WSR Editor in Chief Julius Buchanan hosted Churni Bhattacharya, Chief Product Officer; David Hatfield, Chief Technology Officer; and Jack Martin, Chief Marketing Officer at Amplify Platform, for the webinar “Connected Data Is the New Alpha: The Conversation.” The discussion tested claims from the executives’ white paper, “Connected Data Is the New Alpha: Why Connected Data Determines Who Wins the AI Era.”
The paper contrasts roughly 12.5% organic growth at firms with connected data architectures with an industry rate near 3%. Martin argued that the underlying problem for many firms is fragmented data spread across CRM, financial planning, billing and other systems. AI, he said, can expose and amplify that fragmentation rather than solve it automatically. “AI is the how, not the what,” Martin said.
Bhattacharya drew a distinction between integration and genuinely connected data. A CRM or planning system may be accurate on its own, she explained, yet a workflow spanning several applications can create multiple versions of the “truth.” She suggested testing that problem through a basic concept such as a household: If CRM, custody, proposal and planning systems define the same household differently, the firm still has reconciliation work to do. AI raises the stakes because poor inputs can produce increasingly polished but unreliable outputs.
Addressing whether technology actually causes the growth gap, Martin said that high-performing firms may share many of the same tools and talent as slower-growing peers. He argued that the difference lies in how firms use connected data and automated workflows to free advisor capacity for client work, marketing and more personalized service.
Hatfield cautioned against assuming that better AI models will eventually clean up weak data foundations. More capable models can produce faster and more convincing analysis from flawed source data, he said, potentially making errors harder to spot. “You’re just accelerating your failure,” he said. The remedy, in his view, begins with clear definitions, governance and context around the data that AI receives.
That does not necessarily require a large enterprise technology budget. Hatfield advised mid-market firms to establish discipline around their data, define a narrow objective and pursue a sequence of small wins, such as automating labor-intensive meeting notes.
Bhattacharya then addressed the connection between architecture and the client experience. She said clients ultimately notice whether an advisor reaches them at the right time, in the right way and with the right information. When systems produce irrelevant outreach, missing context or incorrect reports, she said, “you sense whether it is seamless or you sense that the seams are showing up.”
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