For most people, there has always been a clear structure when it comes to managing money. You either make decisions yourself, taking full responsibility for the outcome, or you pay for financial advice, where a professional is expected to guide you and can be held accountable if things go wrong. That distinction has long underpinned how the financial system operates, shaping both consumer expectations and regulatory frameworks.
That clarity is beginning to erode. A new category is emerging, one that does not fit neatly into either side of that traditional divide. Banks, platforms, and technology firms are developing tools that do more than simply present information. They guide users through decisions, suggest possible actions, and shape outcomes in subtle but meaningful ways. Yet, despite this influence, they are not formally classified as providing financial advice.
Recent developments in the UK illustrate how quickly this shift is taking place. Lloyds Banking Group has begun piloting an AI-powered investment tool through Scottish Widows. The system is designed to help users navigate investment choices, but it is deliberately framed as “guidance” rather than advice. At the same time, the Financial Conduct Authority is allowing firms to test similar technologies in live environments through its AI testing programme, rather than imposing immediate rules.
These developments point to a broader shift in how financial decisions are being supported and, crucially, how responsibility is being defined. If an algorithm influences the financial decisions you make, but is not technically advising you, the question of accountability becomes harder to answer.
The rise of something in between
To understand what is changing, it is useful to revisit how financial decision-making has traditionally been structured. Financial advice has always been clearly defined and tightly regulated. When an adviser provides a recommendation based on an individual’s circumstances, they are required to ensure that advice is suitable, documented, and compliant with regulatory standards. If the advice proves inappropriate or harmful, there are established mechanisms through which consumers can seek recourse.
At the other end of the spectrum lies self-directed investing. In this case, individuals make their own decisions, relying on publicly available information or personal judgement. The responsibility for those decisions rests entirely with them.
What is emerging now sits between these two models. AI-driven tools are increasingly designed to guide users through financial choices without crossing the threshold into formal advice. They may suggest asset allocations, highlight commonly chosen strategies among similar users, or present a curated set of options based on basic inputs. These features create an experience that feels structured and supportive, reducing the uncertainty that often accompanies financial decision-making.
However, these tools avoid making explicit, personalised recommendations that would bring them within the scope of regulated advice. The investment tool being piloted by Lloyds, for example, has been described as functioning like a “satnav for investments”, helping users navigate options without making decisions for them.
This distinction reflects a conscious effort by firms to operate within a space that allows them to influence decisions while limiting regulatory obligations. The result is the creation of a new category that did not previously exist in such a defined form. It is neither fully independent decision-making nor regulated advice, but a hybrid model in which guidance is provided without the formal responsibilities that traditionally accompany it.
The Regulatory Grey Zone
The emergence of this hybrid category is closely tied to how financial regulation is structured. In the UK, the distinction between advice and guidance determines both the level of oversight and the protections available to consumers. Advice involves personalised recommendations and is subject to strict regulatory requirements. Guidance is broader and carries fewer obligations.
This boundary is now being tested.
The Financial Conduct Authority has been actively reviewing how artificial intelligence could reshape retail financial services, including its impact on competition, market structure, and consumer outcomes. At the same time, it has signalled that it does not intend to introduce entirely new AI-specific rules, instead relying on existing frameworks and principles-based regulation.
Alongside this, the regulator has introduced a new category known as “targeted support”, designed to bridge the gap between full financial advice and generic guidance. This framework aims to help consumers who are currently underserved, with an estimated 23 million people in the UK lacking access to affordable financial advice.
These developments highlight a deeper issue. Accountability does not scale as easily as technology. When a human adviser provides advice, responsibility is clearly defined. When an AI tool influences decisions across a large number of users, the line becomes less obvious. Firms can argue that they are not providing advice, while consumers remain responsible for their own choices.
The challenge becomes more pronounced at scale. AI systems can interact with thousands or even millions of users simultaneously, meaning that small design choices in how options are presented can have widespread effects. Regulatory frameworks, which were built around individual relationships and clearly defined actions, are now having to adapt to systems that operate very differently.
The Behavioural Shift Already Underway
While regulatory frameworks continue to evolve, changes in consumer behaviour are already becoming evident. AI tools are lowering the barrier to engaging with financial decisions, offering users faster and more accessible ways to navigate complex choices. For many, this provides an entry point into investing or financial planning that might otherwise feel out of reach.
There are clear benefits to this shift. Greater accessibility can encourage broader participation in financial markets and reduce reliance on expensive or hard-to-access advisory services. This aligns with wider policy efforts to close the so-called “advice gap” and improve financial inclusion.
However, the way decisions are made is also changing. When users are presented with suggested options or guided pathways, their choices are shaped by how those options are framed. Even if the final decision rests with the individual, the structure of the system influences the outcome.
There is also the question of confidence. Tools that appear personalised and data-driven can create a sense of precision that may not always reflect reality. Many systems rely on generalised models or limited inputs, meaning they may not fully capture the complexity of an individual’s financial situation. Yet users may interpret their outputs as authoritative.
Regulators have already raised concerns about transparency and the potential for bias in AI-driven decision-making. A UK parliamentary committee has warned that the increasing use of AI in financial services could expose consumers to risks including mis-selling, opaque decision processes, and insufficient accountability.
Another important consideration is incentives. AI systems are designed with specific objectives, which may include engagement, efficiency, or commercial outcomes. The way information is presented and the options that are prioritised can reflect these objectives. This does not necessarily lead to poor outcomes, but it does mean that guidance is shaped by underlying design choices rather than being entirely neutral.
Taken together, these developments point to a broader shift in how individuals interact with their finances. Decision-making is becoming more guided, more structured, and increasingly influenced by systems that operate at scale. At the same time, the point at which responsibility lies is becoming less clearly defined.
Where This Leaves You
The growing role of AI in financial decision-making does not represent a simple replacement of human advice with automated systems. Instead, it introduces a more complex landscape in which different forms of guidance coexist, each with its own implications for responsibility and risk.
AI-driven tools are likely to remain a central part of this landscape. They offer clear advantages in terms of accessibility and efficiency, and their use is expected to expand as technology continues to develop. For many individuals, they will provide a valuable way to engage with financial decisions that might otherwise feel inaccessible.
At the same time, they introduce a degree of ambiguity that did not previously exist. The traditional categories that defined financial decision-making are becoming less distinct, and the protections associated with those categories are not always immediately clear.
For individuals, this means paying closer attention to how these tools are positioned and what they actually provide. Understanding whether a system is offering general guidance or regulated advice is an important part of assessing the level of protection available. It also requires recognising the limits of what these tools can deliver, particularly when they rely on simplified models or incomplete information.
The broader issue is that the system is evolving more quickly than the rules that govern it. As AI continues to shape how financial decisions are made, the question of responsibility will become increasingly important. Guidance may become more sophisticated and more widely available, but without clear definitions, the allocation of responsibility remains uncertain.
AI will play a growing role in how individuals manage their money. That trajectory is already clear. What remains unresolved is how accountability will be defined in a system where influence is widespread, but responsibility is less clearly assigned.
💼 Unpacked
Financial advice vs financial guidance
Financial advice is a personalised recommendation based on your specific circumstances and is regulated by the Financial Conduct Authority, with accountability if it’s unsuitable. Financial guidance is general information or suggestions to help decisions, but without personalisation or the same legal protections.
Regulatory sandbox
A regulatory sandbox is a controlled testing environment run by the Financial Conduct Authority where firms can trial new financial products, like AI tools, with real users under supervision. It allows innovation while limiting risk before full regulation is applied.
Targeted support
Targeted support is a framework introduced by the Financial Conduct Authority that allows firms to provide more tailored help to groups of consumers without giving full personalised advice. It sits between generic guidance and regulated financial advice.
Advice gap
The advice gap refers to the large number of people who do not receive financial advice, often due to high costs or limited access. Regulators and firms, including the Financial Conduct Authority, see this as a key issue AI tools could help address.
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Sources
1. Lloyds pilots AI investment guidance tool as UK regulator studies impact
Source: Reuters
Link: Read article
2. FCA announces second cohort for AI Live Testing
Source: Financial Conduct Authority
Link: Read article
3. UK regulator kicks off review on impact of AI on retail finance
Source: Reuters
Link: Read article
4. AI and the FCA: our approach
Source: Financial Conduct Authority
Link: Read article
5. PS25/22: Supporting consumers’ pensions and investment decisions (targeted support rules)
Source: Financial Conduct Authority
Link: Read article
6. Britain needs AI stress tests for financial services, lawmakers say
Source: Reuters
Link: Read article
