Other parts of this series:
In the first post in this series, we looked at the growth of AI in insurance and its vast potential for transforming processes, products and the customer experience. The potential is great, but insurers seeking to make the best use of these capabilities need an intelligent framework that augments their people’s work, rethinks how they operate with intelligent automation, and unlocks growth through data.
Using AI, for example, people will be able to spend more time on exceptional work, or the 20% of non-routine tasks that drive 80% of value creation. Organizations can re-imagine business models and processes, with smart machines continually reviewing end-to-end processes and applying “intelligent automation of process change” to refine and optimize. And companies will apply AI to greatly enhance large data analytics, evolve algorithms using transactional data more quickly, and combine data in new ways to discover trends.
It’s not a matter of “humans versus machines”; rather, AI is about “humans augmented by machines.” Accenture calls this “applied intelligence.” Insurers will need to support their human workforces in adapting to AI. That includes fostering the right corporate culture and skills base. Retraining will be essential as virtual customer service agents and chatbots automate routine tasks, freeing human representatives to focus on higher-value activities.
AI will also create new jobs – perhaps even new categories of jobs – for the human workforce. Insurers that make extensive use of AI technologies will need humans – data scientists, AI developers and others – with the skills to build, use and maintain these technologies. That means attracting some of the best digital talent into what is perceived to be a slow-moving, traditional industry. Insurers will also need to complement their own human and virtual employees with external resources, including AI vendors and start-ups, and to redesign their approach to outsourcing.
There are other challenges insurers will face as they explore the use of AI. For example, some jobs in the more technical areas of underwriting and claims involve skills that take years to develop. Insurers will need to make tough decisions about automating these jobs. While there may be gains from automation in terms of efficiency and productivity, the insurer may not want to lose the insight and experience associated with the humans who hold these jobs. The C-Suite will need to examine these and other risks as intelligent automation and AI capabilities mature.
Intelligent automation should not simply be about automating existing human processes (along with their flaws). It should be about fundamentally redefining these processes – and maybe even the whole business model – to achieve the best outcomes. Insurers have laid a solid foundation with robotic process automation, creating rules-based virtual workforces with the ability to scale. Now they need to build on those foundations with intelligent automation.
In the next blog, we will examine how insurers can use AI to transform customer service and to unlock the value trapped in data.