This study evaluates whether generative AI tools built on the language model GPT-3 can streamline the processes of digital marketing agencies. The method used for gathering qualitative data was two sets of semi-structured individual interviews with different digital marketing agencies. The agencies were interviewed regarding frequent processes, AI usage, and attitudes toward the technology. Two ChatGPT experiments were conducted to get the interviewees’ insights on its use and the results. The data was categorized with the help of qualitative content analysis. Previous research and journals were additionally used to discuss the potential and consequences of AI, GPT in general, and GPT-3. Information about the different tools that use GPT-3 was collected through websites, articles, and blogs. The study’s data shows that tools using GPT-3 can streamline repetitive or time-consuming processes within ideation, content production, data analysis, personalized customer interactions, and increase productivity within digital marketing agencies. The tools’ tendencies to produce discriminating, faulty, generic, or uncreative information nevertheless create the need for constant human monitoring, source criticism, post-processing, and complementing with creative inputs. Researchers recommend the method of post-processing generative AI results. Digital marketing agencies have already begun implementing this method. Agencies’ attitudes toward the technology’s future within the industry are generally positive. The technology might, according to the interviewed agencies, become a threat to digital marketing professions in the future. This threat may occur if AI develops the creative ability to produce material that evokes emotions in the same way humans currently can. The agencies also believe that the technological change within the industry will come with new copyright laws, regulations, and pricing structures emphasizing creativity and competence.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-66022 |
| Date | January 2024 |
| Creators | Ekman, Hampus, Strand, Erik |
| Publisher | Malmö universitet, Fakulteten för teknik och samhälle (TS) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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