Why BCG Urges Insurers to Target AI to Stay Competitive
Insurers invest heavily in AI, but many still fail to realise its full value.
A new report from Boston Consulting Group (BCG) warns that the industry risks wasting opportunity by spreading resources too thinly across too many functions.
Instead, insurers are advised to target AI at specific high-impact areas to create tangible improvements in profit and loss.
BCG prioritises value over volume
BCG’s analysis highlights that companies gain most when they concentrate AI resources in a few high-value areas before expanding efforts elsewhere.
Functions like underwriting, customer service, claims and sales deliver measurable results when AI is applied at scale.
For commercial property and casualty insurance, especially in the US and UK, BCG reports AI can improve efficiency in complex lines of business by as much as 36%.
This stems largely from augmenting human underwriting with machine support.
Using previously inaccessible unstructured data in underwriting decisions may also improve loss ratios by up to three percentage points.
In customer service, insurers equipping staff with AI tools have seen productivity gains above 30%. Much of that comes from deploying knowledge assistants – systems that provide employees with quick access to critical data and answers – accounting for nearly two-thirds of the gains in this area.
The logic is clear: start where AI can make the biggest operational and financial difference, then expand.
Broad strategies that aim to apply AI in every function at once dilute value and complicate implementation.
BCG warns that when AI efforts are limited to isolated tech departments, businesses risk creating disconnected tools with little impact on wider goals.
Claims and cloud migration: High-yield opportunities
Claims management shows some of the clearest results from AI adoption.
Automation tools are transforming areas like first-notice-of-loss data capture, document processing and triaging. These standalone applications reduce costs by up to 20% and increase claims processing speeds by up to 50%.
For basic claims, automation is now enabling real-time resolutions in up to 70% of cases.
This cuts operational costs by 30% to 50% and improves customer satisfaction through faster and more transparent service.
On the sales side, AI’s role depends on the distribution model.
In direct channels, AI-powered agents process large volumes of leads and guide customers to suitable sales paths.
Meanwhile in broker-based models, AI automates administrative tasks that typically occupy over half of an agent's time, lifting their productivity and freeing up focus for higher-value client work.
Another area where insurers are seeing real impact is within information technology.
One European insurer is rolling out an AI-led “smart migration” programme aimed at transitioning over half its product base from legacy systems to cloud platforms.
BCG notes that the project is expected to cut migration time by 50% and reduce associated costs by 30%.
In software development and IT operations, AI is streamlining delivery.
Coding assistants accelerate writing, refactoring and testing. Virtual agents automate level 1 support, freeing technical staff to handle more complex queries.
Rethinking the operating model for AI success
BCG doesn’t just call for smarter technology deployment, it urges insurers to rework their operating models and track AI outcomes directly through the profit and loss sheet.
One of the biggest risks for insurers taking a passive or late-follower approach is the failure to develop the necessary human capabilities alongside AI systems.
BCG suggests a resource allocation model where only 10% goes to algorithms and 20% to tech and data.
The rest should be invested in people—training, roles, workflows and cross-functional collaboration between IT and business.
Too often, insurers fall short by not adapting internal structures and failing to align new tools with strategic goals.
AI, BCG argues, cannot replace business direction but can dramatically accelerate it if correctly applied.
“Most companies do not go the extra mile of redesigning the operating model and value tracking to the P&L,” BCG says, noting that success requires substantive changes to operating models and cross-functional collaboration between business and IT departments.
AI in insurtech is not just about innovation – it’s about making targeted changes that deliver measurable outcomes.
Firms that succeed will be those that apply AI deliberately, reshape their operations around it and empower their people to use it to full effect.
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