AI in Packaging Design: What Implications Do Artificial Intelligence Tools Have on the Packaging Designer's Role in Small and Medium-sized Enterprises?

Abstrakt

There is barely an industry left, which is unaffected by the disruptive arrival of
AI technologies (Bounfour, 2022). The question remains how those job fields
that, from a conventional perspective, greatly rely on human skills and
dexterity, will be influenced — such as packaging design where AI has
generated equal amounts of excitement and concern (Ma et al., 2009). This thesis has a particular focus on small and medium-sized enterprises (SME) due to their nature of being more exposed to scarcity of resources, which are usually
required when implementing AI (Cowling et al., 2015). Therefore, this study will
concentrate on the research question of what implications AI tools have on
the packaging designer’s role in SMEs. The study’s research design is guided
by epistemological principles with an interpretive theoretical perspective
following a constructionist, inductive and qualitative mono-method approach.
Seven experts within packaging design, design and AI and its implementation
within SMEs have participated in six in-depth and semi-structured interviews.
Descriptive typologies were applied to examine the data and to abstract the
different types of implications, being visualized in a Folk Taxonomy.

Major findings were that packaging design is a field of multiplicity serving
differentiation, communication and persuading the consumer. The role of the
packaging designer is defined by controlling future-oriented, user-centered and
strategy-driven decisions, brand activation, USPs and ESPs. Furthermore, the
rise of AI tools is stated as a bottom-up movement, while also discussing
technology acceptance, AI vs. human intelligence, the demand for education
and the need for content creation firms to apply these tools. These findings
strengthened the comprehension of the packaging designer’s role with a special
focus on SMEs by identifying seven Modes of Implications being caused by the
utilization of AI tools. These modes include the strengthening of Persuasive
Visualization (1), their Performance Amplification (2), enabling Toolbox
Expansion (3), reinforcing Situational Adaptability (4), implying Specialization
Necessity (5), introducing Validation and Risk Mitigation (6) and encouraging
them to Design Beyond the Status Quo (7). The thesis concludes by discussing
the theoretical and managerial perspectives and suggestions for future research
within the field.