EXPLORING THE IMPACT OF AI ON GRAPHIC DESIGN EFFICIENCY- A DUAL APPROACH THROUGH SLR AND EXPERIMENTAL COMPARATIVE TRIALS

Abstract

Integrating artificial intelligence (AI) into graphic design software has transformed workflows, enhancing efficiency and creativity. This research combines experimental trials and a systematic literature review (SLR) to evaluate AI's impact on workflow efficiency in Adobe applications. The SLR analyzed 14 academic articles published between 2020 and 2024, selected from 1,515 articles identified via Google Scholar. It focused on topic areas, methodologies, possibilities, limitations, and future recommendations. Notably, 71.43% of the reviewed articles were published in 2023–2024, reflecting growing research interest. Methodological trends showed a dominance of qualitative studies (71.43%), followed by mixed methodology (21.43%) and quantitative research (7.14%). The experimental design examined four Adobe tasks: auto-reframing, sky replacement, smart object selection, and object removal. Each task was performed manually and using AI features. AI-assisted methods reduced time by 56.05% on average, with workflow steps decreasing from 12.14 (manual) to 4.29 (AI-assisted). Statistical analysis confirmed significant improvements (p < 0.001, Cohen's d: 2.854 for steps, 1.134 for time). Despite substantial efficiency gains, limitations include the narrow focus on Adobe tools, specific tasks, and reliance on 14 articles published between 2020 and 2024, suggesting the need for broader analysis to generalize findings.

Keywords

• AI-Enhanced Design Communication
• Digital Media Workflow Optimization
• Computer-Mediated Design Processes
• Visual Communication Automation
• Human-AI Creative Collaboration

Supporting Institution

4th International Symposium on Communication in the Digital Age ©CIDA 2024 - IEEE

YAPAY ZEKANIN GRAFİK TASARIM VERİMLİLİĞİNDEKİ ETKİSİNİN ARAŞTIRILMASI: DENEYSEL KARŞILAŞTIRMALI DENEMELER VE SLR İLE İKİLİ BİR YAKLAŞIM

Abstract

Yapay zekayı (AI) grafik tasarım yazılımlarına entegre etmek, iş akışlarını dönüştürerek verimliliği ve yaratıcılığı artırdı. Bu araştırma, Adobe uygulamalarında AI'nın iş akışı verimliliği üzerindeki etkisini değerlendirmek için deneysel denemeleri ve sistematik bir literatür incelemesini (SLR) birleştiriyor. SLR, Google Akademik aracılığıyla belirlenen 1.515 makaleden seçilen, 2020 ile 2024 arasında yayınlanan 14 akademik makaleyi analiz etti. Konu alanlarına, metodolojilere, olasılıklara, sınırlamalara ve gelecekteki önerilere odaklandı. Özellikle, incelenen makalelerin %71,43'ü 2023-2024'te yayınlanmış olup, bu da artan araştırma ilgisini yansıtmaktadır. Metodolojik eğilimler, nitel çalışmaların (%71,43) baskın olduğunu, bunu karma metodolojinin (%21,43) ve nicel araştırmanın (%7,14) izlediğini gösterdi. Deneysel tasarım, dört Adobe görevini inceledi: otomatik yeniden çerçeveleme, gökyüzü değiştirme, akıllı nesne seçimi ve nesne kaldırma. Her görev manuel olarak ve AI özellikleri kullanılarak gerçekleştirildi. Yapay zeka destekli yöntemler, iş akışı adımlarının 12,14'ten (manuel) 4,29'a (AI destekli) düşmesiyle ortalama %56,05 oranında zamanı azalttı. İstatistiksel analiz önemli iyileştirmeleri doğruladı (p < 0,001, Cohen'in d: adımlar için 2,854, zaman için 1,134). Önemli verimlilik kazanımlarına rağmen, sınırlamalar arasında Adobe araçlarına dar odaklanma, belirli görevler ve 2020 ile 2024 arasında yayınlanan 14 makaleye güvenilmesi yer alıyor ve bulguları genelleştirmek için daha geniş bir analize ihtiyaç olduğunu gösteriyor.

Keywords

• Yapay Zeka Destekli Tasarım İletişimi
• Dijital Medya İş Akışı Optimizasyonu
• Bilgisayar Aracılı Tasarım Süreçleri
• Görsel İletişim Otomasyonu
• İnsan-Yapay Zeka Yaratıcı İşbirliği

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