Why do we let artificial intelligence (AI) off the hook when we make hiring decisions and assess people based on performance? There are no job descriptions of, “collect data, run some analytics, and make predictions,” without accountability measures. It is
time for AI to be successful, and for us to address its missing link: the capability to achieve outcomes.
According to Gartner:
Nearly 30% of the 37 million US patients with severe chronic kidney disease (CKD) are not tested prior to stage 3. We discovered, together with a medical lab data management company, that causal AI could yield $7-$11 million in the $700 million field of CKD treatment. During the pilot, we determined that we could use lab records to proactively screen incoming patients and alert doctors about the potential need for early testing.
What would you implement if you had a magic wand? Most organizations are anxious over the fact that they have no idea how to start to solve their biggest problems. Many feel that they are unsolvable.
Causal AI provides a path to action. Outcomes are changed instead of just observing or predicting them (and creates a fundamental shift in value) through data engineering, digital twins, and machine learning. AgileThought has developed a program to help you quickly move from pilot to production.