The economic and social landscape of early 2026 is being reshaped by the convergence of biological longevity and the maturation of digital asset infrastructure. For insurance companies and financial advisors, this intersection requires a change the type of advice being given as traditional wealth management strategies are no longer sufficient for a population increasingly expected to live past the age of ninety due to Artificial intelligence (AI)-driven health breakthroughs. AI is increasingly being used for more than just an alternative Google search as it is set to become a core driver of lifespan extension, whilst tokenised real-world assets have provided the investment granularity needed to support longer lives. Furthermore, in the next 23 years it is estimated that there will be $124trillion being passed from one generation to another. Hence, financial advisors need to understand these changes and adapt the advice they give. According to the World Economic Forum, global life expectancy has surged from 67 years in 2000 to 73 in 2019, with projections pushing past 77 by 2050. Yet the triumph is bittersweet. Healthy life expectancy has lagged, leaving people to spend nearly two extra years in poorer health. This gap amplifies healthcare costs, strains families and erodes productivity at precisely the moment societies need sustained economic contribution. Unfortunately, financial planning and savings have not kept up. Historically, expected life spans meant people lived 10 to 15 beyond stopping work; now, being retired for 20-30 years is becoming the norm which can be challenging if without adequate savings. The projected global retirement savings gap, $400 trillion by 2050, signals a structural crisis and many of us are ill-equipped for this new reality.
The most compelling evidence of AI-driven longevity is emerging from the medical field of oncology. Researchers at the Spanish National Cancer Research Centre achieved complete regression of pancreatic ductal adenocarcinoma in pre-clinical models, a disease with a five-year survival rate of approximately 10 per cent. Researchers deployed an AI-optimised triple-combination therapy targeting three independent molecular pathways simultaneously. This design prevents tumour adaptation by blocking resistance mechanisms that typically arise when only one pathway is targeted. In genetically engineered mouse models and patient-derived tumour xenografts, this therapy resulted in complete and durable tumour regression with no resistance observed for over 200 days post-treatment. Notably, this approach reflects a shift towards rational therapy design, where AI models account for biological complexity rather than relying on sequential trial-and-error drug development. Longevity gains are also being accelerated by structural changes in scientific research - platforms such as Opensci and OpenDNA use AI to bypass traditional publishing delays, enabling faster data sharing and collaborative discovery. These systems support bilingual reasoning, allowing language models trained on proteins and RNA to interact and predict molecular structures in seconds. One notable development is the ProRNA3D-single tool, which visualises how viral RNA binds to human proteins. This capability is essential for developing therapies for Alzheimer’s disease and emerging viral threats. Similarly, the RiboNN model developed by the University of Texas at Austin and Sanofi has demonstrated double the accuracy of earlier methods in predicting mRNA protein production across different cell types. This precision enables targeted therapies that increase efficacy while reducing systemic side effects.
Meanwhile, programmable money offers a partial antidote. Smart contracts and stablecoins can automate lifelong income streams, trigger conditional healthcare disbursements, adjust for inflation via oracles and execute inheritance on verified events, delivering precision and immediacy that legacy rails cannot. As digitisation deepens, the need for always-on, condition-driven payments becomes non-negotiable. Without them, longevity risks becoming a fiscal burden rather than a dividend. The question is no longer how long we live, but how intelligently our money can live with us. As lifespans extend, investors increasingly require assets that offer both growth and liquidity. Digital assets have evolved from speculative instruments into foundational components of diversified portfolios. This shift is driven by large-scale tokenisation, which enables digital representation of real-world assets on blockchain networks. The global on-chain, real-world asset market, excluding stablecoins, has reached approximately $24 billion, representing a 380 per cent increase since 2022; growth has been concentrated in private credit, government bonds and real estate. And large institutions have transitioned from pilot programmes to live deployment. BlackRock’s BUIDL fund surpassed $2 billion in assets in 2024, offering institutional-grade yield with T+0 settlement cycles.
Tokenisation market projections by 2030
Sources: theblock, pointsville
Tokenised equities and money market funds are particularly suited to longer retirement horizons, as they remove market open and close gaps that amplify volatility. Blockchain-based equities enable continuous liquidity whilst smart contracts automate dividend distribution and compliance, reducing operational costs by 40 to 60 per cent. However, real estate remains a primary target for tokenisation due to its historical illiquidity - the global real estate market is valued at approximately $280 trillion, yet access has traditionally been limited. Essentially, tokenisation allows properties to be divided into thousands of digital units, enabling fractional ownership from as little as $500. This model allows sellers to unlock trapped capital whilst retaining control and gives investors exposure to property assets with improved liquidity. By 2035, tokenised real estate is projected to reach $4 trillion, transforming the asset class into a global, tradeable market. Moreover, the convergence of health and financial innovation has redefined the role of the financial advisor. Advisors are no longer solely asset selectors but infrastructure orchestrators who manage digital custody, automated legal structures and AI-related risk. At the same time, we are seeing the rise of the “human oracle” and automated estate planning. Advisors increasingly function as human oracles, validating real-world events that trigger blockchain-powered smart contracts. These include incapacity or death confirmations that activate automated inheritance protocols, reducing probate delays and administrative friction. As wealth becomes increasingly tokenised, EY believes digital wallets are expected to replace traditional bank accounts for many high-net-worth individuals by 2027. Advisors are required to integrate these wallets, which hold tokenised assets and private keys, into broader financial structures whilst ensuring security and continuity. This create a major challenge as to how to manage agentic risk, defined as the actions taken by autonomous AI systems without direct human oversight. Platforms such as Moltbook illustrate the scale of this issue attracting over 1million AI driven agents in a few days, capable of accessing email, managing calendars and executing code. Whilst efficiency gains are substantial, liability risks are significant. Improper disclosure or unauthorised actions by an AI agent can expose firms to legal and regulatory consequences, not to mention potentially accessing individuals bank accounts.
Therefore, in order to mitigate these risks, organisations are adopting the Agentic Risk and Capability Framework. This governance system evaluates three risk dimensions: components, design and capabilities. Advisors are increasingly required, as the human in the loop, to disclose agentic risk, detailing safeguards and permission boundaries to clients. Extended lifespans introduce systemic financial risks that can destabilise pension schemes and personal portfolios creating unfunded liability spikes. The longevity gap refers to the strain caused by people living longer than actuarial models predict and research from the IMF and the Centre for Retirement Research indicates that each additional year of life expectancy increases pension liabilities by 3 to 5 per cent. For plans with $2.2 trillion in liabilities, a single-year shock could add up to $110 billion in obligations; a two-year longevity increase could raise obligations by 4 to 8 per cent. However, traditional actuarial models are poorly equipped to account for rapid AI-driven medical advances, increasing the risk of underfunding. Longer retirements increase exposure to cumulative inflation. Over a 40-year retirement, traditional bonds may fail to preserve purchasing power, necessitating a shift towards assets capable of generating real returns over extended horizons. Whilst risks are substantial, longer healthy lives also generate new economic opportunities. Demand for reliable income over extended retirements is driving innovation in longevity bonds and deferred annuities. Advanced mortality models such as the linear-rational Wishart model allow insurers to price long-duration products more accurately, so improving sustainability. High-yield tokenised assets including private credit and institutional-grade Treasuries offer inflation-beating returns with continuous liquidity. Hence, as wealth increasingly moves on-chain, these assets are becoming central to longevity-focused portfolios.
The convergence of AI-driven health innovation and digital asset infrastructure has created a defining moment for wealth strategy in 2026. Boards must recalibrate pension assumptions and embrace tokenised transparency. Financial advisors are evolving into infrastructure orchestrators, managing digital custody and “human oracles” validating blockchain-triggered estate protocols. Yet agentic risk looms: autonomous AI accessing bank accounts demands new governance frameworks. The existential question is not how long we live but whether programmable money can intelligently adapt, or whether extended lifespans become fiscal catastrophes for unprepared generations inheriting $124 trillion amid structural underfunding. Success will depend on balancing AI automation with human fiduciary judgement in an era where both life and wealth last longer than ever before.
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This article first appeared in Digital Bytes (24th of February, 2026), a weekly newsletter by Jonny Fry of Team Blockchain.