How AI Is Transforming Financial Planning

Most people's experience of financial planning starts at a bank, where the advisor is paid to sell products rather than give advice. The plan you receive is often an investment illustration dressed up with charts and projections. What it is not, in most cases, is a comprehensive plan for your financial life.

Braden Warwick spent his PhD optimizing aircraft noise at Queen's University, then made an unlikely career switch: joining PWL Capital, a Canadian fee-only wealth management firm, to apply an engineering mindset to financial planning. Today he is the firm's Financial Planning Product Architect and is building the AI infrastructure that will eventually allow PWL to scale quality financial advice beyond its current client base.

He joined The AI Report podcast to walk through how they do it.

What a Real Financial Plan Actually Covers

Before getting into the AI piece, Braden is clear about what financial planning actually is, because the industry has spent decades confusing it with investment management.

A comprehensive financial plan covers six areas: investing, cash flow, tax, insurance, retirement, and estate planning. Most people only ever hear about the first one.

PWL's model is different. Its advisors charge a fee based on the assets they manage and do not receive commissions or referral fees from investment products. The incentive is to give the best possible advice across all six areas of someone's financial life.

The Engineering Frame

Braden approaches financial planning the same way he approached aerospace engineering: define your objectives, establish your constraints, then solve for the best outcome.

The objectives are the client's goals, which are more varied than most people assume. Some clients want to maximize wealth. Others want to retire early, fund education, give money to their kids, or simply be able to spend generously on experiences throughout their life. Figuring out what actually matters to a specific person, rather than assuming the goal is maximum returns, is the first job of the financial planner.

Constraints are the parameters that shape what is possible, many of them set by the tax code. The role of the planner is to identify what levers exist within those constraints and pull the right ones for each client's situation.

Once objectives and constraints are defined, the plan can be built. PWL uses Monte Carlo simulations to model outcomes: run thousands of different simulations of someone's financial life with varying market conditions, and make sure the plan holds up across the worst half of those scenarios, not just the average one. The output is not a single projected number but a distribution of possible outcomes, and the question the planner is asking is whether the plan survives the bad ones.

What this unlocks is counterintuitive. Most people assume financial planning is about being told to save more and spend less. Braden describes the actual goal differently: figure out the maximum a client can sustainably spend across their life while still meeting their goals. Sometimes that number is higher than the client expected. He talks about clients who come in over-saving, and the advisor's job in those cases is to give them permission to spend more on the things that actually matter to them, whether that is travel, time with family, or experiences they have been putting off. The simulation makes that conversation concrete. Instead of a vague reassurance, there is a number.

Braden also notes that most financial software captures market uncertainty well but misses other critical forms of uncertainty: real estate values, life expectancy, changes in spending over time. Those need to be modeled even if they fall outside the standard Monte Carlo framework.

What PWL Is Building with AI

PWL manages approximately five to six billion dollars in assets and was acquired by One Digital, one of the largest financial advisory networks in the United States, in early 2025. Braden has been building the firm's proprietary technology stack since joining in 2020, and AI has dramatically accelerated what he can deliver as, largely, a team of one.

The centerpiece of what PWL is building is a planning checklist: over a hundred individual planning items spanning all six areas of a comprehensive financial plan. Each item accumulates notes as an advisor works on it. When it is time to produce a client deliverable, all of those notes, along with the client's goals, financial situation, and household details, are fed into an LLM running on Microsoft Azure. The model generates a one to two page summary of where the client stands and what they need to focus on.

Clients are not looking for a hundred-page document, Braden explained. They want to know if they are on track, and if not, what needs to change. The AI summary does that pre-population work for the advisor, who then edits it and adds their own context before it reaches the client. The human relationship stays at the center. The AI handles the consistency and the heavy lifting.

Why They Built Their Own Tools

The reason PWL built its own AI meeting note tool rather than buying one of the many available products comes down to one thing: context.

Years ago, before AI was a significant factor, PWL committed to building a data lake: a single unified store of client data flowing from their CRM, their planning software, their portfolio management systems, and their onboarding tools. Most firms their size still operate those systems independently, copying client information manually between platforms.

Because that infrastructure already existed, Braden argued, it made no sense to adopt an off-the-shelf meeting note tool that would only have access to what was said in a single meeting. The point of the meeting note tool is not just to transcribe the call. It is to surface insights in the context of everything the firm already knows about the client: their goals, their full financial picture, their household structure, their planning history.

Building their own tool means the AI has all of that context. Buying a third-party tool would mean the AI only has a slice of it.

What Financial Planning Looks Like in 2031

Braden's longer-term vision is to encode the thinking of the best financial planners in the country into an AI platform, creating what he calls a brain of financial planning. The firm's advisors are contributing their expertise to a shared system that gets better as more knowledge is added.

He is direct about what this could eventually mean: AI-powered financial planning advice that reaches people who cannot currently afford, or do not yet have access to, a full-service wealth management relationship. The quality of advice would scale beyond the firm's existing client base.

Watch the full conversation with Braden Warwick on The AI Report podcast.

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