Trust, transparency, encouragement: Starting points for the design of operational AI innovation processes
The triad of rational management ideal models, practical experience and psychological research impulses promises a holistic insight into the processes and design approaches for operational AI implementation.
This ai:conomics Policy Brief complements the economic research on the consequences of AI intro-
ductions conducted by ai:conomics with companies. It thus will invite companies to take a targeted
approach to the conscious design of corporate innovation processes in the technology field of AI, taking uncertainty into account as a key contextual factor for AI innovation. Current practice-oriented process models for the operational introduction of AI innovations serve as the basis for interviews with people with experience in the introduction of AI in large German companies. Scientific findings and models from organizational psychology research enrich the practical reflection with starting points for the targeted design of sustainable operational innovation processes.
These are the main findings:
- Due to the complexity and dynamics of the subject area, operational AI implementation has to deal with an above-average degree of uncertainty. This increases the complexity and intricacy of successful innovation process design.
- The uncertainty factor means that decisions are made on the basis of limited or ambivalent information. This can lead to increased emotional strain, stress or anxiety. Psychological parameters, such as organizational and personal trust, transparency and an organizational culture based on psychological security, can provide positive impetus for courage, creativity and openness in companies.
- Interviewees describe their experiences of AI implementation in three large German corporations as idea development and implementation processes that evolve from manageable innovation-driving circles of actors into a complex operational stakeholder context. As the maturity ofthe content increases, so does the need to argue the benefits, risks and implementation requirements.
- The interviews confirm the influence of psychological parameters on the success of operational AI implementation. Organizational trust can be increased through process standards and transparent communication. Personal trust appears to strengthen decision-making situations with a high degree of uncertainty. Especially in the early phases, psychological security strengthens idea generation.
- The three central internal stakeholders - middle management, works council and rollout partners - and the decision-making situations associated with them in the implementation process can be used as examples to illustrate how the different psychological parameters can interact to strengthen each other.
