Despite rapid advancements in artificial intelligence and automation, many insurers are still failing to translate technology investments into measurable productivity gains. According to Puneet Chattree (pictured), insurance industry lead at Accenture Canada, the barriers are no longer technical – they are structural, strategic, and cultural.
Chattree said that while insurers recognize the potential of AI to transform efficiency and competitiveness, many remain caught in outdated approaches that prevent true scale. “Let’s forget for a moment about the economy or national policy,” he said. “If every company looks inward – if each insurer really took control of how they want to drive this productivity gap – the question is: what’s holding them back?”
The first and perhaps most fundamental problem, Chattree said, is that many insurance leaders still equate productivity with cost reduction.
“Not every organization thinks about productivity; they think about cost,” he explained. “They drive outcomes around cost – reducing it by a hundred basis points to return value to shareholders or members. But cost is only one part of the equation.”
True productivity, he argued, isn’t just about efficiency, it’s about becoming smarter and more effective in how insurers achieve outcomes. That shift requires reframing productivity as a strategic lever rather than an accounting exercise.
“You have to start at the top,” he said. “Thinking about productivity as a key lever of value – and then asking, ‘Where are we going to get those productivity gains from?’ Not just cost, but productivity across the entire business.”
Even among insurers that have launched AI programs, Chattree said a common obstacle is strategic fragmentation – where AI roadmaps are built independently from the company’s core business goals.
“We hear a lot from insurers, ‘We’re creating our AI strategy,’” he said. “And I often sit there and ask, ‘How are you embedding that into your business?’ Because you shouldn’t have two different strategies. You should have one.”
AI, in his view, should be integrated as an enabler of broader transformation, alongside process redesign, smarter data management, and new organizational structures that reduce silos and decision bottlenecks. “There’s AI you can use for that, yes,” he added. “But the real question is: are you structuring the organization itself to move faster?”
Many insurers, he said, still rely on hierarchical decision-making models that make it difficult to deploy AI solutions quickly or adapt processes around them. You can have the best models in the world, Chattree noted, “but if you need six approvals to deploy a pilot, you’re not going to move the needle.”
Another factor holding back transformation is what Chattree calls the use case mentality – focusing on isolated AI applications rather than reimagining the entire value chain.
“When we think of use cases, we can drive an outcome in one area,” he said. “But when we think about the value chain, we can ask: with the use of technology, how does this whole process change?”
In claims, for example, Chattree said insurers often fail to see how AI can streamline workflows from end to end.
That same thinking applies in marketing and lead generation, where many insurers still treat segmentation and outreach as separate functions.
“A really good example we talk about is personalized marketing,” he said. “It feels personalized – but it’s actually just smarter lead generation and segmentation. The automation behind it makes it more seamless and relevant to the customer, whether through a broker or direct-to-consumer.”
Thinking in terms of value chains, he said, forces insurers to look at how technologies like AI, automation, and data analytics can transform how work gets done – not just which task gets automated.
Even as insurers work to close these gaps, Chattree warned that many are underestimating the skills transformation required to support large-scale AI adoption.
“We often talk about this idea that it’s not just about reimagining the work – it’s about reimagining the workforce,” he said. “You have to think about what skills will be needed five years from now to deliver on that strategy.”
That includes identifying which parts of the current workforce can be upskilled to operate effectively in AI-enabled environments, and where gaps must be filled with new talent. When we think about the workforce required in an AI-native model, he said, very few carriers or brokers have thought about what that means in terms of the skills they need to attract today so that they’re ready for tomorrow.
In personal lines, for example, insurers are beginning to explore more digitally native business models that leverage AI to improve margins and responsiveness. But without a parallel workforce strategy, those ambitions risk stalling.
Ultimately, Chattree believes that most insurers’ challenges come down to integration – between business strategy, technology execution, and human capital planning.
“It’s about connecting the dots,” he said. “If AI is built separately from business priorities, if productivity is treated as cost-cutting, and if workforce planning is an afterthought, you end up automating the wrong things.”
He emphasized that the technology itself is no longer the bottleneck. “The capability exists,” he said. “What’s missing is the alignment, the clarity of vision, and the courage to redesign around it.”
That redesign, he added, is what will distinguish the insurers that merely implement AI from those that truly transform through it.
