At TSAM London 2026, a clear shift emerged across the asset management industry: the conversation is moving beyond AI potential and toward real-world execution.
In a post-event interview, Simon Bray (Head of EMEA), Sunil Odedra (Chief Technology Officer), and Andrew Eames (Head of Pre-sales), shared their key insights from the event, covering cyber resilience, AI adoption, and the future of investor communications.
Cyber resilience in Asset Management: from technology to organisation
One of the strongest themes from TSAM London was that cyber resilience is no longer just a technology issue, it is an organisational challenge.
As highlighted by Sunil Odedra, firms are increasingly recognising that responding to cyber threats requires coordination across technology, operations, risk, and communications. While many organisations have frameworks in place, the real challenge lies in execution under pressure.
In practice, this is where many firms fall short: plans exist, but when tested in real scenarios, coordination and communication often break down.
The cyber threat landscape is also evolving rapidly. AI-driven attacks including deepfakes and advanced phishing are making threats harder to detect and respond to. This is forcing firms to shift their focus from prevention alone to resilience, including containment and recovery.
This shift reflects a growing recognition that not every attack can be prevented, making the ability to limit damage and recover quickly just as critical as defence.
AI in Asset Management: Moving from experimentation to execution
AI was a central topic across TSAM London 2026, but the tone of the discussion has changed.
According to Andrew Eames, firms are no longer focused on AI as a concept, they are focused on practical applications. Use cases such as content generation, reporting automation, and personalisation at scale are gaining traction across asset management marketing and operations.
However, widespread adoption is still a work in progress with operational barriers including data quality, accessibility, governance and compliance holding firms back.
Beyond these technical barriers, firms are also grappling with how to embed AI into existing workflows in a structured, scalable way, and build the organisational confidence required to use it effectively.
AI also introduces new challenges around governance and risk. Ensuring accuracy, controlling outputs, and avoiding unintended consequences are becoming just as important as unlocking efficiency gains.
Investor communications and trust: The role of data and process
Another major takeaway from TSAM London 2026 was the importance of trust in investor communications.
Panels hosted by Patrick McKenna, Chief Commercial Officer at Kurtosys, highlighted how trust is built or lost through communication. Inconsistent reporting, unclear disclosures, and fragmented messaging can undermine investor confidence.
While AI and automation offer significant opportunities to improve efficiency, they also expose weaknesses in these foundations. As a result, firms are increasingly focusing on strengthening data governance, improving content accuracy, and ensuring consistency across all client communications.
The event also reinforced that asset management remains a relationship-driven industry, where trust, personal connection, and human judgement still play a central role. Technology is most effective when it supports these relationships, not replaces them.
Closing the gap between expectation and execution
Across cyber resilience, AI adoption, and investor communications, one theme stood out at TSAM London 2026: The technology is already available, but execution remains the key differentiator.
This challenge is compounded by increasing pressure on teams, who must balance more initiatives, channels, and expectations without a corresponding increase in resources. As a result, firms are being forced to prioritise more deliberately, focusing on the initiatives that deliver the greatest impact.
Asset managers that can align their data, workflows, and teams will be best positioned to scale AI effectively, strengthen resilience, and deliver consistent, high-quality client experiences.
As the industry continues to evolve, closing the gap between expectation and execution will define the leaders in asset management.
FAQs
- What is cyber resilience in asset management and why is it important?
Cyber resilience in asset management refers to an organisation’s ability to prepare for, respond to, and recover from cyber threats. It is critical because attacks are becoming more sophisticated, and firms must ensure business continuity, protect investor data, and maintain trust even when breaches occur. - Why is AI adoption slow in asset management?
AI adoption is slowed by challenges such as poor data quality, limited data accessibility, governance concerns, and regulatory compliance requirements. Firms also struggle to integrate AI into existing workflows and ensure outputs are accurate and trustworthy. - How is AI being used in asset management today?
Asset managers are increasingly using AI for content generation, automated reporting, and personalisation at scale. These practical applications are helping improve efficiency, streamline operations, and enhance client communication. - How does data impact investor trust in asset management?
Data plays a central role in investor trust. Inaccurate, inconsistent, or fragmented communications can damage credibility, while strong data governance and clear, consistent reporting help build confidence and strengthen client relationships. - What is the biggest challenge asset managers face with AI and digital transformation?
The biggest challenge is not access to technology, but execution. Firms must align data, workflows, and teams to successfully scale AI, improve resilience, and deliver consistent client experiences.
