Artificial intelligence (AI) has been around for decades, starting in the 1950s with a white paper from Alan Turing on whether machines can think and learn. Since then, global university projects have theorized and developed automation for machine learning. In 1997 two major events occurred: Deep Blue defeated chess expert Gary Kasparov in chess, and Dragon Systems developed the first speech recognition software.

With the maturity of data warehousing and data interchange, AI has come to the forefront of the discussion. Many vendors advertise AI as part of their solution but the question is how is it applied?

To be effective, AI in insurance technology solutions must be applied by use case and carried out on insurance-specific functionality. OWIT’s philosophy is to focus AI on operational and process efficiencies.

OWIT Global’s solutions are rich in functionality. Our team applies AI to our solution use case by use case with the input from our customers to drive our roadmap, i.e., dynamic rules derivation, error correction, and recommendations of data elements.

OWIT believes that AI should be thoughtful and applied against a functional requirement. Once a solution is functionally rich, AI can then be targeted, applied, and tested.

AI is an evolution, not a blanket resolution.