What if you could test how a client would react to a message before it’s even sent?
The emerging world of AI-powered simulation sandboxes could provide just such an opportunity.
Financial Planning’s recent AI Virtual Summit, a precursor to the upcoming Advise AI conference in Las Vegas, focused on this topic during a fireside chat between Editor-in-Chief Brian Wallheimer and EY Consulting’s Sameer Munshi, head of behavioral science and simulation.
What are simulation sandboxes?
With AI simulation sandboxes, which Munshi compared to crystal balls, advisors can “recreate” any demographic in the world via synthetic data and agentic AI.
“It’s recreating the parameters of a human,” he said. “It’s decoding human behavior based on how you describe it.”
Once that simulation is set up, Munshi said advisors can interact with these “people” in a qualitative conversation, posing targeted questions in order to test what messaging — or even a new price point — resonates with a particular client population.
“‘How can I engage? What if I raise prices?’ The use cases are really limitless,” he said. “Simulation changes the sort of historical approach of, ‘Let’s go try something in the real world,’ and then ask, ‘Did it work?’ Now you can say, ‘Let’s test it in the sandbox. Will it work in the real world?'”
The immediate benefits of the AI simulation sandbox are obvious, said Munshi. Traditional surveys can take months and hundreds of thousands of dollars to complete. And by the time the advisors sees the survey results, the world may have changed so much that the data is no longer useful.
“The power of this technology is understanding what investors or consumers actually want, even if it’s not a perfect correlation to what exists today from a research perspective,” he said. “The fact that you can get it in days instead of months is going to completely change how we think about research.”
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A diverse array of organizations, from nonprofit institutions to the Department of Defense, is already engaging with this technology, said Munshi.
“If you’re running for office at any level, wouldn’t you want a crystal ball that can recreate your district or your voting population, so that you can test your campaign messaging?” he said. “You can test that versus another candidate, and you can see who you can sway.”
How advisors could deploy this technology, keeping compliance in mind
Compliance is an important use case for AI-powered simulation environments, said William Trout, director of securities and investments at technology data firm Datos Insights, who spoke with FP outside of the summit. In terms of investment suitability, simulations could test portfolio recommendations against diverse client profiles, ensuring recommendations truly serve client interests rather than advisor compensation structures, he said.
“Marketing compliance would benefit from testing communications across different demographics to identify misleading language,” he said. “Documentation standards could be strengthened by generating compliant communication templates and creating audit trails. This is crucial since the SEC can demand all electronic client communications.”
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Anti-money laundering is a major compliance concern, and simulations could test transaction monitoring using synthetic suspicious patterns, said Trout.
“Training applications could create realistic ethical scenarios without exposing actual client data,” he said. “The key advantage is proactive risk identification — testing compliance frameworks safely before real-world application.”
During the fireside chat, Munshi said advisors could create a sandbox of 200-300 clients in their book of business, fed with nonsensitive data.
“Now, as an advisor, you’re able to mimic everything from, ‘What’s the right medium and timing of a message?'” he said. “‘How do I think about the next-gen conversation?’ Anything that you’re going to do in the real world, you can now … practice if you’re sort of newer to the industry, or you’re optimizing so that you’re spending your time and getting the best outcome out of that time invested.”
Chad D. Cummings, CEO of estate planning and tax firm Cummings & Cummings Law in Bonita Springs, Florida, assists high net worth clients and family offices with developing and implementing tax-efficient and legally compliant financial, estate and wealth preservation plans. He spoke with FP outside of the Virtual Summit. The next step for firms considering adoption of these sandboxes, Cummings said, is to begin with a narrow pilot program that uses nonsensitive data. For example, an advisory team could test how an AI-generated client reacts to a quarterly market commentary before distributing it.
“Compliance officers should be integrated into the process from the outset to ensure the tool is configured with the relevant SEC, FINRA and CFP Board standards,” he said. “Firms should also establish internal policies clarifying that AI tools are aids, not substitutes, and that final responsibility always remains with the advisor.”
More real-world applications of this technology
While AI adoption among financial advisors has increased dramatically in 2025, the specific concept of comprehensive simulation environments for testing client reactions is “pretty nascent,” said Trout, who has not seen many deployed use cases for AI-powered simulation sandboxes in wealth management.
“That said, I think the sandboxes are definitely worth trying out, as they offer potentially transformative benefits across multiple operational areas,” he said.
Such sandboxes enable risk-free experimentation with client interactions, marketing strategies and portfolio recommendations in controlled environments, said Trout.
“They accelerate client growth by helping advisors identify high-potential prospects and refine outreach strategies that improve conversion rates and retention,” he said. “Enhanced productivity comes from offloading routine tasks like meeting preparation, follow-ups and client research to AI agents, allowing advisors to focus on high-value relationship building and strategic planning.”
Another example of how advisors can use sandboxes is determining whether to raise fees, and if so, how much, said Munshi.
“What happens if you just increase the fees with your standard disclosures?” he said. “Who reacts? Is it 10% of your book? Is it 50%? Do you retain them? Or do they leave? You can ask these questions in your sandbox and watch what happens. If only 5% or 10% of your book leaves, but you’re earning 10 basis points in perpetuity, you’re going to be on net more profitable. I’m not saying that’s the right thing to do, but you’re able to test that.”
Advisors can also use the technology to decide how to invest in ads, said Munshi.
“The whole thing is effectively an experiment,” he said. “You are coming up with … copy ideas. You’re thinking about which platform, LinkedIn or Meta or even TikTok these days, and you’re spending a lot of money to learn which ads succeed. Is it based on the timing? Was it the platform? Digital marketing optimization is the best we’ve had to date. It’s still very expensive, if you compare it to what you can now do in a simulation.”
The sandboxes also provide continuous learning opportunities through data generation that trains models and refines strategies over time, said Trout.
“Perhaps most critically, they enable innovation without disrupting existing operations, making them ideal for pilot programs and proof-of-concept testing while delivering data-driven insights into client behavior and preferences,” said Trout.
The relationship between advisor and client must remain
How will clients respond if they realize advisors are using this technology?
Wallheimer referenced a recent Morningstar study that found that investors would be willing to pay an average of $74 per hour for the services of advisors who wrote their own emails. That figure dropped to $54 per hour when investors knew the emails were written by AI.
In response, Munshi said he “firmly believes” AI only advances, not replaces, human talents.
“But I do think it completely sort of shifts the day-to-day away from the monotonous inputting and chair-swivel compliance, all these frustrating tasks that you have to do,” he said. “It frees up time to do the thing that advisors are so talented at, which is developing, maintaining and expanding human relationships.”
When it comes to insights gleaned from simulated sandboxes, Munshi said there should always be a human check.
“Because it’s at the end of the day, it’s a relationship,” he said. “It’s very possible, when you’re getting down to the individual level, you’re going to know, as an advisor, more than the simulation.”
