Publicação
Challenges and ways to create value with generative AI technology in MC's business model
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| datacite.subject.sdg | 08:Trabalho Digno e Crescimento Económico | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.advisor | Celeste, Pedro Manuel Amador Rodrigues | |
| dc.contributor.author | Lemos, Tânia Cristina Rego | |
| dc.date.accessioned | 2026-06-19T17:56:20Z | |
| dc.date.available | 2026-06-19T17:56:20Z | |
| dc.date.embargo | 2027-06-19 | |
| dc.date.issued | 2025-06-07 | |
| dc.date.submitted | 2025-03-01 | |
| dc.description.abstract | Generative artificial intelligence (GenAI) presents a once-in-a-generation opportunity for companies, with the potential to transform innovation, growth, and productivity. In the retail sector, it promises to unlock value equivalent to a margin increase of 1.2 to 1.9 percentage points (pp) across the industry. MC, a leader in the food retail sector in Portugal, has consistently strengthened its position through technological innovation and was a pioneer in implementing AI-based solutions in Portuguese retail. This case study explores the challenges and opportunities for MC to create value using GenAI in its business model. The investigation included an internal interview with a leader in the innovation area and two surveys: one internal survey for MC employees (88 respondents) and one external survey for supermarket customers (156 respondents). The main conclusions reveal that MC has a well-structured strategy for implementing GenAI, with existing cases already generating value. The surveys indicate high awareness and interest in GenAI among MC employees and supermarket customers, with 98.9% of employees and 80.4% of customers aware of GenAI tools. Usage rates are also high, with 92% of employees and 71.2% of customers having used them. The employee survey reveals a highly positive attitude (95.4%), reflecting the company's innovative culture. However, significant barriers include lack of time to learn (65.9%), insufficient training (61.4%), and inadequate technical support (53.4%). Curiosity (92%) is the predominant sentiment, and confidence is moderate, indicating a need for more training and support. Among customers, while 90.2% recognize the benefits, only 58.2% are willing to share personal data due to trust issues (73.4%). GenAI is seen as most useful for locating products, providing product information, and tracking online orders. | eng |
| dc.identifier.other | 07efdb4e-c5b2-48a7-8f29-a02fe08ba556 | |
| dc.identifier.tid | 204306159 | |
| dc.identifier.uri | http://hdl.handle.net/10400.14/58198 | |
| dc.language.iso | eng | |
| dc.rights.uri | N/A | |
| dc.subject | Digital transformation | eng |
| dc.subject | New technologies | eng |
| dc.subject | Artificial intelligence | eng |
| dc.subject | Generative artificial intelligence | eng |
| dc.subject | Food retail market | eng |
| dc.title | Challenges and ways to create value with generative AI technology in MC's business model | por |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | Mestrado em Inovação e Transformação Digital - Executivo |
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