Brendan McLoughlin, President of e123, recently participated in an executive education course at the Massachusetts Institute of Technology on Artificial Intelligence (AI) and its implications for business strategy. This is the fourteenth in a series of blog posts where he shares some of the insights he gained and how they apply to health insurance distribution.
According to RAND Corporation, upwards of 80% of artificial intelligence (AI) initiatives fail. This is almost double the failure rate of other technology initiatives, and would probably lead smart executives to conclude that AI projects are not worth the risk. However, the potential for AI to create transformational advantage in health Insurance distribution is real, and the rewards of effectively using AI make it worth discussing how to do things right.
In my last two posts, I introduced the eight mistakes organizations make when trying to implement change. So now let's turn the discussion a full 180 degrees and discuss what business leaders can do to improve the chances of success for AI initiatives.
Baby Steps
The most important step you can take to ensure AI success is a baby step - in other words, start small. AI is a powerful set of tools that has the potential to revolutionize every aspect of health insurance, but it is a mistake to try to do everything at once. Just like other technology tools, AI should be applied to discrete business challenges to create better outcomes. As is often the case with new technology, the edict from leadership is to “implement AI”. Such a broad scope sets up AI for failure, where a tightly defined scope centered around a quantifiable business outcome is more likely to result in success.
We see examples of these baby steps on the claims processing side of health insurance. Rather than attempting to “implement AI”, or even “reinvent” claims processing using AI, smart insurance companies are leveraging AI to marginally improve the process. By focusing on reducing manual intervention and its associated errors rather than completely reinventing the claims process, health insurance companies are saving hundreds of millions of dollars in unnecessary costs.
Similar opportunities for incremental improvement exist on the distribution side of the health insurance industry. A simple example is producer productivity. It is common place to hear health insurance sales executives say that 20% of their agents are responsible for upwards of 90% of their production. Finding a way to activate the next 10% of agents, not all agents, just the next 10%, could have a massive impact on customer acquisition and profitable revenue generation. An AI-enabled commission system, that can test and predict the commission schemes that will best motivate those second-tier agents, might be the simplest and most effective way to use AI to create immediate value.
Small Projects - Big Teams
Too often, AI initiatives are walled off from the organization and siloed into an “AI team”. Usually housed within the tech group, this team is tasked with implementing AI - complete with brainstorming sessions and hackathons. But successful AI implementations require both buy-in and participation from a broad group of stakeholders.
Regardless of the industry, studies show that AI initiatives driven by cross-functional teams have a greater chance of positive outcomes for the organization. In the case of health insurance distribution, this means that business leaders and technology leaders must work together to drive success. We often hear that insurance distribution executives - VPs of Sales, Partnerships, Agency Operations - are tasked with growing the number of producers selling their products. This could be an ideal application for AI, but only if leaders from across the organization come together with a defined objective. Representatives from sales, operations, finance, and of course, technology should work together to define how their organization can attract, motivate and retain the best producers, and then empower a cross-functional team to make it happen.
The Power of Partnership
It is not surprising that studies show organizations that try to “go at it alone” with AI implementations are less likely to succeed. And while it is tempting for health plans and insurance companies to think that building internal AI capability is a strategic advantage, the reality is often the opposite. True sustainable advantage comes from how an organization implements technology, not necessarily from building the capability in-house, which can often be costly and a waste of time and resources.
Similar to ecommerce, cloud computing and payment processing, AI is a core technology that is rapidly evolving and is likely not the core competence of a healthcare organization. The speed, cost and value of AI implementations can be dramatically improved by partnering with a technology firm whose sole reason for being is successfully utilizing AI in real world applications.
Conclusion
While the failure rate for AI initiatives may seem daunting, taking a strategic and measured approach can greatly improve the chances of success. Starting with small, clearly defined projects that tackle specific business challenges, assembling cross-functional teams that bring diverse expertise, and leveraging external partnerships for AI expertise are all key strategies that can help health insurance companies harness AI’s transformative potential. By approaching AI in incremental, collaborative ways, health insurance organizations can avoid common pitfalls and set themselves up for long-term success and competitive advantage in an evolving marketplace.
Want to learn more about e123 and the future of AI in insurance distribution? Get in touch here.
For prior posts in this series, click here or below: