There is a lot of talk about AI’s impact on digital marketing, but you need data to know if that talk is accurate. While there is a lot of data about it available, much is two or more years old. The speed of AI evolution since ChatGPT was unveiled in 2021 means those statistics are only good for showing how much things have changed.
Here is data about marketers’ attitudes toward and use of AI from surveys conducted in 2024.
Marketers’ attitudes towards AI
- 71% expect generative AI to eliminate busy work and let them focus more on strategic work. (Salesforce)
- 80% want AI to reduce time spent on repetitive, data-driven tasks. (Marketing AI Institute)
- 64% want more actionable insights from marketing data. (Marketing AI Institute)
- 70.6% believe AI can outperform humans in some way. (InfluencerMarketingHub)
- 50.6% expect AI to greatly enhance marketing efforts (InfluencerMarketingHub)
- 67.3% expect AI will soon be making high-level strategic decisions. (InfluencerMarketingHub)
- 63% say most content in 2024 will come from gen AI. (Synthesia)
- 56% say gen AI content outperforms human content. (Synthesia)
Employment concerns
- 59.8% fear AI could jeopardize their employment vs. 35.6% in 2023 (InfluencerMarketingHub)
- 47% say AI will eliminate more jobs than it creates in the next three years, a 7 percentage point jump from 2023. (Marketing AI Institute)
Belief AI will eliminate jobs, by employees’ place in the organization:
- 50% of Executives (CEOs/Presidents, CMOs, and Other C-suite executives)
- 39% of Managers
- 40% of Entry level (Marketing AI Institute)
Use concerns
- 60% are concerned AI content could harm brands through biases, plagiarism and value misalignment. (Synthesia)
Marketers top three concerns about AI in general (Salesforce):
- Accuracy and quality
- Trust
- Job loss
Marketers’ top three concerns about generative AI (Salesforce):
- Data exposure or leakage
- Lack of necessary data
- Lack of strategy or use cases
Marketers’ use of AI
- 85% of B2B marketers use gen AI, 76% are satisfied or very satisfied with the results. (Pipeline360)
- 99% are personally using AI in some fashion. (Marketing AI Institute)
- 69.1% have integrated AI into marketing operations. (InfluencerMarketingHub)
- 36% have AI infused into daily workflows, vs. 29% in 2023. (Marketing AI Institute)
- 15% “couldn’t live without AI” vs. 6% in 2023. (Marketing AI Institute)
- 24% say customer service AI is most helpful for their business. (Synthesia)
Marketers’ top AI use cases: (Salesforce)
- Automating customer interactions
- Generating content
- Getting performance analytics
The most common uses of gen AI by marketers: (Salesforce)
- Basic content creation (76%)
- Writing copy (76%)
- Inspiring their creative thinking (71%)
- Analyzing market data (63%)
- Generating image assets (62%)
Level of understanding of gen AI (Marketing AI Institute)
- Intermediate: 61% vs. 54% in 2023.
- Advanced: 16% vs. 11% 2023
Implementation
- 32% of marketing organizations have fully implemented AI. (Salesforce)
- 43% of marketing organizations are experimenting with it. (Salesforce)
- 51% are either piloting or scaling AI vs. 42% in 2023. (Marketing AI Institute)
- 42.2% say GenAI has led to transformative changes in marketing strategies. (InfluencerMarketingHub)
- ~70% report technical challenges with AI marketing software: integration, compatibility, steep learning curve. (InfluencerMarketingHub)
Barriers to adoption
- 71.7% of non-adopters say lack of understanding is main barrier vs. 41.9% in 2023. (InfluencerMarketingHub)
- 67% say lack of education and training is the top barrier vs. 64% in 2023. (Marketing AI Institute)
- 23% say organization has AI education/training for the marketing team. (Marketing AI Institute)
- 39% of marketers don’t know how to use gen AI safely. (Salesforce)
- 43% say they don’t know how to get the most value out of gen AI. (Salesforce)
- 54% say gen AI training programs are important for successfully using it in their role. (Salesforce)
- 70% say employer does not provide gen AI training. (Salesforce)
Top AI organizational barriers to adoption of AI
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