Where companies are using - and avoiding - Artificial Intelligence
In our latest Concord Tech Talk, our expert panelists discuss the era of AI.
How much are we really doing with Artificial Intelligence? Outside of the Googles and Amazons of the world, what many people are calling “AI” isn’t actually so. Enough with the buzzword, we want the real deal. Read on for the insights from our latest Concord Tech Talks session as shared by panelists Tawfiq Bajjali of Anthem and Pavel Pavlov of HyperAspect.
Perspectives on Artificial Intelligence
The classic definition of Artificial Intelligence is the development of computer systems that mimic cognitive behavior, but AI really entails different levels of learning and looking for patterns in data that normally a developer must specify.
The AI field is incredibly broad and no longer limited to machine learning.
The Changing AI Landscape
The AI landscape just five years ago was barbaric compared to today! Previously left up to statisticians, we now have full-blown toolsets, like Google’s TensorFlow, to jump-start AI adoption.
A combination of factors are driving advancements in AI, including greater awareness of business threats, regulatory drivers, and consumer demand for increasingly personalized products.
Big companies are willing to make an investment in AI intellectual property and have the budget to do so, but smaller companies are leveraging existing platforms to make faster strides.
Where Do I Start?
Above all else, know what you want to accomplish functionally. There are many vague ideas of what AI accomplishes…and often it’s not entirely accurate. Is there a conventional solution to what you want to solve?
Work AI into your current technology footprint in parallel and conduct some innovation activity off to the side. Small, consistent innovations will help reimagine new experiences.
The healthcare industry is using machine learning in fraud prevention. Rather than charging fraudulent payments, companies are working to prevent them from happening entirely by applying AI operationally.
The psychiatry and mental health fields are finding uses for AI in text analysis to pinpoint predictive behaviors that are otherwise undetected.
Retailers in particular are finding ways to incentivize and increase the lifelong value of the consumer through AI.
As an often over-hyped discipline, it’s challenging to separate the practical applications from the buzzword, but ultimately AI is nothing without data. It’s best to start with small innovations and find self-taught resources to supplement your team if you’re just beginning to dabble in the field.