Executive Summary
Artificial intelligence is entering a new phase across the wealth management industry.
The conversation is shifting away from simply asking whether advisors should use AI. Increasingly, the question is how deeply AI should be integrated into the operating infrastructure of an advisory firm.
Recent industry developments illustrate that transition.
LPL Financial is building artificial intelligence directly into a broader technology environment connecting data, cybersecurity, advisor workflows and client applications. New AI-native infrastructure is being developed specifically for regulated advisory firms. Meanwhile, industry technology leaders are warning that fragmented data and disconnected systems could prevent firms from realizing AI’s potential.
Regulators are paying attention as well. The SEC’s 2026 Examination Priorities specifically identify artificial intelligence, automated technology, cybersecurity and the policies firms use to supervise emerging technology as areas of focus.
The message for advisory firms is becoming clearer: AI is evolving from a productivity tool into business infrastructure.
Technology & AI Scoreboard
| Trend | Direction | BKLM View |
|---|---|---|
| Agentic AI | ▲ Accelerating | AI moving from answering questions to completing workflows |
| Integrated Advisor Platforms | ▲ Strong | Large firms are consolidating fragmented technology |
| AI Governance | ▲ Increasing | Policies and supervision becoming essential |
| Data Infrastructure | ▲ Critical | Poor data could become the biggest obstacle to AI adoption |
| Cybersecurity | ▲ High Priority | Greater AI adoption increases the importance of security controls |
| Human Advice | ► Essential | AI is increasing advisor capacity—not eliminating the advisor |
1. LPL Makes a Major Bet on AI-Powered Advice
One of the industry’s most important recent technology developments is coming from LPL Financial.
LPL introduced Latitude, a unified technology environment connecting data, cybersecurity, infrastructure, artificial intelligence, advisor workflows and investor applications. The company describes the initiative as an AI-embedded technology experience rather than simply another standalone application.
At its Focus 2026 conference, LPL continued to emphasize how integrated technology and AI can increase advisor capacity and allow advisors to deliver more personalized and comprehensive advice.
One of the most interesting components is Cyan, LPL’s forthcoming AI agent. LPL identifies Cyan as part of the Latitude technology environment alongside its advisor workstation, client applications, integrated data and cybersecurity infrastructure.
BKLM View
This is much bigger than another AI meeting assistant.
A major wealth-management platform is attempting to place artificial intelligence directly inside the technology environment advisors already use.
That could represent the next stage of AdvisorTech.
Instead of opening an AI application and asking it to perform a task, the longer-term opportunity is for intelligence to exist inside the advisor’s normal workflow.
AI could eventually become less visible—not because it is less important, but because it is embedded everywhere.
2. Agentic AI Could Be the Next AdvisorTech Battleground
The first generation of generative AI largely helped advisors create something.
Draft an email.
Summarize a meeting.
Generate marketing content.
Research a topic.
Prepare an outline.
Agentic AI is potentially much more significant.
Rather than simply responding to a prompt, an AI agent can potentially understand context, interact with connected systems and execute parts of a multi-step workflow.
That transition is beginning to appear in wealth management.
Astraeus recently launched an AI-native infrastructure platform designed specifically for investment advisory firms, wealth technology platforms and other regulated businesses. The platform is intended to provide artificial intelligence with firm-specific context and support firms building AI-native operating environments.
At the same time, WealthManagement.com’s recent examination of agentic platforms highlights another issue: advisors evaluating these systems increasingly need to look beyond impressive demonstrations.
Integration capabilities, security standards, vendor financial stability, certifications and pricing could all become important considerations as AI systems become more deeply connected to firm operations.
BKLM View
There is an enormous difference between software that drafts an email and software authorized to take an action.
The potential productivity gains are significant.
So are the risks.
As AI progresses from assistant to agent, advisory firms will increasingly need to determine exactly what technology is allowed to access, recommend, change and execute.
That makes governance almost as important as capability.
3. Wealth Management Has a Data Problem
AI is exposing a technology problem that existed long before ChatGPT:
Many advisory firms operate with fragmented technology stacks.
CRM information may sit in one system.
Financial-planning information exists somewhere else.
Portfolio data resides on another platform.
Documents, marketing, compliance and client-service systems may each maintain separate information.
An August analysis published by WealthManagement.com argues that this fragmentation could become a major obstacle to AI adoption because coordinated AI systems require consistent, governed and integrated data. The analysis cites McKinsey estimates suggesting isolated AI task automation can produce productivity improvements, but redesigned workflows involving coordinated AI agents could create substantially greater gains.
The industry’s movement toward consolidation is already visible.
For example, Wells Fargo’s Advisor Gateway initiative has consolidated more than 200 proprietary and third-party tools into a single integrated advisor experience.
Other firms are approaching technology similarly. Perigon Wealth Management recently described its strategy as choosing long-term technology partners rather than constantly rebuilding its technology stack around individual new features.
BKLM View
For many advisory firms, the most important AI project may not actually be an AI project.
It may be:
Cleaning the CRM.
Organizing client data.
Connecting systems.
Standardizing workflows.
Creating a reliable source of truth.
A firm with excellent data and average AI may ultimately outperform a firm with sophisticated AI sitting on top of disorganized information.
And this issue becomes even more important as firms grow through acquisitions.
Every acquired practice can introduce another CRM structure, another set of workflows and another collection of technology.
AI makes solving that fragmentation increasingly valuable.
4. AI Is Changing the Economics of Advisor Capacity
Much of the early AI conversation focused on cost savings.
That may ultimately prove too narrow.
The larger opportunity could be capacity creation.
Consider the amount of an advisor’s week consumed by activities surrounding the actual client relationship:
- Meeting preparation
- Meeting notes
- CRM updates
- Follow-up emails
- Research
- Internal communication
- Scheduling
- Document preparation
- Marketing
- Administrative workflows
AI does not need to replace the advisor to materially change the economics of an advisory practice.
It only needs to reduce the amount of time the advisor spends on non-client-facing work.
Recent industry commentary is increasingly making this distinction. Advisors who rethink workflows around AI are finding opportunities to create additional capacity for clients rather than simply selecting another technology tool.
LPL is making a similar argument at the enterprise level: technology-enabled efficiency can create additional advisor capacity for personalized and comprehensive wealth management.
BKLM View
This could eventually become one of AI’s biggest contributions to advisory-firm economics.
Imagine an advisor who can effectively serve 120 relationships with the same service quality previously possible with 90.
Or a $1 billion RIA that can continue growing without increasing administrative headcount at the same historical rate.
Or a senior advisor who gains several additional hours each week for prospecting, centers of influence and existing high-value clients.
Those improvements can affect more than expenses.
They can influence:
Organic growth.
Operating margins.
Advisor productivity.
Client capacity.
Scalability.
And ultimately, enterprise value.
5. AI Governance Is Becoming Essential
As adoption expands, regulatory oversight becomes increasingly important.
The SEC’s Fiscal Year 2026 Examination Priorities specifically address recent advancements in artificial intelligence.
The Division of Examinations says it will review the accuracy of registrants’ representations regarding their AI capabilities and assess whether firms have adequate policies and procedures to monitor or supervise the use of AI technologies.
The SEC specifically references potential AI use across areas including back-office operations, fraud prevention and detection, anti-money-laundering functions and trading, where applicable.
That creates an important distinction between experimenting with AI personally and implementing AI institutionally.
Advisory firms increasingly need answers to questions such as:
- Which AI tools are employees permitted to use?
- Can client information be entered into those systems?
- How does the vendor store and protect data?
- Is firm data used to train external models?
- Which AI-generated materials require human review?
- How are AI-assisted recommendations supervised?
- Who approves new AI vendors?
- What happens when AI produces incorrect information?
- What controls exist before an AI agent can initiate an action?
BKLM View
The era of unofficial AI adoption inside advisory firms is likely ending.
A written AI policy could increasingly become as fundamental to an advisory firm’s infrastructure as cybersecurity procedures, email retention policies and business-continuity planning.
The firms that move fastest will still need appropriate controls.
Speed without governance creates a different kind of risk.
6. The Bigger Shift: From Technology Stack to Intelligence Layer
Taken together, these developments suggest something larger is occurring.
For roughly two decades, advisor technology largely evolved by adding applications.
A growing firm might assemble:
CRM + Financial Planning + Portfolio Management + Reporting + Document Storage + Marketing + Compliance + Communication
Every new problem created another potential software solution.
AI could begin changing that model.
Instead of an advisor manually moving between multiple applications, an intelligence layer could eventually understand information across those systems and assist with—or ultimately execute—parts of the workflow.
A client meeting could trigger:
Meeting Summary → CRM Update → Follow-Up Email → Planning Task → Service Request → Compliance Documentation
Instead of five separate manual processes, these steps could increasingly become parts of one connected workflow.
That is why the industry’s focus on data integration is so important.
AI cannot effectively orchestrate a business it cannot understand.
What Advisory Firms Should Be Doing Now
Advisory firms do not need to rebuild their businesses around AI overnight.
But they should begin preparing their infrastructure.
1. Audit the Technology Stack
Determine which applications are essential, which overlap and which cannot communicate effectively with other systems.
2. Clean the CRM
Accurate, structured client and prospect information will become increasingly valuable as AI capabilities improve.
3. Identify Repetitive Workflows
Look for high-volume administrative activities that consume staff and advisor time.
Those are often the best initial automation opportunities.
4. Establish an AI Policy
Define approved applications, data rules, human-review requirements and vendor standards.
5. Measure Capacity Created
Do not evaluate AI solely by software cost.
Measure hours saved, faster response times, increased advisor capacity and improvements in client service.
6. Keep the Advisor at the Center
Automate administration—not relationships.
The objective should be to give advisors more time for the activities where human judgment, trust and communication create the greatest value.
BKLM Perspective
Artificial intelligence is rapidly moving from a productivity experiment to a strategic business issue for advisory firms.
The first phase was largely about saving time.
The next phase appears considerably more important.
AI is beginning to affect how firms structure workflows, organize data, service clients, supervise employees, select technology vendors and create capacity for growth.
We believe this will eventually intersect directly with another major industry issue:
practice valuation.
Consider two advisory firms with identical AUM, revenue and profitability.
One operates through disconnected systems, inconsistent CRM data, advisor-dependent processes and limited technology governance.
The other has integrated technology, organized data, documented workflows, scalable processes, strong cybersecurity and institutional AI controls.
Over time, those may become very different businesses.
The second firm should be easier to scale.
Easier to transition.
Easier to integrate.
And potentially more attractive to an acquirer.
For advisors building businesses with a five-, ten- or twenty-year horizon, that may ultimately be the most important AI story of all.
Sources & Further Reading
LPL Financial — LPL Latitude
LPL’s unified technology environment integrating data, cybersecurity, infrastructure, AI, advisor workflows and investor applications.
Read the LPL announcement
LPL Financial — Focus 2026
LPL’s discussion of integrated technology, scale and advisor growth at its annual conference.
Read the Focus 2026 announcement
WealthManagement.com — Wealth Management’s AI Strategy Has a Foundation Problem
Analysis of fragmented technology stacks, data architecture and the infrastructure required for AI adoption.
Read the analysis
WealthManagement.com — Astraeus Launches AI Platform for Advisory Firms
Coverage of a new AI-native infrastructure platform designed for regulated advisory businesses.
Read the article
WealthManagement.com — A Lingua Franca for Advisors on AI
Analysis of the questions advisory firms should consider when evaluating AI agents and vendors.
Read the article
WealthManagement.com — The Latest Evolution of Enterprise Technology Is Advisor-Led
Discussion of Wells Fargo’s consolidation of more than 200 tools into Advisor Gateway.
Read the article
U.S. Securities and Exchange Commission — Fiscal Year 2026 Examination Priorities
SEC examination priorities addressing AI, emerging financial technology, cybersecurity and supervisory policies.
Read the SEC Examination Priorities