The Advice Industry Is About to Split Apart

Every major technology wave unbundles something.

• The PC unbundled mainframes.
• The internet unbundled retail and media.
• Smartphones unbundled entire business models into apps.

Now, generative AI is beginning to unbundle financial advice. Not by instantly replacing human advisors, but by peeling apart dozens of hidden services that have been packaged together as “advice” for decades.

For high-income professionals — especially doctors, engineers, and founders in high-cost states like California — this shift won’t just change how you get advice. It will change what “advice” even means.

Financial Advice Today Is a Bundle Most People Don’t Recognize

When most people think of a financial advisor, they picture a single role: someone who helps them invest, plan, and make smart money decisions.

In reality, financial planning is a bundle of 15+ different jobs:

• Investment management and portfolio construction
• Tax planning and tax-aware withdrawal strategies
• Cash-flow planning and budgeting
• Student loan strategy and debt paydown plans
• Equity compensation planning (RSUs, ISOs, NSOs, ESPPs)
• Retirement projections and income planning
• Insurance reviews and risk management
• Estate and legacy coordination with attorneys
• Exit planning for business owners
• Scenario analysis for big life decisions
• Behavioral coaching during market volatility
• Life planning (career changes, sabbaticals, family choices)
• Account transfers, rollovers, and paperwork
• Financial education and plain-language explanations
• Accountability, check-ins, and course correction over time

Most clients don’t see each piece. They see one outcome: “My advisor has my back.”

AI, however, doesn’t care about the bundle. It sees each discrete job: data gathering, modeling, scenario building, reporting, communication, and so on. And that’s exactly where Benedict Evans’ framework becomes important: when a new platform shows up, it tends to find hidden bundles in an industry and break them apart.

What Benedict Evans Sees in This Platform Shift

Benedict Evans is an independent analyst who has spent more than two decades studying how technology platforms (from PCs and the web to mobile and social) change industries, value chains, and business models. In his 2025 presentation “AI eats the world,” he argues that generative AI is another platform shift on the scale of the internet or smartphones: a new layer that will sit underneath everything we do in technology and business.

A few themes from his work matter directly for financial planning:

• Models are converging. The underlying AI models look more and more like commodities. The real advantage will come from product, distribution, UX, and trust.
• AI is an “infinite interns” machine. It doesn’t replace one person with one AI. It gives every knowledge worker the equivalent of a small team of junior analysts.
• Platform shifts unbundle industries. Just as the internet unbundled newspapers and big-box retail, AI will unbundle categories like “search” and “financial advice” into very specific jobs to be done.
• Adoption takes time. Many people have experimented with AI tools, but far fewer use them every day. We’re early in figuring out how this fits into normal life.

Put simply: AI is not a magic replacement for professionals. It’s a new substrate that changes what work looks like, where value is created, and which parts of an industry get automated first.

Why AI Is the Perfect Unbundling Machine for Finance

1. AI Understands Intent, Not Just Tasks

Traditional software is good at following rules: “If income is X and expenses are Y, show a warning.”

Generative AI can go a level deeper. It can interpret:

• What you’re trying to achieve (retire early, change careers, start a business)
• What constraints you face (student loans, Bay Area rent, kids, aging parents)
• How you prioritize (freedom vs. status, flexibility vs. maximum net worth)

Finance is fundamentally about intent. Two people with the same balance sheet can make completely different decisions based on their values and risk tolerance. AI can help surface those differences faster, but it still struggles to answer the deeper questions: “What should I do?” “What will I regret less?”

2. “Infinite Interns” Changes the Scale of Planning

Evans uses a memorable phrase: AI gives you “infinite interns.” Instead of hiring a team of analysts, you suddenly have the ability to:

• Model dozens of retirement scenarios in minutes
• Test different tax strategies side by side
• Summarize a 30-page benefits booklet into a one-page decision guide
• Draft emails, letters, and explanations that would normally eat an advisor’s entire afternoon

For advisors, this means one person can now do the work that previously required a small team. For clients, it means the ceiling on what’s possible in personalized planning is suddenly much higher.

3. The Jevons Paradox: We Won’t Plan Less, We’ll Plan More

Historically, when technology makes something cheaper or easier, we don’t use less of it. We use more. Evans points to the industrial revolution, where steam engines effectively multiplied the productive capacity of entire countries.

Applied to personal finance, as the cost of analysis, projections, and reporting falls toward zero:

• Households will want more scenarios, not fewer.
• Founders will want more what-if cases around exits, dilution, and second acts.
• Doctors and tech employees will want more views of “If I cut back to part-time” or “If I leave California in five years.”

Demand for planning doesn’t shrink. It grows. The limiting factor won’t be the math anymore. It will be who helps you interpret the results and turn them into action.

4. Tasks Will Automate Faster Than Trust

A crucial observation from Evans’ analysis: many people have tried AI tools like ChatGPT, but only a small fraction use them daily. Curiosity is high; embedded trust and habit are low.

Financial decisions live at the intersection of numbers and emotions:

• Fear during bear markets
• Guilt around spending or family expectations
• Stress from volatile income or equity compensation
• Uncertainty about retirement timing or career changes

AI can build a Roth conversion schedule. It can optimize a tax-aware withdrawal strategy. But it cannot sit across from you after a layoff, a diagnosis, or a divorce and say, “Here is the plan. Here is why you’re going to be okay.”

That gap between calculation and confidence is where human advisors remain essential.

The Rise of the Third-Wave Advisor

If we zoom out, we can see three broad eras of personal finance advice:

Wave 1: The Brokers

Stockbrokers and product salespeople who were paid primarily to transact. The focus was on picking investments and selling what was on the shelf.

Wave 2: The Fiduciary Advisors

Registered Investment Advisors and planners who focused on goals-based planning, long-term portfolios, and acting in the client’s best interest. Fees shifted from commissions to planning fees and assets-under-management models.

Wave 3: The AI-Augmented Advisor

The next evolution is not “robot replaces human.” It is: a human advisor who uses AI to handle the heavy lifting of analysis, modeling, and administration, freeing up more time for:

• Deep discovery about what clients actually want from life
• Coaching and behavioral support through big transitions
• Complex, multi-variable decision-making that spans money, family, and career
• Ongoing accountability and course correction as life changes

In this “third wave,” the advisor becomes a decision architect: someone who designs the environment and strategy in which smart financial choices are easier to make and easier to stick with.

What AI Will Unbundle Inside Financial Planning

If we apply the logic of unbundling to the list of advisor jobs, we can roughly group them into three buckets:

Bucket 1: Fully Automatable (0–2 Years)

• Budgeting and spending categorization
• Basic savings rate and retirement age projections
• Automated portfolio rebalancing based on risk targets
• Flagging tax-inefficient accounts or asset locations
• Organizing and summarizing financial documents
• Creating simple financial “snapshots” for clients

Bucket 2: Semi-Automatable (2–5 Years)

• Multi-account tax optimization across taxable, Roth, and pre-tax accounts
• Modeling equity compensation strategies and exit scenarios
• Comparing state tax outcomes for relocation or remote work
• Advanced retirement income strategies (Roth conversions, bracket management)
• Suggesting estate planning structures in collaboration with attorneys
• Continuous monitoring for planning opportunities and risks

Bucket 3: Human-Critical (Indefinite Horizon)

• Prioritizing competing goals when you can’t do everything at once
• Helping couples align when they disagree about money
• Coaching clients through bear markets and scary headlines
• Navigating layoffs, career pivots, burnout, or selling a business
• Translating financial strategy into a life that actually feels good to live
• Standing in your corner when everything feels uncertain

AI will dramatically expand what’s possible in Buckets 1 and 2. But Bucket 3 is where long-term, trust-based advisory relationships will concentrate.

What This Means for High-Income Professionals

If you’re a high earner in California — a physician, tech employee, business owner, or senior leader at a startup — AI will make it easier than ever to:

• Build your own spreadsheets and models
• Ask tools to analyze your spending and investments
• Get rough answers to questions about early retirement, moving states, or going part-time

But you may also find yourself facing:

• More options, not fewer. AI multiplies the number of paths you can see.
• More decision fatigue. Every tool can give you a different “optimal” answer.
• More fear of missing out. As strategies and edge cases become more visible, it’s easy to feel like you’re always behind.

The gap will widen between people who use AI to clarify their path and people who use AI to generate a thousand conflicting scenarios and then freeze.

In that world, an advisor’s job isn’t to hoard information. It’s to:

• Filter noise from signal
• Prioritize the next right move
• Personalize strategy to your life, values, and constraints
• Humanize the process so you feel confident acting on the plan

About Benedict Evans and “AI Eats the World”

Benedict Evans is a well-known technology analyst who has spent much of his career helping companies and investors understand how major platform shifts — such as the rise of smartphones or the move to cloud computing — reshape industries. His work often focuses on asking better strategic questions rather than predicting specific winners.

This article builds on themes from his November 2025 presentation, “AI eats the world”, which examines how generative AI is changing capital expenditure, data center buildout, software development, enterprise automation, and consumer behavior. While the conclusions here are tailored to financial planning and wealth management, many of the core ideas about unbundling, “infinite interns,” and shifting value capture come directly from his analysis of the broader tech landscape.

For readers who want to go deeper into his work, you can find more at his website: ben-evans.com.

Where RYSE Fits in This New Landscape

At RYSE Financial, we don’t see AI as a threat to human advice. We see it as a way to give our clients better analysis, more scenarios, and clearer trade-offs — while doubling down on the parts of the relationship that algorithms can’t touch: trust, judgment, and walking with you through real life.

If you’re a high-income professional who wants a financial plan that takes advantage of new tools without turning your life into a science experiment, we’d love to talk.

Ready to see what an AI-augmented financial plan looks like?

• Schedule an introductory call:  https://calendly.com/rysefinancial/introductory-call
• Learn more about our financial planning approach:  https://www.rysefinancial.com/financial-planning