A Tale of an AI Summit

If you had the opportunity to attend the AI Summit on December 10, 2019 at The Javits Center in New York, one thing would have become very apparent: that AI is no longer a concept, hype, or something that is years from reach. It is a technology that is real; it is a technology that has been adopted; and several verticals have already begun differentiating their business with this next wave of innovation. 

The conference was organized with several stages: a Delivery Stage for Visionary CxO, an Implement Stage for Senior Strategists, and a Develop Stage for Technical Leads. In addition, there were areas focused by verticals such as Retail, Finance, Healthcare & Sales Marketing, each speaking to how they have managed to leverage AI to improve their customer experience, optimize their business, or differentiate themselves in the marketplace.

I was able to attend several talks with a wide array of topics ranging from high level strategy to deep implementation as well as case studies speaking to best practices. Here, I’d like to synthesize some of the knowledge I gained from the conference and share what I was extremely clear: if a business has not defined their Data and AI Strategy, they should be making it a priority for 2020.

Making It Real

The conference kicked off with an insightful keynote given by Lori Beer, Global Chief Information Officer from JPMorgan Chase.  She discussed what JPMorgan is doing to leverage AI and also shared the best practices on how to define a Data and AI Strategy: take into consideration data management, invest in research, define governance models for risk control, develop and hire the right talent, prioritize the right use cases, and build a common platform within the business to reduce infrastructure complexities. 

She also stressed that  Data and AI cannot be treated as a grassroots pet project – a mantra that was repeated on multiple occasions in multiple talks.  Data and AI requires buy-in and executive sponsorship. Executives must be involved at the onset in order to get adoption off the ground, to tear down the silos within the business, and to help build the appropriate data foundation to enable the business to leverage the capability. Like most digital transformation initiatives, this one is no different and requires leadership from the top to prioritize the development of a data platform that will allow AI to be leveraged.  Lori spoke of how JPMorgan started with a business leader that would be impacted by AI had them partner with the CTO to help remove all barriers to make AI a reality.

Insurance 

I also visited the Finance Summit section at the conference where I heard the uses cases of AI and how it is being leveraged to help lower premiums, increase safety and improve the claims experience. 

By leveraging AI, insurance companies can recognize that a customer is experiencing an issue, proactively reach out to that customer, and provide a timely resolution. For example, you have a flight to NY and for reasons beyond your control you are running late, which will lead you to miss your flight.  Your purchased flight insurance provider, however, predicts this scenario and reaches out to you to book you on a later flight. These are the type of uses cases that will help insurance companies increase their market share with a competitive advantage because they harness contextual data and build value for their users.

There were several other examples where they talked about how AI will help reduce the claims cost for insurers, provide better risk pricing, and modify risky behavior. For example, a driver that drives above the speed limit or doesn’t maintain their car appropriately by changing tires or brakes on the vehicle would receive higher rates, while a driver who does obey the speed limit and regularly maintains their car would receive lower rates. This is already possible as telematic systems are able to provide this data to insurance providers.  With this data, insurance providers can offer better premiums and affordable insurance to the appropriate customers.

Healthcare

At the Healthcare summit, a case study was presented around a system of physicians, hospitals, and communities (TriHealth) and its desire to reduce patient readmissions. Hospital readmissions cost Medicare roughly $26 billion annually, with about $17 billion spent on avoidable hospital trips after discharge.  Based on a Healthcare Cost and Utilization Project Statistical Brief released by the Agency for Healthcare Research and Quality, the average cost of readmission for any diagnosis in 2016 was $14,400.  Clearly, the cost of readmission causing a drain on hospital resources and a negative financial impact on patients. 

TriHealth leveraged Natural Language Processing to extract data and built the ability to predict future patient readmissions across all diseases and conditions.  This solution resulted in a 52% improvement in readmission accuracy. In addition, it optimized a hospital’s resource efficiency which enabled leveraging resources to spend more time proactively engaging patients, thus improving the patient experience at hospitals.   With the help of AI, TriHealth was able to release patients earlier or keep them to provide extra care for a few more days if needed, effectively preventing readmissions.  

This is a great example of how this technology can be leveraged to improve not only a business by increasing efficiency, but most importantly how it is improving the quality of life for their customers – in this case their patients. In this scenario, AI isn’t replacing humans, but giving them more time to provide the patient the care that should be given to anyone recovering from a health condition.

Auto Industry

With the help of AI, an automotive industry company, Hyundai Motor Company, is also disrupting its vertical by adopting Conversational UX. With this technology, it is able to provide targeted information quickly to their customer base, keeping them engaged.  Hyundai has also provided a means for their customers to interact with their vehicles from the comfort of a conversation within their own homes. These features enrich the experience of shopping for or interacting with vehicles thus creating retention with the customer base.  

Hyundai has developed an intelligent assistant that provides a voice-enabled AI providing line-up of vehicles based upon questions asked by the prospect consumer.  Customers asking “Which vehicles gets the best gas mileage” would first be presented with Hyundai vehicles with that best ranking, providing them a short-list of vehicles that meet their needs. 

Hyundai has also leveraged Conversational UX to allow controlling settings on your vehicle from the comfort of your home with their BlueLink Alexa Skill.  The Alexa Skill allows a user to conveniently start their vehicle, lock it, change the temperature, and more. 

Conclusion 

Overall it was a very insightful conference with a plethora of inspirational case studies to help businesses learn what to take into consideration. Attendees were also able to network with others who have begun their journey of adopting AI as a capability in their business.

Much like most digital transformation initiatives, the first step is always the hardest. But a journey of a 1000 miles is taken one step at a time. It doesn't have to be large steps either. What is most important is just getting started and beginning the process of continuous innovation and learning.  

So, break some eggs and perhaps in the next conference, I will hear more about your case study on how you have unlocked the value of your data and leveraged AI for your business.