In enterprise environments, AI adoption depends on more than technology. Companies need to be confident that it works reliably in real operations.
In a recent interview with Analytics Insight Magazine, Gabriel De Dominicis, CEO of KAPTO AI, shares how organizations can move from early AI initiatives to practical, day-to-day use.
With over 25 years in tech entrepreneurship, his perspective is focused on execution. AI only becomes valuable when it can handle real processes consistently, at scale, and within regulatory requirements.
At KAPTO, the focus is on improving how document-heavy processes are managed across operations.
This includes:
- Reducing processing time
- Limiting manual intervention
- Ensuring consistent decisions
- Increasing visibility and control over workflows
In regulated and high-volume environments, these improvements directly affect cost, risk, and service quality.
As discussed in the interview, many companies are still testing AI in isolated use cases. The challenge is making it reliable enough to support core operations.
Gabriel highlights a few key principles:
- Trust is built through consistent, measurable results
- AI should integrate into existing processes
- Control, transparency, and reliability are critical for adoption
Read the full interview here: Analytics Insight Magazine: Gabriel De Dominicis on Building Trust in Enterprise AI
