AI + Digital Assets: The Next Operational Frontier for Financial Markets

Across the capital markets, 2026 is shaping up to be a defining year for the transformation of operations in the financial industry. Regulatory-driven change implementations like US Treasury Clearing and the march to global T+1 settlement draw closer. Market innovations, such as extending US Equity trading hours to a 24/5 model, are gaining traction. Artificial intelligence is moving from experimentation to more widespread adoption, while digital assets are gaining regulatory clarity and market momentum. This convergence is no longer theoretical – it is reshaping the core of market operations, from post-trade workflows to real-time payments to resiliency frameworks.

At this year’s SIFMA Operations Conference & Exhibition, we will bring together the leaders who are building that future.

The conversations come at an inflection point for our industry. In April 2025, SIFMA published “The Evolving Role of the Operations Professional,” a blog highlighting four key priorities for operations teams: AI-driven innovation, technology infrastructure modernization, regulatory change management, and operational resilience. Since then, firms have moved beyond early pilots toward scaled deployment and real-world execution.

Today, the question is no longer whether these technologies will transform financial operations. Rather, it is how quickly firms can operationalize and embed them.

AI Is Becoming Embedded Infrastructure, Not Just a Tool

The industry has entered a phase where AI is no longer just augmenting workflows — it is becoming embedded in the infrastructure that powers them. In payments and commerce systems, AI is increasingly embedded directly into routing, analytics, and real-time decision making. For operations teams, the evolution of AI from pilot program to enterprise-wide deployment is particularly significant.

A key development driving this shift is the rise of agentic AI, which are systems capable of managing multi-step processes rather than performing a single automated task. Instead of supporting one component of an operational workflow, AI agents can now orchestrate entire processes across data sources, systems, and decision points.

This evolution is creating both opportunity and pressure for firms. Operations leaders are increasingly tasked with deploying AI at scale and delivering measurable impact, while ensuring that control frameworks keep pace with the technology. Monitoring and controlling these systems is becoming a critical discipline in the operations space. It is essential for firms to understand how automated agents behave and to maintain accountability and oversight.

After years of foundational investment, firms are now realizing and demanding tangible ROI from scaled agentic AI deployments. Industry reports over the past year have highlighted 20–40% productivity gains in some credit workflows and 30% faster turnaround times, leading to operational cost savings and employee productivity amplification. For example, agentic systems are orchestrating end-to-end processes such as post-trade reconciliation—automatically matching trades across fragmented systems, investigating discrepancies, and escalating only true exceptions—while compliance agents handle multi-step KYC reviews, fraud investigations, and regulatory reporting with minimal human intervention.

These capabilities shift operations from reactive fixes to proactive, autonomous workflows. As firms embed these agents as core infrastructure, the focus turns to disciplined measurement: tracking not just adoption but actual efficiency lifts, anomaly detection rates, and risk reduction to ensure sustainable value.

The 10x ops professional represents the next evolution in financial operations: a highly skilled individual amplified by a team of agentic AI co-workers to deliver exponential impact. In the 2026 “10x bank” vision—highlighted in Accenture’s top banking trends and echoed across industry reports—traditional headcount constraints dissolve as one operations leader orchestrates autonomous AI agents to handle complex, multi-step workflows end-to-end. What once required entire teams (reconciliations, compliance checks, post-trade matching, KYC reviews, anomaly detection, and regulatory reporting) now runs at scale with minimal intervention.

Siloed and Disparate Data: A Barrier and a Catalyst for AI Transformation

As firms scale AI, another reality has emerged: legacy infrastructure and older technology remain one of the largest barriers to transformation.

While legacy systems remain a persistent barrier, fragmented and poor-quality data has emerged as the single biggest throttle on agentic AI scaling in 2026. Industry analyses consistently identify brittle data foundations—siloed sources, inconsistent quality, and lack of real-time governance—as the root cause limiting effectiveness beyond pilots. Without clean, AI-ready data estates, up to 40% of agentic initiatives risk underperforming or failing to deliver promised returns.

Forward-looking operations leaders are addressing this head-on by prioritizing enterprise-wide data modernization first: rebuilding governed platforms, unifying master data, and establishing real-time pipelines. This foundational work, often accelerated by AI-assisted coding for new architectures, enables agents to operate reliably across systems, turning legacy constraints into catalysts for transformation and unlocking the full efficiency potential of embedded AI. The ability to successfully utilize new AI capabilities with modernization of existing infrastructure will shape how quickly firms can realize the promised efficiency and cost benefits.

Digital Assets Are Moving Into the Regulatory Mainstream

While AI is transforming operational workflows, digital assets are simultaneously reshaping the infrastructure of financial markets.

Digital asset policy is evolving quickly, with regulators providing clearer frameworks that enable broader engagement by banks, broker-dealers, and custodians. Stablecoins and tokenized assets, once considered experimental, are increasingly viewed as building blocks for next-generation financial infrastructure.

For operations teams, these developments introduce a potential new operational paradigm. Tokenized assets and blockchain-based settlement systems could support near-instantaneous clearing, programmable collateral, and 24/7 markets, capabilities that will increasingly intersect with existing post-trade infrastructure.

This evolution requires firms to rethink operational and technological support models designed around batch processing and traditional market hours. As market hours extend and digital assets mature, operations teams will play a critical role in integrating these systems with existing financial market infrastructure while maintaining safety, transparency, and efficiency.

Regulation and Governance in an AI-Driven Market

As innovation accelerates, regulators are increasingly focused on ensuring that new technologies are deployed responsibly.

As agentic AI scales, governance has evolved into a specialized discipline—often termed “AgentOps”—that treats autonomous agents as digital identities requiring real-time observability, telemetry, supervisor hierarchies, and robust controls. Regulators and firms alike emphasize explainability, auditability, and accountability to manage new risks unintended behaviors in multi-agent orchestrations. Banks are implementing shadow-mode testing and dynamic oversight to maintain compliance while accelerating deployment.

This balanced approach is critical: mature governance frameworks enable leaders to pull ahead, with reports showing they are significantly more likely to achieve scaled ROI and avoid operational pitfalls. For operations teams, bridging innovation and regulation means embedding these controls from the start—ensuring agentic systems enhance resilience rather than introduce new vulnerabilities in an increasingly automated environment

The intersection of AI governance and digital asset regulation will be a key theme in industry discussions, particularly as firms navigate questions around accountability, risk management, and operational oversight.

Operational Resilience in an Increasingly Automated Environment

Operational resilience has long been a core priority for financial institutions, but the environment in which firms operate continues to evolve. Since 2024, the shift from a T+2 settlement cycle to T+1 and now the push for 24/7 equity trading have both removed the natural circuit breakers in the day that were previously enabled firms to recover from outages and issues. The reduction in recovery time plus market volatility, cyber threats, and geopolitical uncertainty all require firms to maintain robust operational frameworks. At the same time, the increasing use of AI introduces new considerations: automated systems can significantly enhance monitoring, fraud detection, and surveillance, but they also introduce new operational dependencies.

Operations teams are therefore focused on building resilient systems capable of operating in volatile environments, ensuring both traditional infrastructure and emerging AI-driven processes can withstand disruption.

In many cases, AI itself is becoming a powerful tool for strengthening resilience. It helps firms detect anomalies faster, anticipate operational risks, and respond more dynamically to market events.

Talent and the Future of the Operations Workforce

The transformation of financial operations is not just technological. It is also human.

As AI becomes embedded across operational workflows, the role of the operations professional continues to evolve. Rather than replacing human expertise, AI increasingly acts as an amplifier of human capability, allowing smaller teams to oversee more complex systems and make higher-value decisions. Managing processes will now be over teams of agents changing how human talent is onboarded, trained and mentored through to management levels within organizations.

This shift is also prompting firms to rethink traditional workforce models. As automation expands, some functions historically outsourced or handled through large operational teams may be redesigned or brought back in-house, supported by AI-enabled workflows and more specialized talent.

For the next generation of operations leaders, the skillset will increasingly blend technology fluency, risk management expertise, and operational strategy.

Join Us at SIFMA Ops 2026

At SIFMA’s Operations Conference & Exhibition taking place May 11-14, 2026, we will explore these themes in depth, bringing together operations leaders, technologists, regulators, and policymakers to discuss how the industry can modernize market infrastructure responsibly and effectively.

Sessions will examine topics including:

• AI and Emerging Technology – From Experimentation to Execution
• The Future of Compliance and Operations: Harnessing Advanced Tech, New Assets, New Operating Models
• Tokenization and Digital Assets – The Next Wave of Financial Services Transformation
• AI Governance – Risk, Controls, and Compliance
• Operationalizing Tokenized Assets
• Reimagining Post-Trade Operations
• T+1 Goes Global – Operational Implications
• Cyber Resilience in a Third-Party Ecosystem

The SIFMA Operations Conference remains the premier forum where the industry’s operations community tackles its most pressing challenges and shapes the future of financial market infrastructure. We look forward to continuing the conversation in 2026 and helping define the next chapter of operational excellence in global markets.