Introduction

Pension systems globally manage $55.7 trillion in assets, representing 69% of GDP across major economies. However, a $70 trillion retirement savings gap recorded in 2015 is forecasted to grow to $400 trillion by 2050. Factors such as ageing populations, extended life spans, and declining birth rates place financial strain on systems. Artificial intelligence (AI) emerges as a transformative tool to address inefficiencies, optimise retirement outcomes, and enhance system sustainability.

Overview of the pension value chain

The pension value chain comprises five core stages:

• Membership and payment channels: Simplifying participation and contributions.
• Recordkeeping and account management: Ensuring accurate and transparent data handling.
• Governance and investment strategy: Strengthening trustee decision-making through enhanced analytics.
• Investment management: Improving asset allocation and risk management.
• Payout phase: Tailoring decumulation strategies to ensure post-retirement financial stability.

AI integration is pivotal at each stage, helping resolve structural inefficiencies while promoting adaptability in volatile economic conditions.

Membership and payment channels

AI-driven onboarding systems, chatbots, and robo-advisers simplify enrolment and improve member engagement. Digital payment systems support efficient transactions, boosting participation and accessibility. Between 2014 and 2017, these advancements enabled financial inclusion for 515 million adults. AI personalisation also addresses inequalities by tailoring contributions to members’ unique circumstances and financial literacy levels.

Recordkeeping and account management

AI enhances data accuracy and compliance, consolidating legacy systems to prevent errors and fraud. Platforms like UK pension dashboards, supported by AI, improve data transparency while reducing administrative costs by up to 4%. Synthetic datasets can mitigate biases in member data, ensuring inclusivity and fairness in decision-making.

Governance and investment strategy

AI strengthens governance by providing real-time insights into sponsor strength and investment strategies. Tools like Discover AI assess sponsor covenant health and track external market impacts, enabling trustees to make informed decisions. Machine learning (ML) aids in inflation risk scenario analysis and adapting strategies to demographic shifts, ensuring pension systems remain sustainable in dynamic economic environments.

Investment management

AI-powered analytics support asset allocation, particularly in private markets and sustainable portfolios. Robo-advisers help individual members build diversified investments aligned with their risk preferences. Betterment, for instance, optimises portfolios to reduce tax liabilities, while Ellevest accounts for gender-specific retirement needs. AI also predicts inflation and market risks, enabling trustees to respond proactively to economic shifts.

Payout phase

AI facilitates customised decumulation strategies for Defined Contribution (DC) plans, addressing longevity risks and withdrawal optimisation. Predictive analytics improve trustees’ ability to assess risk and model future scenarios, ensuring income security for retirees. Personalised tools empower members to navigate their post-retirement financial plans confidently.

Addressing pension challenges

AI effectively addresses major challenges:

• Changing demographics: AI enhances trustee decisions by integrating member-specific data and broader demographic trends.
• Inflation risks: Advanced ML tools improve forecasting and stress testing, aiding inflation-proof pension management.
• Rising inequality: Tools like pension dashboards and robo-advisers foster inclusivity by improving access for underserved populations.
• Financial literacy: AI-powered chatbots and personalised communication bridge knowledge gaps, enhancing member understanding.
• Personalisation demands: AI-driven solutions ensure offerings are tailored to member risk profiles and evolving needs.

Conclusions and key principles

Ethical AI integration is essential for sustainable pension systems:

• Balance simplicity with customisation: Solutions must accommodate varying financial literacy levels while avoiding choice overload.
• Foster collaboration: Cross-stakeholder partnerships are necessary to uphold operational standards and ensure sustainable AI adoption.
• Build trust: Transparency, data privacy protections, and measurable benchmarks are critical to maintaining member confidence in AI-enabled systems.

AI offers transformative opportunities to enhance governance, operational efficiency, and retirement outcomes. When implemented responsibly, it can address the most pressing challenges of modern pension systems.