Staying relevant in the AI era: A guide for mid-career investment professionals
As artificial intelligence is increasingly integrated into daily workflows across investment management, how can mid-career professionals adapt and thrive?
Artificial intelligence (AI) and automation have the potential to enhance productivity, improve outcomes and reshape the client experience in investment management. While this creates a host of opportunities for mid-career professionals, it also raises a burning question: how do you stay relevant in an industry that’s evolving so fast?
It begins with appreciating where the industry is likely to be heading in the near future. While much of the focus today is on generative AI (GenAI) tools, institutions are increasingly turning their attention to Agentic AI, capable of managing entire workflows independently. Agentic AI will usher in a far greater productivity boost than current GenAI tools and copilots, predicts consultancy McKinsey.
In this new landscape, the finance industry could soon consist of professionals overseeing, validating and determining goals for ‘teams’ of AI agents, enabling them to do many more tasks, far more efficiently. Fluency in AI tools and Agentic AI will be non-negotiable.
Maxim Tambling, Head of Global Talent Management at Vanguard, said: “I really don't see a role type where not having AI literacy is going to be okay in the future.”
To provide finance professionals practical guidance on using Agentic AI, CFA Institute recently published a report with examples of how such systems can be incorporated in investment management workflows, along with advice on how to turn early prototypes into more reliable, auditable tools.
Agentic AI will drive the next stage of automation and enhancement of the investment process. Already, AI’s ability to sift through vast datasets to identify patterns and generate insight has been applied to streamlining portfolio construction and optimization. AI can also greatly improve execution of trades.
These functions can be further improved and automated by integrating AI agents’ natural language processing capabilities and contextual awareness. For example, Agentic AI can augment traditional portfolio construction to produce highly customized, client-specific portfolios at scale.
Staying in the loop
To succeed in an increasingly AI-driven industry, finance professionals will need to be able to work alongside technology and understand its strategic implications for stakeholders.
The goal for mid-career professionals is not to become AI experts. Instead, it is to become fluent in the use of the GenAI tools for their day-to-day workflows, and familiar enough with emerging technologies such as Agentic AI and quantum computing to understand how they can be used to derive a competitive advantage for their firms — along with the risks of using them, and the oversight needed to keep things on track.
To keep abreast of the latest AI developments impacting their industry, mid-career professionals should adopt a proactive, multi-channel learning strategy. This includes following resources such as CFA Institute’s The Automation Ahead series and other reputable fintech and AI newsletters, attending industry conferences and webinars, and engaging with thought leaders on platforms like LinkedIn.
It's also worth seeking opportunities to pick up AI skills on the job. One way to do that, according to Eleonore Dachicourt, CFA, Head of Sustainable Investments, Wealth Management, Asia, at BNP Paribas, is to participate in cross-generational knowledge exchange by working with younger colleagues.
“As senior leaders, we need to empower and learn from the younger generation – the digital natives – for whom technology and AI come naturally, while we bring experience, context, and judgement,” she said. “That blend of skills is where the real value lies.”
Another way is to assign yourself mini projects which require picking up specific AI skills or knowledge by a given deadline, as well as committing more broadly to lifelong learning for mid-career finance professionals, and finding ways to fit professional development into a busy schedule.
Time for self-reflection
In view of the AI-driven transformation that lies ahead, it’s also a good time to take stock of the role you’re currently performing, said Stephanie Liang Shi Xian, CFA, Portfolio Manager at Dimensional Fund Advisors.
“Ask yourself what are the things you’re doing that AI can either automate or reduce, and what are the things that are still adding value overall,” she said.
For Liang, the inexorable march of automation means her role is increasingly about providing human oversight. “When everything is rules-based, you need to make sure things are going as expected,” she said. “You need experience and critical thinking to identify when things go wrong.”
A host of other human skills are needed to ensure that you continue to add value as AI works its way into more processes. Scott Taylor, Professor of Organizational Behavior at Babson College, highlighted the importance of communicating with others and winning their trust.
“I may be able to get AI to do a lot of what I do, but I still have to convince others about the relevance of that work,” said Taylor. “I still have to be able to take feedback effectively about that work. There’s a heightened need to be able to take that AI output or discovery and socialize it in a way that has impact in how we do business or how we make decisions.”
Tambling added that the people best able to achieve insights and innovation with the help of AI will be the ones with the highest levels of curiosity. “The people who know how to shape and frame questions really well, who know how to iterate and continue to build on work, who have a sense of what the output should look like, as well as the ethical considerations of AI use, and who are adaptable and able to problem-solve — they’re the key things we see.”
Virtuous cycle of tech and human capabilities
The finance industry of the future will be powered by a mutually reinforcing combination of AI tools and human insight, intuition and interpersonal skills.
Take wealth management, where AI is alleviating the administrative burden for advisors, supporting compliance and fraud detection. This frees advisors to devote more time to cultivating client relationships — calling on their communication and interpersonal skills such empathy and active listening. Moreover, AI can also help advisors build trust with clients — for example, by analyzing client communications to detect changes in sentiment or financial needs.
Then there’s fund distribution, which also revolves around adeptly identifying and handling client needs. Predictive analytics, for example, can forecast investor behavior, helping sales teams target prospects more effectively. But here again, using those data-driven insights to improve business outcomes hinges on having solid people skills like self-awareness, storytelling, collaboration and relationship building.
These skills do not have to be innate — they can be learned. One route is to enroll in one-on-one career coaching, workshops or leadership development programs. Another is to participate in cross-functional projects to practice collaboration and adaptability in diverse team settings. Then there’s actively soliciting feedback from colleagues and mentors, as well as just reading and reflecting on the topic.
Ultimately, like developing any skill, it’s about staying consistent and open to learning. And it’s a commitment worth making. At a time of rapid technological disruption, it’s the enduring power of human interaction that anchors professionals, ensuring they remain not just relevant, but indispensable.
As artificial intelligence transforms how investment professionals analyze markets, build portfolios, and manage risk, CFA Institute is delivering cutting-edge research to support the profession.
Explore AI in Asset Management: Tools, Applications, and Frontiers from CFA Institute Research Foundation and CFA Institute Policy Center.
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