In the asset management world, a quiet revolution is underway. While tech headlines often focus on flashy consumer applications, financial services firms are exploring how agentic AI can transform their investment processes and client communications. I recently sat down with Mark Goodey, co-founder of AI Infin8, to discuss this transformation and why many companies struggle to move from AI theory to practical application.
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The Dilemma of Relevancy
Goodey, a Chartered Director with over 25 years in financial services, described what he calls the “dilemma of relevancy” facing decision-makers in asset management. Many executives approach AI with inherent biases based on their experience and age, often thinking, “I know what I know, and I don’t know what I don’t know. If I don’t know what it is, how can I trust it?”
This hesitation creates a gap between executive mandates to “do more with AI” and meaningful implementation. Many organizations default to creating another chatbot or adding a “Copilot button” without addressing substantive business challenges.
From What to Why: The Real AI Opportunity
What makes AI Infin8’s approach different is their focus on explaining not just what the data shows, but why it matters. “Many companies can explain what happened in your data. Zero can explain why in this specialized field,” Goodey noted.
Traditional asset management reporting has excelled at describing structured data – columns, rows, and mathematical calculations. But clients don’t want more math; they want to understand what the numbers mean for their investments. AI can bridge this gap by translating complex financial data into clear narratives that explain both what happened and why it matters.
The Human-AI Partnership
Despite the technological possibilities, Goodey emphasized that AI implementation in financial services isn’t about removing humans from the equation. “This is not a play on removing humans necessarily, but an augmentation. Human-AI coupled together is a good thing.”
Regulatory requirements in financial services mean responsibility cannot be delegated to a computer. Instead, effective AI deployment creates systems where technology handles repetitive tasks, data analysis, and content generation while humans provide oversight, expertise, and relationship management.
Starting Small, Seeing Big Results
When I asked Goodey what advice he’d give asset management professionals looking to transform their reporting processes with AI, his answer was clear: don’t try to “boil the ocean.”
AI Infin8’s approach begins with asking clients for existing data they’ve already reported on – anonymized if needed. “Give me ten days,” Goodey said. “The team will do their magic. We’ll come back to you and recommend.” This consultative approach allows organizations to see practical applications of AI with their own data before making significant investments.
The AI Maturity Gap
Despite the buzz around AI at industry conferences like T-SAM London (Technology Solutions for Asset Managers), Goodey believes the financial services industry is still in early adoption stages. While some sectors like pharmaceuticals have moved further ahead, many financial firms are just beginning their AI journey.
This creates both challenges and opportunities. Organizations that can move beyond theoretical applications to practical implementations have the chance to differentiate themselves significantly. But doing so requires breaking through human limitations rather than technological ones.
The asset management industry stands at an inflection point where agentic AI can transform how firms analyze investments, communicate with clients, and streamline operations. As Goodey puts it, the real value comes when you can “explain why in a way the end consumer can understand.” That’s the promise of AI that forward-thinking asset managers are beginning to unlock.
This article was originally published on LinkedIn.
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