Women in AI: Elena Sanz Varela
Elena Sanz Varela always liked to build things. “I like a material outcome, something tangible that I can touch with my hands and see with my eyes,” she says. To Elena, success means seeing a project fully implemented. As Channel Architecture Director at Bankia, one of the largest banks in Spain, this means seeing a solution successfully deployed and operational within the bank. “The project is not complete if no one is using the solution yet,” she says.
Before her current role at Bankia, Elena was at Accenture for nine years, where she shifted into new roles every year and learned new skills around consolidating architecture principles, working cross-functionally with global teams throughout the UK, Portugal, and India, and applying new and emerging technologies. With this foundation and wide-ranging experience, Elena felt confident and prepared for her role with Bankia.
Elena is responsible for two departments. One is to develop strategy and new ideas for architecture supporting channels, including utilizing web and virtual assistants, and defining the bank’s multi-cloud strategy. The other is to develop chat, such as IPsoft’s Amelia, and voice assistants like Amazon’s Alexa. Elena supports other Amelia and AI projects as well, with primary responsibility for the development for some projects, and assisting other departments with AI implementations.
Elena believes that the finance industry can utilize AI to improve efficiency around cost, staffing and speed of services. “Automation is key,” she believes. To her, this means reassigning staff members to higher-value tasks and allowing AI technology to handle manual processes. She enjoys that the AI industry grows so quickly and that there are opportunities to apply AI to many different fields, tangibly helping clients with their strategic business goals.
Although there remains some fear around AI’s role in today’s workforce, Elena believes it’s because AI is misunderstood, and needs to be explained in a clear, comprehensible way. “People think the way AI works is like magic, which leads to incorrect expectations of timelines for implementing the technology,” says Elena. Currently, AI is still only in a test or pilot phase for many companies, substantial training is required, and it is still considered expensive, even when there are significant opportunities to increase revenue by using AI . Nonetheless, there are plenty of examples of AI use cases that ultimately save money and improve operations, but it takes time to reach those goals, she says.
Elena is a firm believer that working in STEM and AI should be unrelated to gender. She says that attracting more women to pursue STEM careers can be accomplished by leading by example and introducing young women to today’s female industry leaders early on in school. Showing students that the future is limitless, and that ideas can transform society, is a good starting point. Her advice to women looking to join the field: “Be yourself. Fight to be heard and give your opinion. Work with diverse groups.”
In the future, Elena looks forward to seeing a more human, emotional connection with technology. She hopes for more engagement and trust from users by removing the fear around sharing information with AI solutions, by companies taking data security and privacy seriously. She also believes that with time, a more mature and professional experience with AI solutions will emerge in various business cases, and users will have more trust and fun using them as a result.