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AI in practice

What drives AI adoption at an accounting firm?

A qualitative study of the drivers and barriers for AI adoption at SpareBank 1 SMN Regnskapshuset, and how employees see its effect on efficiency and profitability.

Why this case

Accounting is one of the fields where AI is expected to change the most: routine bookkeeping, reconciliation and reporting are exactly the tasks the tools are good at. Whether that potential turns into real efficiency depends on people and organisations, not just on the technology.

Research design

  • Seven semi-structured interviews with informants from five departments, to capture differences across the organisation.
  • Abductive approach: moving between the theory and what the informants actually said.
  • UTAUT to understand adoption at the individual level: expected performance, effort, social influence and facilitating conditions.
  • TOE to understand the organisational level: technology, organisation and environment.

One group member works at SMN. We treat that as a possible source of bias and address it openly in the method.

Findings

A summary of the main drivers and barriers will be added here.

What companies can take from it

Combining an individual and an organisational framework makes it possible to separate the problems that training can fix from the ones that need changes in structure, systems or leadership.