For decades, insurers benefited from a stable business environment with relatively straightforward risk and capital management considerations. However, business as usual has turned into business as unusual. Social, technological, economic, environmental and political risks have become increasingly volatile. As a result, covering more frequent and severe loss events while operating a capital-intensive business is much more challenging.
Because of these challenges, we regularly tell carriers—traditionally a cautious lot— there's an urgent need for change. But we also tell them that there is great potential for reinventing their businesses and operations, redefining the very nature of insurance. Considering the obstacles the industry faces, why are we optimistic?
For starters, technology is enabling business and operational improvements that until recently could only be dreamed of. Satellites, drones and sensors are increasingly connected and provide more and better data that help carriers and their stakeholders manage property, health and longevity risks in real time, not just retroactively. In fact, we’re nearing the point where insurers, armed with deep insights into what causes loss and how, can move from just compensating stakeholders after claims events to helping them avoid loss in the first place—a truly profound reinvention of the meaning of insurance.
As we describe in further detail later in this report, we’re seeing certain trends emerge in an industry that’s moving beyond its traditionally incremental approach to change:
New opportunities at the nexus of life, health and wealth. Growing consumer expectations for customer-focused rather than product-centric offerings are causing insurers to consider more holistic coverages, with ongoing education and advice being a key part of their value proposition. Notably, an aging population with urgent questions about retirement affordability and potential coverage gaps is creating new opportunities for carriers at the intersection of life, health and wealth. For example, rather than just selling a customer a traditional annuity in a one-time transaction, insurers—as part of a network of carriers, health, and supplemental coverage providers—can help individuals calculate total expected retirement spending and then plan coverage, investments and future disbursements accordingly, with each provider reengaging the customer at appropriate life stages.
To make this work, carriers should change from product- to customer-centric organizations that provide holistic solutions over the long term. This requires business and operating models that are fit for purpose, as well as appropriate technology and partnerships that facilitate seamless distribution and service.Responsibly governed AI that supports workers. To take meaningful advantage of an ongoing surge in information—from financial performance to operational risk to customer behavior—carriers have access to increasingly powerful AI tools, including agentic AI and deep learning. These resources can process and interpret data related to general trends, specific incidents and individuals in a fraction of the time and expense required just a few years ago, quickly recommending actions for underwriting, advisors, policyholders and customers.
That said, the human element remains vital. When deployed appropriately, AI doesn’t take jobs but enhances both them and the bottom line. And in fact, insurers aren’t ready to fully rely on AI-driven recommendations because of concerns about accuracy and bias. Therefore, responsible governance of AI and its outputs is critical, particularly for brokers and agents as they attempt to provide trustworthy advice that maintains the integrity of the carrier’s reputation and capital.
An increasingly strategic role for IT. Modern operational infrastructure and AI advancements are changing the nature of carriers’ technology investments and the IT function itself. Not having to build and maintain on-site systems can free IT from being primarily a maintenance function to one that strategically guides insurers’ business, with a focus on innovation that fuels growth. This can come from identifying—or even developing—promising new technologies and joining in appropriate partnerships and ecosystems where stakeholders can complement and enhance each other's capabilities to meet customer and policyholder needs over the long-term.
The growth of private credit. Private equity investment in (primarily) life and retirement providers has caused carriers to further reevaluate their strategies and product offerings, as well as how they invest their capital. This has led to increasing involvement in private credit—certainly not a new concept or vehicle for insurers but on a considerably larger scale than in the past. As a result, carriers are conducting detailed operational, actuarial and financial analyses to reshape business models, assess and govern risk, more effectively allocate capital, and refine their product portfolios to better align with emerging market demands and opportunities.
An industry on the brink of a breakthrough
Taken together, what do these developments portend? They indicate a growing commitment by insurers to improve business and operating models and work in concert with a variety of partners to create innovative ways of safeguarding people and property. Despite the industry’s traditional reluctance to embrace transformative change, the myriad shocks of the past 25 years have moved the industry beyond a tipping point. Carriers are closer than many think to breakthrough innovation and growth and, because they're fully aware change will continue with or without them, many are no longer intimidated by the prospect of reinventing their businesses.
New opportunities at the nexus of life, health and wealth
Retirees live longer than they used to, and with that comes the need to tap into savings over many years, including during often extended periods of dependency. Yet most people remain unprepared for the realities of retirement, as evidenced by the fact almost half of Americans don’t have a retirement account and only about a quarter have more than $100,000 in retirement account savings.
More than a matter of cost, a matter of preparedness
Unfortunately, retirement planning is often an afterthought. Many retirees and their families mistakenly believe that Social Security, Medicare and/or Medicaid will cover their costs and serve as a fallback option without understanding eligibility qualifications that frequently require spend-downs or exhausting of other assets before a true benefit can be provided.
Of note, for those who become dependent, annual long-term care (LTC) expenses for an individual usually run in the high five figures, and often more. Families often wind up covering much of this amount and related burdens, including unpaid caregiving by relatives. On a national scale, this imposes significant social and economic costs.
Further complicating matters, federal budget rules could shrink Medicare payments over the coming decade, squeezing providers and reducing access at a time of high demand. For retirees, this could translate into higher out-of-pocket costs, fewer doctors who take Medicare and longer waiting times to see medical professionals.
Simply put, under the current system, government programs, insurers, and most individuals and their families can’t cover retirement’s aggregate financial costs and care needs. Institutional capacity, knowledge and planning remain dangerously underdeveloped for an aging population, despite a corresponding increase in the need for savings and care. Yet retirement solutions, including annuities and other supplemental health benefits, rarely take into account the full range of possible retirement costs.
By shifting from product-centric offerings to holistic advice and partnerships, providers can both reduce risks for aging populations and differentiate themselves from competitors.
Creating an integrated retirement ecosystem
The convergence of these life, health and wealth concerns requires a proactive, cross-sector system of well-being that combines financial security with health and caregiving support, rather than a fragmented set of financial, insurance and healthcare transactions. By shifting from product-centric to holistic offerings, enabled by new tech and partnerships, providers can both reduce risks for aging populations and differentiate themselves from competitors. Comprehensive benefit packages should include health coaching, predictable drug and LTC cost management, and digital platforms that connect families, providers and advisors in real time.
Examples include:
- Enhancing benefit design to integrate LTC financing, caregiving support and health expense management alongside traditional retirement and other voluntary benefit products.
- Expanding alliances across sectors with healthcare systems, insurers, housing and technology firms to develop bundled coverages that address the full spectrum of aging needs. Insurance subsectors can play a vital role here: retirement and annuity providers to provide income security, health insurers to manage care and medication costs, and supplemental health carriers to bridge gaps such as dental, vision, and critical illness. Moreover, to improve the user experience, these solutions should be accessible through a single online “front door.”
- Investing in digital coaching platforms that provide real-time guidance, predictive analytics, family engagement tools and proactive prompts for estate planning steps including financial planning, caregiving education, wills, powers of attorney and advance care directives. More specifically, these platforms should address:
- Financial matters, including Medicare/Medigap/Medicare Advantage trade-offs, Extra help/low income subsidies & Medicare Savings Programs enrollment, LTC financing basics, housing retrofit funding, and emergency savings.
- Lifestyle matters, including preventive care adherence, home safety and fall prevention, medication management, caregiver readiness and social connection.
- Adopting success metrics that include wellbeing, independence and family resilience, not just portfolio performance.
What you can do now
Put customers front and center with a data-based approach. Customer understanding hinges on investing in, implementing and using technology appropriately. Data-gathering tools that collect and store information in a real-time feedback loop can help you better understand the customer lifecycle and identify coverage gaps. Facilitating touchpoints beyond time of purchase and claims can lead to cross-selling opportunities that meet customer needs with compelling offerings over the long term.
Provide a seamless user experience. Thoughtfully plan and implement your tech to make interactions and transactions practical and easy for customers, employees and agents. If your website is hard to navigate, claims portal an impediment to resolution, self-service tools (e.g., chatbots) unhelpful, coverage terms confusing, and view of the customer incomplete, you’ll alienate customers, policyholders and your own workforce. Note that this extends beyond your native environment: your tech also should integrate effectively with partners and ecosystems.
Confirm that your business and operating models are fit for purpose. While technology and partnerships enable new opportunities, your business and operating models will ultimately determine your success. You shouldn’t expect to be competitive and grow if you're a seller of interchangeable commodities that competes primarily on price.
Advice and distribution in the Age of AI
With the advent of direct channels and modern core systems, the end was supposedly in sight for brokers and agents. Customer self-service on interactive websites containing detailed coverage menus, supported by an integrated back end, was going to simplify distribution and reduce acquisition and retention costs.
However, things haven’t worked out that way —at least not on the scale carriers envisioned. While direct-to-consumer channels account for an increasing percentage of low-margin business like basic auto and property coverage, complex, higher-value offerings still require significant advisor involvement. Carriers need someone they trust to represent them and thoughtfully arrange risk coverage on their behalf, and customers need someone who can explain and help them select appropriate, often complex policy options.
Rather than replacing advisors, digital tools’ real value instead is in supporting and complementing them. On the operational end, this has included simplifying tedious workflows, enabling brokers and agents to be more productive. In terms of risk management and business performance, digital analytics offers deep insights on risk exposures, enabling advisors to make more personalized recommendations and insurers to better manage portfolio performance.
Enter AI
With the rise of GenAI and agentic AI, we’re hearing many of the same claims we did in the early days of digitization, notably that AI will do away with advisors. But at least for the time being, this seems unlikely. While AI is indeed changing ways of working— notably by automating and therefore simplifying (if not outright replacing) many operational processes and applications— brokers and agents continue to play a vital role in placing coverage.
As with digital channels and apps, we see AI helping and augmenting advisors, not replacing them. For simple coverages, AI-informed customer self-support on direct channels has immediate potential. But assessing and managing larger risks requires an understanding of nuance and a level of assurance that people still most effectively provide. Think of it this way: People can easily attempt to diagnose health issues using (often AI-enhanced) online resources. But they still typically need a medical professional to make a formal diagnosis and perform any needed procedures.
Overcoming deployment challenges
Before AI solutions can help insurance advisors, they should be fit for purpose. Even at tech-savvy carriers and brokers, we've seen challenges with GenAI and agentic AI deployment. Insufficiently transparent model development and decision rules can make advisors and other employees uncertain about how to use AI solutions in day-to-day operations. Moreover, building in-house solutions often requires the same development and maintenance costs as traditional ones. As a result, we're seeing many IT functions look for innovative ways to get value from these tech investments, including:
Establishing in-house teams and labs to prioritize and manage enterprise-wide experimentation. This includes IT teams being “solution designers” that work collaboratively with the business to implement scalable solutions.
Embedding dynamic business rules by migrating existing robotic process automation (RPA) to agentic AI.
Prioritizing development and/or acquisition of new skills. This isn’t just a daily operational issue but a way for advisors to maintain professional autonomy.
Moving from a build to sourcing strategy, for example, by acquiring insurtech companies with desired capabilities.
In addition to deployment challenges, AI also presents reputational, compliance, and financial risks. The data that underpin LLMs is not always accurate or dependable, meaning AI outputs can be flawed. Accordingly—and as we note in more detail below—effective governance of AI and its outputs is critical. This is particularly true for brokers and agents as they attempt to provide trustworthy advice, thereby maintaining the integrity of carrier reputations and capital.
Responsibly governed AI can meaningfully assist advisors in several key areas by:
Contributing to the accuracy and appropriateness of product recommendations, helping to align offerings with client needs and regulatory standards.
Identifying the next logical product or follow-up recommendations, facilitating advisor suggestions that are fit for purpose and appropriate to individual circumstances.
Helping brokers, agents and the rest of the organization maintain regulatory compliance and avoid potential regulatory actions and lawsuits.
What you can do now
Employ IT as more than a support function. It should be a strategic advisor that works with the business to identify appropriate use cases and desired solutions. This includes determining what can and can’t be accomplished in-house and potential outside options.
Refine business cases. Because scalability is a good determinant of return on investment, identify and promote solutions that have broad applicability. For example, if 90% of your business is P&C, then developing a suite of life and health solutions probably isn’t the best use of your time and resources.
Protect yourself from reputational, compliance and financial risks. Develop robust AI governance that helps brokers, agents and reps more accurately assess risk and make coverage recommendations according to applicable regulatory and professional standards. This isn’t just a way to stay out of trouble and preserve capital: A reputation for integrity can help you win and keep market share.
Responsible AI governance and innovation: from deployment to discipline
As insurers increasingly embed and rely on AI in core functions, including underwriting, pricing and claims management, they face scrutiny from regulators, customers and the public about how they’re using the technology. This makes Responsible AI governance an urgent priority, and carriers need to specifically address and mitigate operational, bias and regulatory risk.
Regulators are active
The NAIC has drafted a model bulletin on the use of AI systems, which 24 states have adopted to date. Moreover, a growing number of states, notably Colorado and New York, have passed or are drafting their own legislation to target how insurers use AI. The NAIC has also solicited comments on a model law that regulators could use to assess insurers’ AI governance programs and carriers could use to govern their use of AI. While these guidelines’ exact content and release dates are still pending, insurers should prepare for active regulatory guidance and oversight.
Insurers are off to a good start — but there’s more to do
Many insurers have taken steps to establish foundational AI governance practices. These include forming governance bodies and committees, defining accountability for AI governance, conducting readiness assessments or internal audits of their programs against state regulations, and developing comprehensive inventories of AI systems and predictive models. Many carriers are establishing intake and risk-tiering processes and beginning to document policies and standards across the AI model lifecycle.
Although these initial steps are important, they reflect an industry that’s focusing primarily on creating oversight structures and responding to evolving regulations, rather than fully operationalizing Responsible AI programs. They’re often insufficient to meet the complexity of today’s AI risks because they tend to focus on compliance checklists rather than holistic integration of Responsible AI across the business. Many programs are still siloed, lack consistent documentation, and do not have mechanisms to rigorously test models for fairness and bias. As a result, insurers risk being reactive in responding to regulatory mandates after the fact, rather than proactive in shaping trustworthy and resilient AI practices.
Insurers have tended to take a reactive approach to AI governance, rather than operationalizing Responsible AI programs.
The path forward
You’ll need to strengthen fundamentals— building complete and accurate AI inventories—and embed consistent risk-tiering practices. Getting these basics right is essential for creating a governance, risk management and accountability foundation that will help you effectively scale Responsible AI programs. This includes integrating AI governance into your enterprise risk management framework, establishing end-to-end life cycle policies and developing training and awareness programs throughout your workforce. Continuous monitoring and testing for fairness, transparency and accountability should become standard practice. To embed these foundational elements and elevate AI governance from a defensive posture to a strategic enabler of innovation and trust, you should explore automated monitoring solutions, AI/ML impact assessments and AI repositories that centralize governance and data practices.
By proactively investing in Responsible AI programs, you can better balance innovation with compliance, avoiding reputational risks while differentiating yourself in the market. Moreover, robust governance can help you innovate responsibly at scale, embedding accountability and transparency into your operating model, enhancing customer trust, reducing regulatory friction and accelerating the adoption of AI-driven capabilities. By treating Responsible AI as a core competency rather than a regulatory obligation, you can gain sustainable advantages in efficiency, customer engagement and risk resilience.
What you can do now
Strengthen governance structures. Move beyond governance committees to embed AI accountability into enterprise-wide risk management frameworks.
Operationalize AI lifecycle policies. Develop and enforce consistent documentation, testing and monitoring standards across all AI models.
Prioritize fairness and bias testing. Implement regular, rigorous testing of AI systems to detect and mitigate discriminatory outcomes.
Build workforce readiness. Provide training and change management programs to enhance awareness and capabilities across functions.
Apply technology for oversight. Explore how automated monitoring, AI impact assessments and centralized AI data repositories can improve scalability and compliance.
IT: From support function to strategic enabler
As insurers continue to digitally transform their organizations, business leaders, customers and users are making commensurately growing demands on IT. Coupled with a relentless pace of technological change, these expectations are causing IT leaders and their functions to plan more strategically, proactively engage users and other stakeholders, make frequent updates and improvements and constantly innovate.
Accelerating innovation
Insurers have historically relied on singular administration platforms to deliver essential capabilities. However, recent technology advancements are changing carrier priorities from primarily upgrading tech stacks to flexibly scaling tech capabilities that help the business grow. And while core systems still serve as the backbone of IT and business operations, complementary technologies are significantly enhancing them.
That said, we’ve seen no single operating model or strategy that guarantees success. Rather than following any particular methodology, IT functions that enhance agility, flexibility, and the speed at which they deliver capabilities are the most able to provide meaningful value to the business and stakeholders. And industry leaders—notably ones with an API-first mindset that strives for seamless connectivity and real-time data exchange—recognize this.
As we alluded to earlier, we’ve seen business and IT resources at forward-looking carriers collaborate on agile teams to make strategy an on-the-ground reality. On an operational level, this has included cross-functional teams entirely reimagining business processes, often with AI applications as a key enabler. Notable examples of these efforts have included full automation of new business applications at annuities providers and facilitation at other carriers of event-based claims submissions that automatically trigger benefits.
These initiatives have demonstrated that, rather than simply automate current ways of working, there are practical opportunities to fully reimagine end-to-end processes. These moves have saved administrative time and expense at the operational level, while providing claimants with timely, helpful service that inspires brand loyalty.
There are increasing expectations of IT to be an enabler of business strategy, not just a maintenance function.
What you can do now
Invest in product management. The most innovative and customer-focused organizations have mature product management functions that focus on continuous feedback and timely delivery. To compete effectively, IT should closely collaborate with the business to establish agile product management teams that prioritize and iteratively build timely and practical digital capabilities.
Break down tech silos. Many insurance company labs remain siloed experimentation zones. Success depends on bringing prototypes into production, scaling across business lines and embedding outcomes in day-to-day operations.
Reframe IT governance by updating KPI methodology. Traditional KPIs like uptime and cost control don’t correspond to IT’s new mandate. Carriers should measure IT’s performance by business outcomes: customer satisfaction, cycle time reduction, revenue enablement and risk differentiation. Accordingly, position IT as a co-owner of related initiatives, embedding accountability for innovation, resilience and customer impact into enterprise governance frameworks.
Private credit: from strategic vision to operational reality
As investment-led insurance strategies have become more prevalent, private credit has become an important part of insurers’ balance sheets, growing from 10% to 14% of life insurer general account assets over the past decade, according to the US Federal Reserve. This move gathered momentum in the low-interest rate environment following the financial crisis, but even with today’s higher-rates, private credit remains critical for generating attractive risk-adjusted returns and supporting long-term liability management.
For insurers, the challenge is not only gaining access to and increasing allocations at a reasonable cost but also doing so effectively. Private credit creates two primary layers of complexity: managing operational strain in areas with limited data accessibility and integrating these investments into broader reporting and capital strategies.
This can be difficult. Investments and liabilities teams—traditionally siloed functions—need to work side-by-side to enable effective decision-making regarding structuring, asset liability management and infrastructure.
Moreover, segmentation matters. Private credit is not a one-size-fits-all solution and you’ll need to tailor strategy to your business. Liability structures, liquidity needs and capital constraints vary widely across life, P&C and specialty subsectors, and private credit strategies should account for these differences.
Sourcing and managing private credit channels
How you source and manage private credit investments is a pivotal decision, shaped by organizational capabilities, capital constraints, desired speed to market and risk appetite. Insurers typically adopt one or more of the following strategies:
Build in-house capabilities.
Acquire an external asset manager.
Partner with established players.
Be acquired by an external asset manager.
These approaches aren’t mutually exclusive and many insurers revise their model over time based on scale, expertise and market conditions. Each approach comes with trade-offs, requiring careful consideration of strategic alignment, operational complexity, scalability and capital implications.
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| Considerations | Build (in-house) | Buy (acquire manager/assets) | Partner (alliances/outsource) |
| Strategic alignment | High: Full control and full alignment with insurer's objectives and risk appetite, with flexibility to structure capital efficiently. | Moderate to high: Alignment depends on manager’s strategy and post-acquisition integration. Capital efficiency is influenced by the acquired platform’s existing capabilities. | Moderate: Shaped by mandate terms;, offering agility but less operational control;, ultimately acts as an asset manager with insurance companies mandating and owning strategy. |
| Operational complexity | Moderate to high (front-loaded): Significant setup costs, including resources and system implementation, but can streamline with full control. | High: Control gained through M&A, but complexity driven by integration and platform fit, including systems and culture. | Moderate: Operational demands shift to manager but requires oversight and governance of and coordination with manager. |
| Speed | Moderate: Scales with investment, but growth is slower and depends on internal team capacity and expertise in underlying asset class. | High: Immediate scale through acquired platform, but longer-term scalability depends on integration strategy and alignment beyond manager’s existing strategies. | High: Enables scalable deployment across managers and strategies without platform constraints. |
Cost (capital deployment)
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Moderate: Requires balance sheet commitment and ongoing platform costs (e.g., technology, talent retention). | High: Requires significant upfront acquisition capital and ongoing integration costs (e.g., retention, technology, platform alignment). | High: RBC efficiency depends on manager’s structure, which the insurer can evaluate but typically not modify.
Low: Minimal capital outlay, though cost structure depends on investment mandates and manager fee arrangements. |
Turning operational risks into advantages
Whichever sourcing model you choose, realizing private credit’s advantages depends on your ability to manage the complexity that comes with them. Without the right infrastructure to support these assets, the operational cost and risk of owning them can outweigh the benefits.
Unlike public fixed income, private credit is frequently negotiated on a bespoke basis and often requires support across multiple systems, legal entities and regulatory jurisdictions. Capturing bespoke legal terms upon asset onboarding, servicing non-standard cashflows and complying with reporting requirements across regimes are all integral to owning these assets at scale.
Fragmented technology infrastructure often makes this difficult. Asset and liability cash flow modeling, investment analytics, and portfolio construction tools often sit across multiple vendor platforms, functional departments and third-party asset managers, resulting in disparate data across systems, custodians and servicers. These disconnects can make it difficult to form a unified view of the balance sheet and increase the risk that portfolios will fall short of their intended role in supporting liabilities.
Accordingly, you'll need to manage the full investment lifecycle without compromising accuracy, efficiency or reporting integrity. Developing the ability to manage this lifecycle effectively requires sustained investment in operations, data governance and systems integration. This should be a core enabler of portfolio performance, risk oversight, and regulatory compliance, not a back-office afterthought. And in fact, highlighting the strain on traditional operating models that weren’t designed to manage these instruments’ demands at scale, many insurers are expanding headcount in investment accounting and operations teams to keep pace with the data demands and complexity of private credit.
Ineffective operations, data governance and systems integration can compromise the return premiums that drew you to private credit in the first place.
What you can do now
A successful approach to private credit depends on:
Strategic alignment across finance, actuarial, investments and reporting.
Having adequate data to inform and processes to implement strategic decisions that drive value.
Being able to structure from a GAAP, stat and tax perspective to effectively realize the benefits you want.
Your back and middle office, including data management, asset maintenance and valuation, being fit for purpose.
If you think your current resources may be inadequate to meet new demands in any of these areas, then determine before you enter the space where and how much you’ll need to invest.
Related content
- Insurers and private credit: Making a strategic priority a long-term advantage
- How Insurance companies are investing in Private Credit: strategies, structures, and tax considerations for maximizing returns
- Private credit: The rewiring of credit in capital markets
- US Deals 2026 outlook
PwC’s Rich de Haan, Melanie Henderson, Ed Hirsh, Chris Joline, Susmitha Kakumani, Josh Schwartz, and Alex Webb also contributed to this report.
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