKinsey — by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15 to 40%.

McKinsey

About 75% of the value that generative AI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D.

McKinsey

Current generative AI and other technologies have the potential to automate work activities that absorb 60-70% of employees’ time today. The acceleration in the potential for technical automation is largely due to generative AI’s increased ability to understand natural language, which is required for work activities that account for 25% of total work time.

McKinsey

Generative AI could enable labor productivity growth of 0.1 to 0.6% annually through 2040, depending on the rate of technology adoption and redeployment of worker time into other activities.

McKinsey

Value potential of generative AI by business function will vary. McKinsey’s analysis of 16 business functions identified just four –customer operations, marketing and sales, software engineering, and research and development — that could account for approximately 75% of the total annual value from generative AI use cases.

McKinsey

Generative AI could increase sales productivity by 3-5% of current global sales expenditures. Across 63 use cases, generative AI has the potential to generate $2.6 trillion to $4.4 trillion in value across industries.

McKinsey

Generative AI is poised to expand its impact from less than 1% of total IT hardware, software services, ad spending, and gaming market spending to 10% by 2032.

Bloomberg

They estimate a growth boost to GDP from AI of 0.4 percentage points in the US, 0.3 percentage points on average in other DMs, and 0.2 percentage points on average in advanced EMs by 2034.

Goldman Sachs

Our research also shows that 45% of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalisation, attractiveness and affordability over time.

PwC

Generative Artificial Intelligence Market Size

Generative Artificial Intelligence Market Size Share in Artificial Intelligence Market