AI-Powered Asset Management: From Experimentation to Essential Infrastructure

Artificial Intelligence is rapidly becoming a core infrastructure. As regulatory complexity increases, market data costs escalate, and client expectations rise, traditional operating models are under strain. Firms that continue to rely on manual, fragmented processes risk higher costs, slower decision-making, and growing operational and compliance exposure. 

AI offers a different path forward. When applied pragmatically and responsibly, it enables asset managers to streamline operations, enhance insights, and build more resilient, scalable organizations. The shift underway is not about replacing human expertise, but about augmenting it, freeing teams to focus on higher-value activities while AI handles volume, variability, and complexity. 

The asset management industry is facing a convergence of pressures: 

• Regulatory change is accelerating, while global requirements growing in volume, complexity, and interdependency
• Market data spend continues to rise, driven by opaque pricing models, redundant subscriptions, and limited usage transparency
• Operational risk remains high in areas reliant on manual processes and siloed data
• Clients expect faster responses, better transparency, and greater consistency 

AI directly addresses these challenges by transforming how information is captured, analyzed, and acted upon across the organization. Leading firms are adopting AI as a foundational capability embedded into day-to-day workflows. 

AI is already delivering tangible value across the following critical operational domains:  

1. Regulatory Monitoring, Risk, and Controls  

AI enables continuous regulatory change monitoring, intelligent impact analysis, and automated mapping to internal policies and controls. This reduces manual effort, improves traceability, and supports a shift from periodic reviews to near real-time risk visibility. 

2. Market Data as a Service (MDaaS) 

By connecting contracts, invoices, usage data, and benchmarks, AI brings transparency to one of the industry’s largest cost categories. Asset managers can identify inefficiencies, strengthen vendor negotiations, and turn market data from a cost center into a managed strategic asset. 

3. Corporate Actions Processing  

Agentic and generative AI significantly reduce operational risk in voluntary corporate actions by automating announcement capture, eligibility verification, election monitoring, and client communications. This improves accuracy while accelerating turnaround times. 

4. Smarter Data Insights 

AI-driven data governance, quality controls, and secure connectivity frameworks allow organizations to unlock insights faster and more reliably. Intuitive interfaces empower non-technical users while upskilling IT teams to focus on higher-impact work. 

5. RFP and DDQ Management  

AI streamlines proposal and due diligence workflows by automating content retrieval, drafting responses, enforcing consistency, and embedding compliance controls. This reduces cycle times while improving response quality. 

The real value of AI is realized when it is embedded into operating models, not deployed as isolated tools. Successful asset managers focus on three critical enablers:  

• Strong data foundations, including governance, quality, and secure access
• Integrated workflows, where AI supports end-to-end processes rather than individual tasks
• People enablement, ensuring teams trust, adopt, and effectively work alongside AI solutions 

When these elements come together, AI moves beyond efficiency gains to become a source of sustained competitive advantage. 

AI in asset management has crossed a threshold. The question is no longer if firms should adopt AI, but how to do so responsibly, at scale, and with measurable impact. 

Sia’s latest whitepaper, AI-Powered Asset Management: Unlocking Efficiency, Insights, and Competitive Advantage, explores these use cases in depth with practical architectures, governance considerations, and real-world applications across regulatory compliance, market data, operations, and client engagement. 

Download our whitepaper to learn how leading asset managers are embedding AI into their operating models and positioning themselves for long-term success.