Key Takeaways
- Treating advisors as co-designers, not end users, surfaces the highest-impact operational redesign opportunities.
- Disciplined data ownership can help reduce migration time, preserve vendor flexibility and support a sustainable competitive moat.
- Evaluating each tech solution against the full workflow prevents localized wins from sub-optimizing overall process performance.
- AI-compressed timelines can outpace organizational readiness. Embedding change management from the start can help prevent compliance and advisor bottlenecks.
Don’t Automate Your Old Wealth Management Operating Model. Redesign It.
AI and other cutting-edge technologies are radically altering the way wealth management firms work, boosting productivity and opening up new opportunities. But operating models continue to be a strategic differentiator, so it makes sense to redesign operations on the basis of technology that supports a client-centric approach rather than treating technology as peripheral.
Firms that engage their technology experts, advisors and other professionals to radically transform processes have the potential to amplify the impact — and multiply the ROI — of all their tech investments in the years ahead.
We recently engaged operations and technology executives from across the wealth management industry to talk about their experiences in leading redesign initiatives to improve service and efficiency — incorporating AI and other technologies in more powerful ways. Here are seven tips they shared for redesigning operating models effectively.
7 Ways to Ensure Your Operating Model Redesign Is a Success
1. Be creative with cross-team collaboration to achieve optimal results.
Changing an operating model requires close collaboration across multiple internal groups. Firms are organizing forums with different participants and goals to jumpstart progress. One firm hosts regular pitch-style breakfast sessions in which problem owners join with solution builders to connect business pain to technology capability without getting mired in requests for proposals (RFPs). Another firm puts together product and process experts with creative leaders who bring new ideas to the table to help the organization think about — and build — the future differently.
2. Think holistically when redesigning your operating model.
When tackling dozens of use cases for AI or other tech across a complex process, it’s possible to achieve success for each individual process element but end up sub-optimizing the impact on the entire process. Mitigate this risk by maintaining an end-to-end lens as more focused tech solutions are envisioned and integrated. Look at each person’s role holistically and reimagine where AI or tech can play a role to enhance both personal productivity and team coherence.
3. Treat advisors as co-designers, not end users.
Advisors work closely with clients every day. So, they should be involved in every stage of the redesign solution. Ask them what’s not working. Let them explain what’s clunky and frustrating about their routines, using their terms and precise examples. Dig in to surface the worst gaps. Don’t expect them to generate solutions — that’s your role. Look beyond narrow issues to envision changes of a higher order.
Such insights prompted one firm to change its legal entity structure to standardize forms and regulations, simplifying advisor routines and helping the business to scale.
4. Try new tech partners, but hang onto your data.
Many firms want to try new processes and tools. But they should avoid the temptation of trying something new just for the sake of it. Minimizing the number of partners they work with will leave them flexibility if one of them underperforms.
One universal untouchable is data. Firms consider data to be a strategic moat and are investing to get a better grip on their data infrastructure and consistency. One firm noted that strong data quality helped make its CRM migration more efficient, while another said clear data ownership supported a smoother vendor transition.
5. Envision and create more impactful roles for people.
Process redesign should seek to elevate quality and service, not cut positions. One firm reduced operational complexity while also creating a deeper client experience. It did so by combining its separate client-facing and transaction-handling service teams — and then upskilling everyone to form an agile, multi-service unit. This eliminated handoffs, supported one-and-done client sessions and simplified the integration of AI.
6. Embed change management throughout the entire process.
Just because AI can compress timelines doesn’t mean organizations are ready for it. A project that not long ago would have taken months to complete now might take weeks to complete with the help of AI. But with speed comes the risk that legal, compliance and advisor teams — built for slower release cycles — become a bottleneck. Communications, engagement and sound change management from start to finish can reconcile such issues and assure steady progress.
7. Invest prudently in technology — and keep your team fully engaged.
Firms that lack discipline in AI tool selection will accumulate technical debt that erodes the gains of modernization. Firms must balance the competitive demand to streamline the suite of AI and other tools with the need to provide flexibility for advisors — and other team members — to deliver superior client service that can keep growth strong.
Rebuild Your Operating Model — and Capture More Growth
AI and other emerging technologies are reshaping wealth management. The firms that will lead this shift are not the ones with the most advanced tools. They are the ones that redesign their operating models to put those tools to work — around clear data ownership, cross-team collaboration and disciplined investment that compounds rather than accumulates as technical debt.
That kind of redesign is difficult to execute alone. It requires deep understanding of the technology, the workflows and the change management needed to bring advisors and operations teams along. The firms succeeding at it are treating the operating model itself as the strategic asset — engineering it deliberately, governing data as a moat and adapting at the pace AI now demands.
The technology is ready. The differentiator is the operating model you build around it.
Examples discussed in this article are illustrative and not necessarily representative of all firms. Outcomes may vary based on factors such as firm size, business model, service mix, data maturity, technology environment and implementation approach. This article is based on panel discussions from BNY INSITE 2026, which featured executives from wealth management firms that are restructuring their operating models to achieve greater performance from AI and other technologies.
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