Inside WealthTech – from the technology powering the advisor’s tech stack to the WealthTech companies defining the industry, we deliver the stories and strategies behind smarter advice. Each episode features candid conversations with industry leaders about the technologies, ideas, and partnerships transforming the way advisors serve clients, grow their practices, and redefine financial outcomes.
In this episode of Inside WealthTech, filmed live at Future Proof, Envestnet’s Blake Wood, Head of Strategic Partnerships, speaks with Eric Dziewiontkoski, Head of Product for Direct Advisory Suite at Morningstar, to explore how AI is transforming the research landscape, why data governance is becoming a competitive differentiator, and why the human connection remains the ultimate advantage.
Shortening the path from research to recommendation
Data has never been more abundant. For many advisors, the challenge isn't access to data – it's accessing trusted data and making sense of it quickly enough to act. This is the challenge Dziewiontkoski and his team at Morningstar work to solve every day, as they create solutions that help advisors go from data to insights to action.
Advisory research workflows tend to follow a familiar pattern: search for information, screen the search results, find opportunities, contextualize and make sense of the findings, and then determine what to do with the research. Each step takes time. Each handoff between tools introduces friction. In a business where an advisor might be preparing for a dozen client conversations a week, advisors need a way to accelerate this process.
The answer isn’t more data. It’s a smarter path through it – and AI is the solution that’s clearing the way.
“Really look at how you’re solving the problem and ask yourself if AI can help solve that problem faster.”
AI’s real role in wealthtech
When robo-advisors emerged, the fear was that they would replace human advisors. Instead, robo-advisors have proven how much human advisors matter. Today, AI is prompting the same conversation – but the main question has already shifted from whether or not to adopt AI, to how.
The advisors getting the most value from AI are those who use it to shorten the path from insights to action. Take meeting preparation, for instance. Instead of clicking through multiple modules before a client call, an advisor can use AI to surface a portfolio summary and see recent changes, key talking points, and other relevant context, and then go deeper only if needed. Multiplied across a full calendar, the time saved adds up.
Meeting prep is only the beginning. As the investment landscape grows more complex with ETFs as a share class, public-private convergence, and an expanding alternatives market, there are multiple layers of decisions for advisors to work through. Advisors who use AI to navigate that complexity and arrive at a well-grounded recommendation can gain a significant edge.
Ultimately, AI streamlines the process, but it doesn’t replace the advisor’s judgement.
“AI is here. I think we must embrace it. You don’t want it to happen to you. You want it to happen with you.”
The trust layer
AI tools are only as good as the data that powers them. And in a regulated, high-stakes environment like wealth management, it’s critical to have confidence in that data and know where it comes from.
“Data governance, the compliance piece, is really what’s going to differentiate solutions in the market. Having the data, methodologies, and controls in place will help ensure advisors are able to justify their recommendations to a client, compliance officer, or a regulator. Honestly, I think we all need to be taking that more to heart.”
The stakes are high and the margin for error is low. Advisors who can point to the source of an insight and explain the methodology behind a recommendation are in a fundamentally stronger position – with clients, with compliance, and with regulators. In an industry built on trust, platforms like Envestnet’s that take data governance seriously and deliver AI-powered insights based on quality data aren't just reducing risk. They're creating a foundation for smarter decisions, more impactful outcomes, and client relationships that stand the test of time.
Making every client feel like the only client
Building trust is critical in an industry where more and more advisors are retiring and fewer young professionals are entering the field – all while client expectations continue to rise. Opportunities are increasing too, with the generational wealth transfer putting more money in motion than any prior period in history.
As a result, advisors are under pressure to serve a growing book of clients – without losing the personal connection that builds trust.
Technology serves as the great enabler, because it allows advisors to scale their practices and serve more clients more efficiently. Yet there’s a limit to what technology can do on its own. Behind all of their other questions, what clients really want to know is, “am I going to be okay?" These concerns can’t be resolved by data, but by advisors who work to build long-term relationships with clients based on understanding, validation, and trust.
The advisors who use technology to handle the day-to-day research, proposals, and meeting prep are the ones who have more time for the conversations that matter most.
“Investors are more informed than ever, and can use their own tools to invest themselves. But they come to the advisor for the relationship, for the expertise. They want to know they're going to be okay – that they're going to reach their goals.”
Rapid-fire reflections
As part of Inside WealthTech’s speed round, Dziewiontkoski offers his quick takes on wealth management topics and trends:
- Active vs passive in 2028: balance, barbell or outcome driven? “Outcome driven.”
- ESG demand: structural shift or cyclical interest? “Cyclical demand.”
- AI in portfolio construction: augmentation or automation? “Both.”
- Advisor tech stack: best of breed or consolidated suite? “Best of breed. It’s hard to do everything and do everything well.”
- Alternatives in retail portfolios: early innings or fully mainstream? “Early innings. We still need to provide the data and the insights to make better decisions.”
Whether it's prioritizing outcomes, keeping humans in the loop on AI-assisted decisions, or deliberately choosing which tools belong in the stack, Dziewiontkoski's instinct is always to ask what actually moves the needle – for the advisor, and ultimately, for the client.
Stay Inside WealthTech
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Learn more about Envestnet’s wealth management platform and how it helps advisors turn data into decisions.
Full transcript
Envestnet Inside WealthTech – Morningstar
Interviewer: Eric, tell us a little bit about Morningstar and the unique position you occupy in the wealth management ecosystem.
Eric Dziewiontkoski: Many people know Morningstar as a leading provider of independent investment data and research. We've been around for more than 40 years, guided by a mission to empower investor success through transparency, independence, and a long-term perspective. Everything we do, from indexes and research to tools, solutions, and portfolios, is grounded in that mission. We've been at the center of the wealth management ecosystem for decades, and we take that responsibility seriously. Being a mission-driven company focused on helping investors succeed makes it a rewarding place to work.
Interviewer: Morningstar has long been synonymous with research, data, and ratings. As Head of Product for the Direct Advisory Suite, how are you translating that research heritage into workflow-native tools that improve portfolio construction and the client experience?
Eric Dziewiontkoski: From a product perspective, it starts with solving advisor problems. We think about taking our data and research and turning it into action.
Advisors have long relied on Morningstar's data, ratings, and tools to help clients understand their portfolios and reach their goals. In the AI era, quality data matters more than ever. High-quality inputs lead to better outcomes, while poor inputs lead to poor results. That's an area where Morningstar is well positioned. We can provide grounded insights that help advisors move from information to action faster.
Historically, advisors had to search for information, evaluate it, and determine next steps. AI can help accelerate that process. It doesn't replace advisors, but it can help them get from insight to action more efficiently while enabling personalization at scale.
The industry is also facing rapidly expanding product choice, including ETFs, private market access, and new investment structures. Advisors need help making sense of that complexity. Morningstar can help provide the data, analytics, and workflows to support those decisions.
AI is simply one tool for solving problems. The goal isn't to use AI for everything. It's about identifying the right problem and determining when AI can help advisors reach better outcomes faster.
Interviewer: Advisors increasingly operate across multiple custodians and technology platforms. How does Morningstar maintain deep workflow integration while preserving the objectivity and independence that define your brand?
Eric Dziewiontkoski: We recognize that advisors use a wide range of technologies and that Morningstar is only one part of their ecosystem.
Our focus is on strengthening integrations and helping advisors get value from their data more efficiently. That means bringing data into our platform to generate insights, while also enabling data to flow back out so advisors can complete workflows across their broader technology stack.
Ultimately, it's about reducing friction. Technology continues to make that easier, but success still comes down to solving the right problems and prioritizing the areas where advisors need the most support.
Interviewer: Advisors are under pressure to deliver increasingly personalized experiences, whether that's tax-aware investing, ESG preferences, alternatives, or customized portfolio adjustments. How are you designing the platform to support those needs without overwhelming users?
Eric Dziewiontkoski: The answer is simplicity.
We are focused on helping advisors complete their work faster and more intuitively. Historically, many workflows required moving between separate modules for research, portfolio construction, and proposal generation. Today, we're rethinking those experiences and bringing them together in a more unified way.
We recently launched a new AI assistant designed to streamline those workflows. We've also introduced an MCP connector that allows advisors to connect Direct Advisory Suite capabilities into third-party AI environments, giving them access to our research, analytics, and intellectual property within those experiences.
For example, if an advisor has an upcoming client meeting, they can use the assistant to prepare quickly rather than navigating through multiple systems and reports. The goal is to simplify work while enabling faster access to meaningful insights.
Interviewer: As AI becomes more deeply embedded in research and recommendation workflows, how is Morningstar thinking about transparency, explainability, and maintaining advisor trust?
Eric Dziewiontkoski: This is an area where Morningstar's heritage becomes especially important.
We've built our reputation on independence and transparency. Our methodologies have always been publicly available, and we've spent decades earning trust from investors and advisors.
As AI adoption accelerates, trust in the underlying data becomes critical. Our solutions are built on independent research, ratings, and data. We emphasize explainability by providing transparency into the sources and methodologies behind our insights.
We're also committed to strong data governance practices. Client data is not used to train models. As AI becomes increasingly integrated into wealth management, governance, compliance, and transparency will become even more important differentiators.
We've seen similar concerns before. Years ago, many believed robo-advisors would replace human advisors. Instead, advisors adapted and continued to play a critical role. AI represents another evolution. Firms that can provide trusted, explainable outcomes will be best positioned for long-term success.
Interviewer: Looking three to five years ahead, what will differentiate the next generation of intelligent advisory platforms, and where is Morningstar investing?
Eric Dziewiontkoski: We're continuing to invest in our core strengths: data, research, and analytics.
AI is here to stay, and firms need to embrace it thoughtfully. Advisors should be experimenting and learning how these tools can support their businesses, but always with a focus on solving real problems.
The future isn't about replacing advisors. It's about helping them serve more clients and deliver more personalized experiences.
The industry is facing significant demographic shifts, including advisor retirements and increasing client expectations. Advisors will need technology that helps them scale without sacrificing personalization.
Investors today have access to more information than ever before. They aren't looking to advisors simply for information. They want expertise, guidance, and confidence that they'll achieve their goals. We believe Morningstar can help advisors deliver that experience more effectively.
Interviewer: Active or passive investing in 2028?
Eric Dziewiontkoski: Outcome-driven.
Interviewer: ESG demand: structural shift or cyclical interest?
Eric Dziewiontkoski: Cyclical interest.
Interviewer: AI in portfolio construction: augmentation or automation?
Eric Dziewiontkoski: Both, with a human in the loop.
Interviewer: Advisor technology stack: best-of-breed or consolidated suite?
Eric Dziewiontkoski: Best-of-breed. It's hard to do everything and do everything well.
Interviewer: Alternatives in retail portfolios: early innings or fully mainstream?
Eric Dziewiontkoski: Early innings. We still need to provide the data and insights to make better decisions.
Interviewer: Eric, thank you so much for joining us.
Eric Dziewiontkoski: Thanks for having me. It's been a pleasure.
