The narrative surrounding artificial intelligence in the insurance sector often swings between utopian efficiency and existential dread regarding job replacement. However, for Christopher Frankland (pictured), founder of InsurTech360, the industry’s future is not defined by displacement, but by augmentation. As carriers and brokers navigate the practical hurdles of modernizing their stacks, the goal has shifted toward creating a “bionic” workforce - human experts supercharged by data, rather than replaced by algorithms.
Frankland, a veteran of carrier engineering teams before moving into the insurtech advisory space, argued that the industry’s fixation on total automation often misses the nuance of actual insurance work. He identified a middle ground where technology handles the heavy lifting of data retrieval, allowing humans to focus on judgment and empathy.
“I look at the bionic agent as this future version of the workforce where people aren’t being replaced by AI and technology, but are being augmented by intelligence across every step of the insurance journey,” Frankland said. “It’s really the idea of supercharging how people work today using the right tools at the right time.”
This approach addresses a chronic inefficiency in the sector: the disconnect between customer expectations and the tools available to frontline staff. A customer service representative might possess high emotional intelligence, but without immediate access to policy history or risk data, the interaction stalls.
“They can be as empathetic as they can be when speaking with a customer, but if they don't have the right data and the right tools at their disposal, ultimately it’s going to be a negative customer experience,” Frankland said. “By giving people the right tools, the right data, the right information at the right time, it creates more freedom to deliver that elevated customer experience.”
While the vision of bionic workflows was compelling, Frankland noted that the path from concept to reality remained fraught with technical peril. He drew a sharp parallel between the current wave of AI pilots and the robotic process automation (RPA) boom of the previous decade. Just as companies struggled to scale bot fleets, insurers are now finding that generative AI pilots do not easily translate to enterprise-wide deployment.
“When you think about AI pilots, the question is: how do you take something from POC to production and scale it effectively? That’s perhaps the toughest piece of this whole journey,” he said.
As carriers grapple with these complexities, the perennial debate of whether to build proprietary solutions or partner with external vendors resurfaces. Frankland has observed that while internal development often seems cheaper or more controlled at the outset, the long-term maintenance burden is frequently underestimated.
“On the surface, sometimes it looks quite easy to do some of these things,” Frankland said. “You might look at document OCR and say, ‘Well, that's easy. There are plenty of libraries or cloud libraries that I can use to build something similar.’ The challenge is when you start to look under the hood and go a little bit deeper.”
Once business rules and edge cases were layered on to basic functionality, internal projects often became resource sinks. Frankland advised that unless a capability was a core differentiator, carriers should likely look outside.
“When you're doing it yourself, you eventually have to ask: is this really a valuable use of my time and my team's time to build something from scratch that I could essentially just plug into via an API?” he said.
For those opting to buy, Frankland emphasized the need to categorize potential partners accurately. Not every vendor relationship needed to be a marriage; some were simply functional transactions.
“I think for me, if I'm looking at external partners or people to partner with, first of all it’s understanding what the ask is,” he said. “Is it a single function or capability that I'm looking to integrate into a broader workflow or task?”
However, for broader modernization efforts, the criteria shifted from technical specifications to domain expertise and longevity.
“Is it something that's more transformative and strategic? Is this a bigger, longer-term partnership where I might be looking for somebody to be with me on this journey for the next two to five to 10 years?” he asked.
As the industry moves toward 2026, Frankland predicts a period of experimentation focused on striking the right balance between automation and human intervention. The industry has not always done a great job of automating the right things, he noted, often digitizing friction rather than removing it.
“Broadly, I think this idea of accelerated workflows that are more digitized in the right places is key,” Frankland said. “Thinking about how we work in a more bionic sense speaks to the future of the industry and the things we can achieve as people, before we start thinking about replacing people completely with machines.”
