Interpretivism and AI: Qualitative Research

Friese (2026) in Sociologica argues that digitization and AI are changing interpretivism and that qualitative researchers must account for quantification while protecting interpretive aims.

• Friese (2026) accepted the article on 7 July 2026 and deposited it on 10 August 2026, showing the argument is anchored to 2026 debates.
• Friese (2026) notes that computational grounded theory claims to “measure” meaning, quoting the phrase that meaning can be “measured.”
• Friese (2026) highlights that interpretivism’s emphasis on multiple meanings and performative social worlds remains distinctive even as AI tools become more common.

Friese (2026) argues that interpretivism is changing because digitization and AI are now part of how people make meaning, and researchers must reckon with those changes.

Friese (2026) defines interpretivism by its focus on multiple meanings, symbolic interaction, and the performative making of social and material worlds, and then asks how quantification and AI problematize those commitments.

Friese (2026) states that while measurement can aid interpretation, measurement and interpretation have different goals, and researchers should be clear about those differences.

Friese (2026) in Sociologica shows that interpretivism and AI intersect in ways that require explicit methodological choices and documentation.

Qualitative teams should state when they use computational methods, preserve interpretive judgment, and report provenance and role of AI outputs in findings.

If your team wants AI assistance that preserves interpretive control and documents processing steps, consider tools that combine automated analysis with human-led hermeneutics.

To try a platform that supports thematic, frequency, and cross-segment analyses while keeping human interpretation central, Try Evidano for free.