Imagine a world where human and artificial intelligence interconnect to create systems and experiences that are smarter than either alone. A robot in a hospital might save precious time assessing a patient by comparing test results to health data collected from all over the world. A device placed at the front door might identify a visitor as a friend, and let them into the house if the homeowner is expecting them.
From solving medical mysteries to making everyday life easier, artificial intelligence is the answer to the question, “What’s next?”
AI has several definitions but in simple terms, it is the ability for a machine to autonomously analyze data, take action, and then learn from the outcomes. Human oversight compounds these insights and learnings.
AI is the next generation of analytics capability. Although work in the field has been going on for decades, recent attention has been brought to the subject again due to the culmination of three key aspects: substantial improvements in computational power, the proliferation of big data, and advancements in deep learning algorithms.
At Fidelity Labs, we’re exploring what the future with AI and machine learning might look like, whether it’s one year, five years or even 20 years from now. AI could create tremendous opportunity in the financial services industry. We want to be on the forefront of this evolution to support the financial lives of our customers.
Throughout our research, looking both internally and externally, we have identified four essential elements that are necessary to the success of an AI initiative.
- NEED | Relevant and Defined
The need must be aligned with the promise of the technology. Even for a technology-driven initiative like AI, we approach the space with a Design Thinking methodology. We understand the problem from different perspectives and build empathy for all stakeholders.
- DATA | Accessible and Consumable
Data is the fuel that drives AI. Actively finding and securely working with consumable data are essential to the success of AI. Through fluid partitioning and governance practices, we are able to leverage data from across the organization.
- INFRASTRUCTURE | Fast and Secure
Access to advanced computational power supports data processing by reducing ‘friction to start’ and ‘speed to market’. With projects in development and more needing exploration, Fidelity Labs recently acquired two Nvidia DGX-1 supercomputers designed for deep learning and accelerated AI analytics.
- SKILL | Trained and Available
Of course, success is only possible with the skill of a diverse team, including: Data Scientists, Engineers, Product, and Design. All work with a deep understanding and appreciation for the needs of our business and our customers.
In 2013, we used machine learning and AI to develop a system that improves the way customer calls are routed to Fidelity call center associates. Many similarly compelling use cases are in development today.
There is great opportunity for us to continue these experiments, to learn from them, and to build AI capabilities. Our aim is to exceed customer expectations as we evolve existing business and technology models.
Could this change the way we do business? Might it uncover new opportunities to enhance our systems and services? We look to the future of AI with excitement and optimism.