Generative AI is reshaping how media teams work, with usage now showing up across departments and workflows. In 2024, 27.5% of respondents reported using generative AI at least weekly, and 34% said they’ve deployed it in at least one business function. This page connects those adoption signals to productivity claims, customer-operation automation potential, and the governance and quality requirements that help reduce risks like hallucinations.
Key Takeaways
- 27.5% of respondents reported using generative AI at least weekly in 2024
- 50% of respondents said they have already implemented or experimented with generative AI in at least one business process
- 65% of IT leaders expect generative AI to increase productivity in 2024 (Gartner survey)
- $266.0 billion is the projected global generative AI market size by 2030 (CAGR forecast from 2024)
- $153.0 billion global spend on genAI software and services is forecast for 2027
- The global generative AI in media market is projected to reach $18.2 billion in 2024
- In the EU AI Act, providers must comply with transparency obligations for certain AI systems by 2025 (per adopted regulation timetable)
- In the EU AI Act, high-risk AI systems are subject to strict requirements under Article 6 and related chapters
- In the EU, fines for violations of the GDPR can reach up to €20 million or 4% of global annual turnover, whichever is higher
- GenAI could automate 60–70% of work activities in customer operations (McKinsey Global Institute estimate)
- 73% of respondents said genAI improved their productivity at work in 2024 (Microsoft Work Trend Index survey)
- A 2024 MIT study found that LLMs can hallucinate with a frequency requiring verification; the study reported 13% factual error rates in a benchmark (MIT-led evaluation)
- In a 2023 trial, IBM reported that generative AI reduced report-writing time by 30% (IBM case study)
- Training and fine-tuning costs can be materially reduced using parameter-efficient fine-tuning (LoRA); a benchmark reported 10x fewer trainable parameters for LoRA vs full fine-tuning (paper)
- 34% of organizations said they have deployed generative AI in at least one business function in 2024 (survey), showing cross-functional adoption momentum
Generative AI adoption is accelerating fast in media and beyond, with big productivity gains and rapid market growth despite compliance and accuracy risks.
Related reading
01 · Category
Industry Trends10 stats
01
27.5% of respondents reported using generative AI at least weekly in 2024
02
50% of respondents said they have already implemented or experimented with generative AI in at least one business process
03
65% of IT leaders expect generative AI to increase productivity in 2024 (Gartner survey)
04
The ShareGPT dataset (collected from ChatGPT user shares) contains 300,000 conversations (BigScience report dataset description)
05
In the 2024 Media & Entertainment Outlook, PwC estimates that genAI will increase productivity across marketing and creative functions by 20% (PwC analysis)
06
Meta Llama 3 was trained using 15 trillion tokens (Meta AI technical report)
07
27% of respondents use generative AI at least weekly in 2024 (weekly users share).
08
50% of respondents have implemented or experimented with generative AI in at least one business process in 2024 (broader adoption).
09
32% of respondents report using generative AI at least weekly in 2024 (weekly users share).
10
41% of respondents reported using generative AI at least weekly in 2024 (weekly users share).
Interpretation
Industry Trends Interpretation
In Industry Trends, adoption is accelerating fast with 27.5% of respondents using generative AI at least weekly in 2024 and 50% having already implemented or experimented with it in business processes, while 65% of IT leaders expect productivity gains.
report visual · Comparison
Generative AI adoption: weekly use vs broader implementation (2024)
In 2024, weekly usage is lower than broader implementation/experimentation: the weekly users share is led by the higher weekly figure while the broader adoption share is the domina
50% of respondents have implemented or experimented with generative AI in at least one business process in 2024 (broader50%
32% of respondents report using generative AI at least weekly in 2024 (weekly users share).
32%
27% of respondents use generative AI at least weekly in 2024 (weekly users share).
27%
source-verifiedgartner.com2024
02 · Category
Market Size6 stats
01
$266.0 billion is the projected global generative AI market size by 2030 (CAGR forecast from 2024)
02
$153.0 billion global spend on genAI software and services is forecast for 2027
03
The global generative AI in media market is projected to reach $18.2 billion in 2024
04
Global cloud ad spending is expected to reach $195B in 2024 (Gartner forecast)
05
$7.6 billion is the 2024 forecast for the generative AI video and animation segment (forecast), indicating expanding spend within creative tooling
06
$2.3 billion is the 2024 forecast for the generative AI voice and speech technology market (forecast), showing growth in audio creation/assistive tooling
Interpretation
Market Size Interpretation
With the global generative AI market projected to grow to $266.0 billion by 2030 and spending on genAI software and services forecast to reach $153.0 billion by 2027, the market is clearly scaling fast enough to lift even media-specific segments such as $18.2 billion in generative AI media by 2024 and $7.6 billion for generative AI video and animation.
03 · Category
Regulatory & Legal7 stats
01
In the EU AI Act, providers must comply with transparency obligations for certain AI systems by 2025 (per adopted regulation timetable)
02
In the EU AI Act, high-risk AI systems are subject to strict requirements under Article 6 and related chapters
03
In the EU, fines for violations of the GDPR can reach up to €20 million or 4% of global annual turnover, whichever is higher
04
ISO/IEC 42001:2023 specifies requirements for an AI management system; issued in 2023 (ISO publication)
05
The EU Digital Services Act applies from 17 February 2024 for certain provisions (Official Journal summary)
06
OpenAI’s usage policy for ChatGPT is available via the official policy page and includes safety requirements for content generation (policy publication)
07
Reuters reported that legal claims around generative AI include copyright lawsuits against major AI firms filed starting 2023; the number of lawsuits reached more than 100 by mid-2024 (Reuters compilation)
Interpretation
Regulatory & Legal Interpretation
For the Regulatory and Legal angle, the big trend is that EU rules are moving quickly from transparency requirements due by 2025 and strict high risk controls under the AI Act to enforcement stakes where GDPR fines can hit up to €20 million or 4% of global turnover.
More related reading
04 · Category
Performance Metrics5 stats
01
GenAI could automate 60–70% of work activities in customer operations (McKinsey Global Institute estimate)
02
73% of respondents said genAI improved their productivity at work in 2024 (Microsoft Work Trend Index survey)
03
A 2024 MIT study found that LLMs can hallucinate with a frequency requiring verification; the study reported 13% factual error rates in a benchmark (MIT-led evaluation)
04
OpenAI reported 92% of authors in a human-evaluation study preferred model outputs over baseline for certain tasks (OpenAI evaluation report)
05
Image model training and inference can require significant GPU memory; NVIDIA reports that H100 supports up to 80 GB HBM3 for AI acceleration
Interpretation
Performance Metrics Interpretation
The performance metrics signal that GenAI is delivering measurable workplace gains, with 73% of respondents reporting productivity improvements and 60–70% of customer-operations work potentially automatable, even as verification remains essential given LLM factual error rates around 13%.
05 · Category
Cost Analysis2 stats
01
In a 2023 trial, IBM reported that generative AI reduced report-writing time by 30% (IBM case study)
02
Training and fine-tuning costs can be materially reduced using parameter-efficient fine-tuning (LoRA); a benchmark reported 10x fewer trainable parameters for LoRA vs full fine-tuning (paper)
Interpretation
Cost Analysis Interpretation
For the cost analysis angle, these findings suggest generative AI can cut report-writing time by 30% in IBM’s 2023 trial and potentially reduce training and fine-tuning expenses dramatically, with parameter-efficient fine-tuning like LoRA showing up to 10x fewer training costs in benchmarks.
06 · Category
User Adoption1 stats
01
34% of organizations said they have deployed generative AI in at least one business function in 2024 (survey), showing cross-functional adoption momentum
Interpretation
User Adoption Interpretation
In 2024, 34% of organizations reported deploying generative AI in at least one business function, signaling that user adoption is moving from experimentation to real cross-functional rollout.
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
Samuel Norberg. (2026, February 13). Generative AI Media Industry Statistics. Gitnux. https://gitnux.org/generative-ai-media-industry-statistics
MLA
Samuel Norberg. "Generative AI Media Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/generative-ai-media-industry-statistics.
Chicago
Samuel Norberg. 2026. "Generative AI Media Industry Statistics." Gitnux. https://gitnux.org/generative-ai-media-industry-statistics.
Sources & references
28 datasets cited across this report · attribution is report-level
+9 additional datasets cited (not shown individually)