In today’s socio-economic environment, disability insurance has become increasingly vital.
This can be attributed to escalating healthcare costs, unstable job markets, and the growing incidence of chronic illness and mental health conditions. Let us look at some numbers on disability.
Loss of income due to disability coupled with soaring healthcare costs can lead to financial difficulties, and result in bankruptcy, debt, or loss of assets such as home or retirement savings. In such scenarios, timely access to disability insurance becomes critical. The above numbers translate into a significantly high number of disability claims—in our experience, an insurer may have to manage up to 200,000 or more claims on average every year—putting immense pressure on insurers to expedite the process.
However, the disability claims process is complex and lengthy, often resulting in delays in benefits reaching the claimants and increased operational costs for insurers. In our experience, the adjudication of a long-term disability claim can vary from 15 to 20 weeks while short-term disability benefits may take about five to 10 weeks. Social security disability insurance (SSDI) claims are even more time-consuming, where an initial decision can take six to eight months.3
These delays highlight the need for more efficient claims handling to prevent people from slipping into financial hardships and associated repercussions. To achieve this, insurers will need to leverage a combination of digital and composite artificial intelligence (AI) technologies to automate the claims process, optimizing costs and efficiency.
The disability claims process is fraught with difficulties such as administrative hurdles, complex and confusing policies, and the need for multiple documents and medical evidence.
All this impedes timely benefit delivery, posing challenges to claimants who are dependent on it for their livelihood.
Delay in collecting and processing information
Voluminous information from multiple entities (see Figure 1). Several internal staff review and utilize this information throughout the claims value chain. Gathering and processing this information can be time-consuming, delaying the flow of benefits to claimants, adversely affecting customer experience and increasing overall administrative costs for insurers and employers.
Lack of awareness
Claimants and employers are frequently unaware about applicable policy benefits and provisions. This often results in incomplete claim forms, missing information, and documentation leading to repeated interactions between claimants and insurers, which ultimately slows down the process.
Appeals and denials
Subjective clinical evaluations, in cases of co-morbidities and behavioral health, often result in differences between the analysis of the insurer’s clinical consultant and the claimant’s provider. Such subjectivities lead to lengthy investigations and may result in denials, appeals, and disputes adding time to the process.
Manual interventions
Pre-disability earnings and benefits are calculated manually, which is labor-intensive and error prone. Varying employer terms, earnings definitions, offsets, and tax implications further complicate the process. Similarly, unstructured data such as scanned medical documents require manual review and processing, adding time to the process. Additionally, long-term disability claims require monitoring of benefit periods and return-to-work timelines, increasing administrative costs.
Legacy platforms
Insurers operate with traditional legacy systems, characterized by limited automation and increased manual intervention. Claimants frequently seek updates on their claim status, adding to the workload of claims teams. Employers also require regular updates on their employees’ recovery and return-to-work status, along with detailed management reports, which can be difficult to generate with legacy systems.
Fraudulent claims
Fraud is another aspect that plagues the disability insurance process with claimants continuing to receive benefits after recovery or submitting forged documents. Litigation and appeals add another layer of complexity, consuming resources and potentially harming the insurer’s reputation due to prolonged and costly legal proceedings.
Regulatory landscape
Insurers have to comply with multiple federal and state laws such as the Americans with Disabilities Act (ADA), Family Medical Leave Act (FMLA), and Workers’ Compensation while processing disability claims. The presence of concurrent claims for the same condition, for example, short-term disability and FMLA for pregnancy, adds further complexity, making the entire system intricate and demanding to manage.
Insurers must deploy a combination of composite AI and digital technologies at every stage of the customer journey.
By adopting these tools, insurers can strategically design a future-ready, efficient, and sustainable disability claims management model that balances innovation with operational effectiveness and governance.
Deploying AI and digital tools through the end-to-end claims journey (see Figure 2) can enable insurers to deliver a seamless experience to claimants as well as employees. By employing AI, insurers can significantly reduce the complexity and average handle times in disability claims processing.
Claims intake and initial review
AI can be used to guide claimants through the journey, offering clarifications wherever claimants and/or their employers are unaware of policy provisions. AI can automatically sort and verify incoming documents, reduce manual effort, and accelerate the overall claims adjudication process. The back-end process starting from data extraction to the generation of a unified claim file and subsequent ingestion into the claims administration platform can be automated using AI.
Similarly, AI can help perform initial checks to assess eligibility while a human can review and approve claims and handle exceptions. Initial review also involves checking if the claim complies with the provisions of regulations such as FMLA, ADA, and other state-specific regulations, which becomes easy with AI. An AI-enabled system can proactively follow up on missing information and documentation, mitigating delays in obtaining medical and employer records. Insurers can deploy application programming interfaces (APIs) to connect with external medical providers and ecosystems to further reduce the lead times in information gathering. AI can be used to distill complex medical records into concise, clinically relevant summaries aligned with disability criteria
Clinical reviews and claims decisions
AI can aid clinical analysis by extracting data such as impairments and functional limitations and aligning them directly with the policy’s definition of disability and relevant provisions. Adjudicators can use AI to accurately interpret policy provisions and ensure that medical facts are accurately matched to policy terms. Based on the likelihood of approval, expected claim duration, and potential for appeal, predictive models ensure that complex cases are routed to the most experienced adjusters. AI models can be used to arrive at disability duration benchmarks derived from historical claims and medical literature, supporting more consistent and transparent adjudication outcomes.
AI can help insurers in making customer communications simple, clear, compassionate, and personalized, whether conveying approvals, denials, or responding to requests for additional information. AI can be leveraged to offer claimants real-time support, enabling them to ask questions, check claim status, and understand next steps.
Benefits administration
Claimants depend on disability insurance benefits during periods of vulnerability, underscoring the importance of accurate and timely disbursement. AI can interpret policy terms including earnings definition in natural language and integrate with earnings history to calculate precise payouts. Additionally, AI can be deployed to automatically initiate disbursements once claim approvals and eligibility criteria are met. These capabilities not only improve claimant satisfaction but also reduce administrative overhead and the risks of manual errors.
Ongoing claims management
AI can be used to offer personalized encouragement, educational resources, and milestone-tracking to guide claimants through their recovery and facilitate quick return to work. Automated digital check-ins prompt claimants to report progress or changes in condition, ensuring timely updates and reducing follow-ups. Behavioral analytics can detect patterns that indicate potential fraud or readiness to return to work, using insights from claim history and external data.
Employing AI can aid return-to-work planning by predicting the likelihood and timelines of full or partial reintegration into the workforce, benefiting both claimants and employers. These insights help insurers effectively manage loss reserves by identifying cases with high settlement potential. For claimants unlikely to return to work, AI can be used to offer tailored settlement options, improving outcomes for all parties. Additionally, advanced analytics models can help assess the likelihood of legal disputes, enabling proactive case management and resource allocation.
Insurers and employers must embrace wellness as a strategic priority, and here too, AI can help. AI and data-driven tools can be deployed for proactive health management and to prevent disability claims. For example, interactive health apps that monitor both physical and mental wellness can help identify early signs of issues that need attention. Designing wellness programs to promote healthier lifestyles will ultimately build a healthy and resilient workforce, reducing disability claim incidence.
A leading insurer based in the US wanted to transform its medical review and summarization process within the disability claims function.
The insurer was facing several challenges such as the use of manual processes for review of claims and medical documents as well as preparation of clinical summaries, resulting in delays and higher costs. The firm implemented a GenAI-powered solution to automate the process and realized some key benefits:
For insurers, the rising volume of disability claims has made their management extremely tough.
Outdated systems lack the capabilities to process mountains of financial and medical documents quickly and efficiently. This results in long delays, leading to tremendous frustration among claimants already in distress. In the intensely competitive but commoditized insurance space, experience is a critical differentiator, and poor customer outcomes and experience can have significant negative consequences for insurers. And here’s where the powerful combination of composite AI and digital technologies can change the game for all the stakeholders—insurers, claimants, and employers.
AI is the best way forward for insurers—and the time for action is now. In the rapidly evolving insurance landscape, firms that adopt AI will be in a stronger position to optimize costs and efficiencies, meet changing customer expectations, and achieve superior business outcomes. The journey from conceptualization to successful execution, however, is likely to be complex and demanding. To transform the AI vision into true business value, insurers must consider collaborating with a strategic partner equipped with the right domain and technology expertise after a well-rounded market analysis.
1Disability Impacts All of Us Infographic, U.S. Centers for Disease Control and Prevention, April 2025, Retrieved August 2025, https://www.cdc.gov/disability-and-health/articles-documents/disability-impacts-all-of-us-infographic.html
2Persons with a disability: Labor force characteristics – 2024, Bureau of Labor Statistics, U.S. Department of Labor, February 2025, Retrieved August 2025, https://www.bls.gov/news.release/pdf/disabl.pdf
3How long does it take to get a decision after I apply for disability benefits, United States Social Security Administration, March 2024, Retrieved August 2025, https://www.ssa.gov/faqs/en/questions/KA-01801.html