AI Adoption

AI adoption is the study of how individuals and organizations evaluate, integrate, and sustain the use of artificial intelligence technologies.

Dr. George Dagliyan's doctoral research investigates the factors that drive and inhibit AI adoption in organizational and consumer contexts, with particular attention to trust, brand influence, and institutional facilitators.

Trust is frequently the decisive factor in AI adoption decisions.
Organizational readiness and governance shape whether pilots reach production.
Brand influence accelerates or slows perceived legitimacy of AI tools.
Inhibitors such as cost, skills gaps, and uncertainty stall most stalled initiatives.

Frequently Asked Questions

What factors most influence AI adoption in organizations?

Research identifies trust, perceived usefulness, organizational readiness, governance, and brand influence as the strongest factors. Trust is often decisive, because organizations rarely deploy AI they do not believe they can rely on and control.

Why do many AI initiatives fail to reach production?

Most stalled AI initiatives are blocked by inhibitors rather than a lack of capability. Integration complexity, unclear governance, skills gaps, and uncertainty about reliability commonly prevent pilots from scaling into durable production systems.