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[Asset Management distribution teams have long been promised that AI and intelligence platforms would make their jobs easier. Yet, in practice, many wholesalers and their internal sales support reps underutilize these tools.
In speaking with distribution teams, one theme emerges again and again: a lack of trust. Many sales professionals remain skeptical of the technology built for them – questioning its recommendations or doubting its ability to reflect the realities of their client relationships.
This is not just a tech adoption problem as it strikes at the heart of the innovation itself. Is the tech delivering tangible value or are there gaps in the product design or value proposition that create hesitation instead of confidence?
To unpack this innovation challenge in asset management distribution, I spoke to Jeff Mehi, Head of Wealth Partnerships at TIFIN AMP – an AI-driven distribution platform that blends data science, engineering, and machine learning to deliver more intelligent distribution solutions.
What follows is a look at why sales teams are skeptical of distribution intelligence tools and, more importantly, how thoughtful technology design can transform doubt into advocacy. It is a roadmap for leaders who want to drive adoption, accelerate time-to-action, and unlock the full ROI of their data investments.]
Hortz: What are the major challenges you see that asset management distribution teams face?
Mehi: One of the biggest challenges distribution sales teams face is measuring ROI and performance. Management wants to see the results of every campaign, every initiative, and even the efforts of individual salespeople. But in a twenty- to fifty-person distribution team, keeping tabs on everything is complex. Now just imagine when there are over one hundred!
For the sales teams themselves, the struggle starts with efficiency. First, they have a hard time getting the right data. Salespeople often receive irrelevant insights or sales campaigns that do not match what they know about their advisors or the products they are focused on. Then, they run into disconnected systems and enablement tools that do not match or integrate into their daily workflow. That additional manual effort begins to erode trust and may even distract the salesperson from being a salesperson by trying so hard to understand the tools being made available to them. The net result is more frustration and less activity and sales.
Often, instead of addressing the root cause, firms respond by hiring more people – especially internal wholesalers and business intelligence specialists – essentially “blunt forcing” their way through the problem rather than fixing the underlying issues.
What is the result of all this? Lost opportunities. In one case, a salesperson missed a $10 million ETF opportunity because the data was not unified and the salesperson simply did not know it was there.
Ultimately, this creates a two-sided dilemma: management collects data to measure the business, but are they using it effectively? And, are salespeople actually able to leverage that data to make decisions and grow market share in the field?
Hortz: What do you feel are the main reasons sales teams are skeptical of AI distribution tools that were built to support their efforts?
Mehi: In my experience, there are three main reasons why asset management sales teams are skeptical of AI distribution tools: lack of transparency, limited context, and poor user experience. All three have to work together for a tool to succeed – if one is missing, adoption suffers.
Lack of Transparency – The “Black Box” Problem
Many AI tools deliver recommendations or scores without showing how they were generated. Salespeople are handed a spreadsheet with an advisor’s name and some scoring number and told, “Trust us, this is who you should call next.” When those recommendations do not align with their own experience in the field and they cannot see the “why” behind the score, trust decays quickly.
Limited Context – Insights Without Action
Even when tools identify the “what,” they often fail to provide the “how.” A recommendation without supporting information or guidance on how to act on it is incomplete. Salespeople need context around why a lead is prioritized and what steps they should take to make it actionable. Without that, the insight feels disconnected and gets ignored.
Poor User Experience – Clunky and Disruptive Tools
Many platforms are hard to use, do not integrate with CRM systems, and interrupt workflow. When a salesperson has to toggle between multiple screens or re-enter actions into the CRM manually, it slows them down. In a high-velocity sales environment, that kind of friction is the difference between adoption and abandonment.
When you address all three of these issues – transparency, context, and usability – adoption rates change dramatically. While I have seen instances of industry-wide adoption of these tools struggle at 30-40%, our AI distribution platform at TIFIN AMP has achieved approximately 98% adoption by focusing on these core principles. That is why we built our platform with what we call a “glass box” approach, full CRM integration, and actionable insights at the center of the design.
Hortz: Can you give us a brief overview of how you built your AI intelligence tools and distribution platform to address these challenges for distribution professionals?
Mehi: To address these challenges, we built our AI intelligence tools specifically for asset management distribution teams with one goal in mind – generate actionable insights by “connecting the dots” across a unified data organization.
At the core of the platform are three key algorithms that work together:
- Relevancy Algorithm – Determines whether a product is a good fit for a specific advisor.
- Opportunity Set Algorithm – Evaluates the size of the potential opportunity (e.g., $1M vs. $10M).
- Engagement Algorithm – Measures advisor responsiveness and interest over time.
Each of these algorithms produces an individual score, and together they combine into a comprehensive, actionable ranking. Behind the scenes, we are processing 20–30 different factors across these models, but for the end user it all surfaces as a simple, easy-to-read score designed to help salespeople make fast, confident, engagement decisions.
Importantly, we knew from the start that even the most sophisticated AI would not matter if sales teams did not trust it. That is why we built the platform using what we call a “Glass Box” approach. Instead of delivering “black box” scores and saying, “Trust us, call this advisor next,” our tools show the underlying data and logic that shaped the recommendation. Salespeople can see why an advisor was prioritized and which factors influenced the score, which makes the insight both transparent and actionable.
Seamless workflow integration was also critical. We embedded the AI directly inside Salesforce and other sales systems so the intelligence lives where salespeople already work. That way, contextual insights – like spotting a client who increased ETF holdings by 40% in the last six months – surface right at the moment of engagement, not in a disconnected dashboard they rarely open.
To solve the ROI and efficiency pain points for sales managers, we also built the Initiative Command Center. This functionality allows managers to launch targeted sales initiatives at scale and then measure results in real-time across their teams without relying on manual reporting. It closes the loop between strategy and execution by letting managers see exactly what is working, which campaigns are driving revenue, and where to reallocate resources.
Ultimately, these design choices – transparent scoring, workflow integration, and the Initiative Command Center – are all aimed at removing the reporting burden, connecting fragmented data, and giving both salespeople and managers a clear line of sight into performance and ROI. That is what turns intelligence into real distribution enablement.
Hortz: Can you share any thoughts or advice that distribution professionals should consider in using new technologies like AI?
Mehi: At this moment of rapid technological acceleration, my strongest recommendation is for distribution teams to partner on technology development rather than try to build and maintain every piece of an AI and data stack in-house. That advice is not just because I work at a tech firm; it is because objectively, keeping pace with AI innovation is a full-time job. New capabilities are emerging every few months, and it is difficult for most firms to invest in the infrastructure needed to keep up.
For the majority of asset managers, outsourcing to a strategic partner ensures you get a fully customized, fully integrated distribution enablement platform without the risk, cost, and time of trying to build it internally. Building internally, you are often looking at:
- 18+ month roadmaps to reach deployment,
- Multiple headcount or consulting budgets with no guaranteed outcome, and
- Knowledge risk if a key architect or head of distribution intelligence leaves midstream.
Even for firms with sophisticated AI, business intelligence, and tech teams already in place, there is a strong case for partnership. A platform like TIFIN AMP allows those teams to focus on their core functions and enterprise-wide initiatives, while leveraging our expertise to deliver bespoke use cases and distribution-specific intelligence at speed. It is not about replacing internal capabilities – it is about complementing them and accelerating their impact.
For distribution professionals themselves, the message is the same – be vocal about your technology needs. The competitive disadvantage of lagging on AI-driven sales enablement is real; competitors adopting advanced tools will move faster than you. Even when job hunting, it is worth asking: What distribution enablement tools does this firm have to help me succeed?
Bottom line: embrace AI technologies through strategic partnerships. Whether you need a turnkey platform or a specialized partner to amplify your internal team, that is how you keep pace with the market, reduce tech debt, and unlock value faster.
This article was originally published here and is republished on Wealthtender with permission.
About the Author
Bill Hortz
Founder Institute for Innovation Development
To make Wealthtender free for readers, we earn money from advertisers, including financial professionals and firms that pay to be featured. This creates a conflict of interest when we favor their promotion over others. Read our editorial policy and terms of service to learn more. Wealthtender is not a client of these financial services providers.
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