Crafting an AI plan focused on customer service
AI is one of the most talked-about topics among C-suite and CX leaders in 2024. According to research from Capgemini, AI is a top agenda item in 96% of boardrooms. Interest in specific generative AI technologies and tools runs high, with 86% of companies interested in chatbots, 75% in AI-powered data collection analytics, and 71% in text processing. IDC projects that AI systems spending will top $300B in 2026. According to a Forbes Advisor survey, 73% of companies use or plan to leverage AI-powered chatbots for customer service.
This sprawling subject is widely expected to transform many aspects of consumers’ lives as well as how companies do business with customers. Since AI has so much potential to transform insurance company customer experience, CX teams need a smart strategy in order to best evaluate and harness this technology in the years ahead. As the CEO of a CX technology company, I speak with insurance company leaders daily about how they are approaching AI and plan to leverage it. Here’s my take on defining, delivering and implementing an AI strategy and program in the insurance world.
1. Set objectives and goals
Before identifying and deploying AI-powered technologies in your insurance company’s customer experience portfolio, define clear objectives aligned with your firm’s business goals. By clarifying the highest priorities for your work over the next year, you can focus on exploring how AI can help you achieve your top goals.
According to TalkDesk research, companies have many priorities for AI, including improving customer loyalty (54%), improving customer care and outcomes (49%), improving data security and privacy (41%), enhancing CX metrics (38%), and growing profitability (37%). Whether your top priorities are to streamline self-service applications, improve claims processing efficiency, or deliver personalized customer experiences, identifying the most critical use cases will help guide your focus for artificial intelligence. No team has the resources to do everything they might want, but priority-setting ensures you tackle the most beneficial initiatives first.
2. Define goal-driven strategies and initiatives
Defining the best strategies for your company should begin with goals. If goals are what we specifically want to achieve, strategies are the methods by which we hope to achieve them. Any AI initiative should spell out what you and your team hope to achieve and the criteria for determining whether an initiative is a success or a failure.
The AI-powered solution for a specific challenge may be responsible for achieving a company’s entire goal or a part of that goal. For example, an AI chatbot might be how a company hopes to reduce calls that reach live agents by 30%, or it may be one of several tactics being developed to fulfill that target. In either case, having concrete targets and a means to measure success will make your strategy more valuable and actionable.
3. Identify available data assets
AI is driven by access to relevant data. Once you identify your strategic priorities, it’s time to identify the available data sources for addressing each challenge. The appropriate data for each challenge may vary. You’ll need to understand how that data can be accessed and whether it needs to be cleaned or reformatted to serve its role in your AI model. Having a cross-functional team, including data scientists or experts, can help ensure that you can access that data and that it provides maximum value.
The right AI solution for your business will likely require data from internal and external sources. Internal data includes information you have already gathered about your customers, which is usually essential for delivering personalized experiences to each customer. External data sources might consist of third-party databases for account review, risk assessment, application approval, and natural language processing models to help make a customer experience more satisfying and powerful.
4. Develop or purchase appropriate AI tools
The best approach here will vary depending on your needs and your company’s preference for “build versus buy” in technology acquisition. Most companies need partners or tech providers to deploy AI-powered solutions. Working with partners usually accelerates speed-to-market and often lowers costs because multiple businesses can bear the expense of developing advanced analytics and customer-facing experiences through the SaaS software model.
On the other hand, internal software development may allow you to deliver a unique solution for your company’s specific needs. However, internal AI tool development is often costly and time-consuming and requires your internal team to expend resources to keep the solution current.
Fortunately, many use cases in insurance CX are common across multiple companies, so the need for bespoke home-grown solutions is minimized. For example, customers for different auto insurance companies have the same basic needs – applying, onboarding, making payments, filing claims, changing coverages, adding children to plans, and the like. The same is true for most forms of insurance, from homeowners to life insurance.
5. Ensure regulatory compliance and ethical practices
AI is immensely powerful and leverages vast data sets. Insurance companies must ensure that the AI solutions they choose comply with the various data privacy regulations and guidelines where they do business. Data privacy regulations such as GDPR and CCPA mandate stringent data usage and protection guidelines. Ensure you work closely with your legal team to evaluate any tools that will access or collect personal data.
Health insurance carriers must pay particular attention in this area, so they can ensure that highly sensitive health information is protected at all times. Additionally, be prepared to adjust your approaches to CX as laws and accepted practices evolve. Additionally, ensuring transparency and fairness in AI algorithms is essential to mitigate biases and uphold ethical standards.
6. Deploy, monitor and optimize
When you implement your new AI-powered experiences and workflows, measure your progress toward achieving the pre-set targets you established in the goal-setting phase. Like every other element in your CX strategy, you must consider it a work in progress that requires ongoing review and optimization.
Consumer expectations for service and support are constantly rising. The good news is that more and more of your customers prefer digital self-service experiences now than in years past. Great digital experiences that are available across all customer touchpoints can automate even complex processes like claims so that the company gets complete and accurate information and can automatically keep customers and adjusters updated throughout the process.
You can enhance the experiences you have developed based on in-market usage and feedback and implement changes and new experiences as customer expectations and preferences evolve. Both are essential elements of a continuous improvement strategy that can help ensure your company keeps up with competitors and customers.
By defining clear objectives, leveraging data strategically, investing in advanced analytics, and prioritizing ethical considerations, insurance companies can unlock AI’s full potential to drive operational efficiency, enhance customer engagement, and secure a competitive edge in the marketplace.
See more:A forecast of Gen AI in the Japanese insurance industryAI impacts claims for insureds and insurers alike
