Artificial intelligence was first invented in the 1950s and in the time since its birth,…
Rising anxiety over the wave of new artificial intelligence technologies has percolated into the press who decry the the arrival of artificial intelligence. AI is painted in the popular media like it’s a looming plague on business and workers alike. Headlines tick off alarming projections of job loss and unforeseen business vulnerabilities from machine learning, new automation and big data. Is all of this squawking over intelligent technologies warranted or just so much hype?
The scale of the digital transformation is daunting. Advanced analytics, general AI, machine learning, and natural language processing all are changing the DNA of every industry, or soon will be. Projections are as high as $1 trillion in transition costs and 2.5 million jobs knocked out, 885,000 of those in the Insurance sector alone. But intelligent technologies like virtual insurance software will never eliminate the need for humans to serve insureds.
The primary benefit of artificial intelligence software for the financial and insurance industries is the myriad ways it can improve customer experiences. The newest virtual insurance software has natural language abilities and machine learning, all powered by volumes of data. Front office teams are now able to anticipate clients’ needs, predict when they will welcome additional product offers, and what promotions will entice targeted new customers. The upside for customer service teams is the elimination of the tiresome, repetitive tasks freeing them to focus on helping the customer and building policyholder trust and loyalty.
The biggest risk from the digital transformation that carriers and agencies face won’t be job losses but rather by how well they manage the undeniable change that’s coming. Lack of thoughtful planning and delayed action can lead to sapped resources and ultimately leave insurers on the sidelines missing out on the gains offered by these new tools.
Starting out with AI, firms need to make a full and frank assessment of their strategies and in-house capabilities. Next, bring in help early in the process, securing technology partners and consultants that have been fully vetted and fit the company’s goals and culture is vital. Once the team of experts is assembled, identify AI projects to work on–tasks, workflows and lines of business that could benefit the organization the most from the transformation. At this point, it is best to winnow projects to those with the highest projected returns on AI investments. Finally, phase in artificial intelligence projects in stages instead of a single, large roll out.
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