Accenture Capital Markets Blog    

Generative AI (gen AI) is predicted to impact over two-thirds of all functions across the capital markets industry1, suggesting that the technology has the potential to significantly transform all its segments—including asset management.

Historically, asset management firms have commonly not been at the forefront of technology driven change compared to other industries given, e.g., the regulation-heavy environment they are operating in. But we feel this time the situation is different because of the far-reaching effects gen AI will have across technology, operations, data management, ways of working, culture, and ultimately for the way firms create value. The majority of asset manager have already started on this journey. If you are hesitant to get moving or asking how best to scale, below are some thoughts on questions we were recently asked.

You don’t have to be a leader, but you have to get started

To harness the potential of gen AI, firms need to take action and begin exploring its benefits. While concerns around complexity, privacy, and security may hinder immediate widespread adoption, these risks can be managed through careful selection of use cases and appropriate governance practices. Firms could start by taking a gradual approach—identifying specific use cases, launching pilot projects, and cultivating a culture that embraces innovation. A good starting point could be around general productivity use cases that do not require confidential information or impact external clients. An incremental strategy would allow organizations to integrate gen AI across the enterprise at a pace that aligns with its respective risk tolerance.

Gen AI is a transformational shift – not just a tech fad

Gen AI is not like the introduction of e.g., the metaverse; it is like the adoption of the internet. This transformative technology has the potential to revolutionize the asset management industry. The ability of gen AI to generate and personalize vast amounts of content—across text, audio, images, and video—has far-reaching implications for key asset management functions. As the technology continues to mature and becomes more widely adopted, it is also likely to become an integral part of the industry’s technology stack, driving further innovation.

Gen AI is coming for tasks; it isn’t coming for jobs

Gen AI’s strength lies within language-based, generative tasks. Early adopters have seen value using gen AI as an assistant to support enhanced chatbot functionality, better internal search, generation of reports/presentation, proofreading, and other functions supporting creativity. Gen AI can help people do their job more efficiently. For instance, gen AI can go beyond merely identifying exceptions—it can provide detailed explanations, propose action items, and generate summaries that an analyst can review saving time. Consider the numerous emails, executive summaries, meeting notes, presentations, and reports that gen AI could either create or at the very least, proofread and refine. Today, gen AI is re-shaping the roles of individuals (allowing them to spend more time on higher-value activity) while over the long-term, it will shape the operating model.

Humans need to remain in the loop

Gen AI is not meant to replace humans but rather augment their skillset. Looking ahead, we can envision a future where gen AI agents and workflow orchestration will enable even greater scale and automation. However, such a transition will only occur once asset managers become comfortable with the technology, see its potential, and stand up a responsible AI governance framework. Effective change management strategies, targeted training programs and knowledge sharing initiatives are essential to ensure that teams are adaptive and responsive to the new technologies being integrated into their workflows as well as further demystify gen AI. Human expertise and judgment will remain essential with gen AI acting as a “co-pilot” rather than an “autopilot”.

Don’t just wait for technology vendors

By proactively exploring gen AI use cases and developing in-house expertise, firms could be identifying opportunities for innovation and efficiency within their four walls that may not be immediately apparent to external vendors. Relying solely on outside parties to drive adoption could limit a firm’s ability to customize and adapt gen AI solutions to their specific needs. By taking a proactive approach to gen AI adoption, firms can have greater control over the implementation process, ensuring that the technology aligns with their unique business requirements and respective competitive advantages.

Asset managers can take solace in the fact that they can start small. Having the right prioritization framework in place could allow teams to identify those use cases that minimize risk, add value, and contribute to learnings advancing the overall AI journey. Some elements of such a prioritization framework may include the use of public versus private data, end user of the output, regulatory considerations, and the level of human involvement. We would recommend starting by looking across the below categories (non-exhaustive examples) for exploring use cases:

  • Revenue generation: Summarization of sell-side research, personalized investment strategies, portfolio manager assistant, product ideation
  • Stakeholder engagement: Smart account planning, client onboarding automation, know-your-customer (KYC) support, financial advisor/sales assistant, legal review
  • Operations & productivity: Explanation of exceptions (Net Asset Values (NAVs), pricing, corp. actions), intelligent email services, request for proposal (RfP) authoring/reviewing, performance report generation
  • Data management & technology: Metadata harvesting, creation of data dictionaries, coding assistance, code modernization, software development lifecycle (SDLC) automation, synthetic data/testing environments generation, cybersecurity assistant

Selecting the right use case is just as important as learning along the way and evolving your overall governance model. In today’s evolving landscape, the real risk lies more in doing nothing. As gen AI continues to evolve, mature, and become more accessible, those who have already laid the groundwork, fostered a culture of innovation, and strategically embraced the technology should be the ones poised to seize the countless opportunities it presents.

Interested in a conversation? Feel free to reach out to us for a discussion.


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