The original version of this article first appeared in the World Economic Forum.

Artificial intelligence (AI) is reshaping every industry, including financial services, which is currently seeing the first wave of AI financial planners and digital advisers. And while this could make high-quality financial guidance as accessible as a Google search, if AI learns from the wrong playbook, it will only exacerbate the same old problems that already plague financial services such as encouraging unnecessary trading and spending, and frequent churning of investments.

The real issue is not the technology, but the incentives that drive it. If today’s models reward transactions over outcomes, AI will only help financial companies to sell faster, not to serve better. If incentives are aligned to long-term financial wellbeing, however, AI could truly democratise wealth.

That is both the opportunity and the responsibility for the financial services industry in the age of AI.

The World Economic Forum’s report on the future of financial services and responsible AI echoes this tension. It stresses the need to balance innovation and investment with the protection of public and private interests, while remaining alert to risks such as widening the global wealth gap.

Put simply, AI could be one of the most powerful tools for financial inclusion, but only if AI-driven financial services platforms are built with the right intent.

AI mirrors intention

AI amplifies whatever system it is trained on. If an AI-powered financial platform is built to encourage action, a user will likely be encouraged to click more, trade more and spend more. But if it is designed around outcomes, the platform could help more people stay invested, disciplined and focused on achieving their goals, which is what good financial advice does best.

That difference sounds simple, but it is fundamental. Financial platforms already influence how individuals save and invest. AI now extends that influence by learning habits, recognising biases and anticipating emotional triggers, and using that information to tailor recommendations with precision. Used responsibly, AI can empower. Used poorly, it can manipulate.

AI can simultaneously broaden financial access while deepening divides, depending entirely on how it is deployed. When optimised for activity instead of outcomes, engagement-driven models risk accelerating wealth erosion, especially in markets where financial literacy remains uneven.

When automation meets human bias

Every investor knows how hard it is to stay rational when markets move. Behavioural biases such as fear, overconfidence and impatience shape decisions far more than spreadsheets do. Now imagine those biases amplified by an intelligent system that knows exactly when and how to trigger a reaction.

This reality has already come about, with gamified trading and social media-influenced investing leading to excessive risk-taking. In an AI-enabled world, those feedback loops could grow exponentially.

The danger is not automation itself, but misaligned automation that sees machines learning to maximise engagement instead of wellbeing. When that happens, investors lose twice: first through poor timing and again through the compounding effect of costs and mistakes.

And so, regulation is vital. But disclosure-based financial safeguards were not designed for adaptive algorithms. By the time policies for the financial services industry are written, AI technology will have already evolved. The real safeguard lies in business-model design, which aligns what’s good for the client with what’s good for the financial provider.

If financial institutions are rewarded for long-term outcomes rather than transactions, AI will naturally learn to serve that mission. The industry must pivot from more data to better intent.

What alignment looks like in practice

This pivot must start by shifting how success is measured from activity to progress. There are three principles that can guide that change:

• Outcome-aligned business models: Success should be defined by whether clients are better off over time, not by how often they transact. This shifts AI’s optimisation target from activity to outcomes.
• Transparency and explainability: Algorithms that guide real financial decisions must be auditable and understandable. If people cannot see why or understand how a recommendation was made, trust will always be fragile.
• Shared accountability: The industry needs collaborative standards, not to stifle innovation, but to create a shared foundation of trust as AI adoption accelerates. AI governance and financial inclusion will provide a solid foundation for this.

These principles are not new, but AI makes them urgent.

Combining the best of machines and people

AI will never fully replace human advice, but it will help redefine its role. Machines excel at scale, pattern recognition, processing complexity and precision. Humans excel at empathy, judgement and behavioural coaching. The intersection of the two is where the real AI opportunity lies for financial services.

​​An AI-enabled advisory model could make personalised guidance accessible to those who may have lacked access to it in the past, including younger savers, women, lower-income households and those priced out of traditional advice. Meanwhile, human advisors could focus on what technology cannot replicate, such as helping people navigate uncertainty and stay the course with their finances.

AI can help close persistent gaps in financial access by lowering the cost of advice, reducing barriers to entry and tailoring guidance to diverse life stages and cultural contexts. Imagine quality financial guidance available to anyone with a smartphone, with planning for education or retirement that feels intuitive rather than intimidating.

An AI-based future depends on intent

As an industry, financial services has spent decades improving access to financial products. AI provides a chance to improve access to advice in order to offer guidance that’s relevant, transparent and aligned.

But technology alone will not bridge the trust gap. If the financial services industry designs systems that profit when clients succeed, AI will naturally amplify that success. And so, the next chapter of financial innovation should not be measured by how fast we deploy AI, but by how responsibly we build it.

Democratising wealth has always been about trust, access and alignment, and ensuring the system serves people, not the other way around. AI offers a rare chance to start anew. Building with intention will make financial progress possible for everyone.