As businesses try to make sense of AI, it can feel like stepping into a brave new world of bold predictions and sweeping claims. Yet history shows that major technological shifts rarely unfold the way early commentators expect.
In 2015, UK financial advice firms faced a similar moment. Talk of robo-advice dominated headlines, with fears that robots would replace advisers as digital first platforms grew, regulation tightened and clients questioned why financial services still felt so analogue. In reality, the robo-advice era became a live experiment in how technology, human judgement and regulation interact.
A decade on, leaders are hearing the same claims about AI and large language models. Some even warn of an AI bubble, echoing the dot com era when expectations ran ahead of reality.
That’s why the robo-advice journey and the dot com boom are such valuable case studies today. They reveal how hype distorts decisions, how markets eventually settle on hybrid human and digital models and why those lessons matter for anyone building a human plus AI approach in financial services, professional services or customer contact environments like Moneypenny.
In the mid 2010s, robo-advice became shorthand for a much bigger anxiety in UK financial services. The narrative went something like this:
There were real forces behind that story.
Post RDR and MiFID II, firms were under intense pressure to justify fees, evidence value and prove suitability. Digital advice tools promised cleaner audit trails, consistent fact finding and more transparent charging structures. For many boards, that felt safer than relying on dispersed manual processes across large adviser networks.
Operating models built around face to face advice, branch networks and lengthy suitability reports were expensive. Automated asset allocation on a centralised platform looked like a neat way to protect margins and tap new segments without expanding adviser headcount.
Consumers were streaming entertainment, ordering taxis and managing their banking on their phones. A paper heavy, appointment based advice experience felt increasingly out of step. Robo advisers promised simple interfaces, low entry points and always on access.
Against that backdrop, it is no surprise that “robots will replace advisers” became such a powerful meme. As so often with new technology though, the reality turned out to be more nuanced.
Robo advisers found a clear niche, especially for:
The FCA’s work on automated investment services recognised that these models could support competition and help address the advice gap, as long as firms met the same standards on suitability, disclosure and consumer protection as traditional advice firms.
The bigger story was what robo-advice did not do.
When markets were volatile, clients still leaned on advisers for reassurance, context and behavioural coaching. Research during the pandemic showed that human advisers were critical in helping clients stay invested, even as digital tools and portals became more central to day to day interactions.
Many incumbents built or bought their own digital propositions. Over time, the line between “robo” and “traditional” blurred. Clients were no longer choosing between people or platforms, but between firms that could orchestrate both well and those that could not.
The elements that could be automated were exactly the elements that became commoditised: asset allocation, rebalancing and reporting. Differentiation moved to financial planning, coaching, complex structuring, cross border issues, intergenerational wealth and business owner advice.
Studies on hybrid models found investors saw clear benefits in combining both. Digital tools delivered convenience and cost efficiency, while human advisers were valued for holistic planning, accountability and emotional support.
In other words, robo-advice did not replace people. It reshaped the boundary between what technology does best and what humans do best.
Looking back, the pattern is familiar and not unique to financial services.
If this sounds familiar beyond financial services, it should. The dot com bubble followed a similar arc: huge investment and inflated expectations, followed by a correction, then a quieter phase where the real, durable business models emerged. The fact there was a bubble did not mean the underlying technology was a mirage. It meant valuations and expectations ran ahead of what customers, regulation and infrastructure were ready to support.
Whether or not commentators turn out to be right about an “AI bubble”, some of today’s valuations and AI start ups will turn out to be overhyped. The real question for senior leaders is which human plus digital models will still be creating value for clients long after this phase of the AI hype cycle has cooled.
Robo-advice followed exactly this script. It is now clear that the durable model is a hybrid one, where algorithms handle scalable, rules based processes and humans handle judgement, ambiguity, emotion and relationship.
That is the key lesson for leaders reviewing AI in financial services, AI in customer experience or AI for contact centres today. The strategic question is rarely “will this replace us” but “how do we redesign roles, journeys and economics around a blended human plus digital model”.
Generative AI has revived that old sense of existential threat across many B2B sectors, including financial services, legal, professional services, property and customer contact.
The rhetoric is easy to recognise:
In practice, the parallels are striking.
In advice led sectors, AI is already handling first draft commentary, client communications, data heavy analysis and triage of client queries into human and digital paths.
Contact centres and switchboards are seeing similar patterns. AI phone answering, intelligent routing and virtual reception services can deal with common queries and FAQs, while human receptionists focus on complex or sensitive conversations that build relationships.
AI is not chairing annual review meetings, navigating complex family dynamics or signing off on suitability assessments. It is not handling the delicate conversations that a Moneypenny receptionist manages for a law firm or property business after a difficult client experience. The most realistic future is one where advisers and AI tools work together.
It is easy to read commentary about an AI bubble and draw the wrong conclusion. The dot com bubble did burst. Capital flowed out of overhyped businesses and many experiments failed. But the core idea that the internet would transform how we buy, sell and communicate turned out to be absolutely correct.
In some ways, AI may follow a similar pattern: plenty of noise, some overhyped bets, and a set of very real, durable winners that reshape how we work. There are also important differences. The early internet’s bottleneck was demand. AI’s main constraint is energy and compute capacity, which is why many see this moment less as a classic software bubble and more as a deep infrastructure transition.
Some business models and AI use cases will not survive contact with regulation, customer expectations or economics. Others, especially those that blend AI with human expertise in a disciplined way, will quietly become the new normal, just as online banking and ecommerce did after the dot com crash.
For leaders, the risk is not whether commentators turn out to be right about an AI bubble. The bigger risk is sitting out the learning phase and discovering that competitors have already built practical, scalable human plus AI models by the time the hype has settled.
In highly regulated markets, trust is built through accountability, transparency and relationship. Clients want to know who ultimately stands behind the advice or decision, even if technology did much of the analysis.
Regulators reinforce this. Guidance on automated and hybrid advice models makes it clear that regulatory responsibility sits with the firm, not the algorithm, and that consumer protection expectations stay the same regardless of channel.
Just as robo-advice made it possible to serve previously unprofitable segments, AI has the potential to shorten cycle times, reduce error rates and free up senior people to spend more time where they add the most value.
In customer communication, that might mean AI handling initial data capture, identification and intent analysis, while a Moneypenny PA or call handler picks up the conversation with full context. The organisations moving fastest are not ripping out human expertise. They are redesigning how that expertise is deployed.
If you own or run a business in the UK, or you are responsible for strategy, client experience or operational performance, there are some clear lessons from robo-advice and the dot com bubble that apply directly to AI and automation today.
The financial advice winners were not the firms that simply launched a portal. They reimagined end to end client journeys and asked:
You can apply the same lens to AI and LLMs in an advice business, legal practice, property firm or contact centre. Map journeys, identify pain points and design a blended experience where AI solves specific problems rather than becoming a bolt on feature. AI will sit closer to your core infrastructure than to a single app, so treating it as just another software add on is exactly the kind of misread that has fuelled so much bubble talk.
In regulated sectors there will always be points where human sign off and judgement need to remain central, such as:
Codify these boundaries early and communicate them clearly. The goal is not to minimise human involvement, but to make it purposeful and visible in your operating model.
Advisers who embraced robo tools found they could spend more time in meaningful client conversations. In the same way, your teams can use AI to:
That needs investment in skills and confidence, not just licences. Leaders should offer training that demystifies AI, encourage controlled experimentation and recognise people who improve outcomes by working with technology. For a partner like Moneypenny, that might mean training receptionists and PAs to work alongside AI call answering and triage tools so they can deliver a more personal, more informed human response.
The early robo-advice market struggled where disclosure, clarity and suitability were weak. Governance frameworks matured as lessons were learned.
For AI, firms will need clear principles around data quality, model oversight, explainability, documentation of AI influenced decisions and fair treatment of customers when algorithms are involved. Testing AI assistants and virtual agents thoroughly before they go live is essential.
Done well, governance is not a brake on innovation. It gives boards, regulators and partners confidence to scale promising use cases, whether in financial advice, claims handling or outsourced switchboard services.
If your people and clients only hear AI framed as a cost cutting or headcount reduction tool, they will resist it. Instead, frame your strategy around:
Share concrete examples where the blend is already working. That might be a client who gets quicker turnaround times because AI pre screens documents, followed by a more thoughtful conversation with your expert. Or a customer who gets straight through to the right Moneypenny PA because AI routing has already understood intent and priority.
Although this is a financial services case study, its lessons apply across a wide range of sectors, from professional services and property through to consumer facing businesses. Whether you run a legal practice, a property group, a professional services firm, a healthcare clinic or a busy consumer service business, you face the same core questions:
You also face similar pressures: regulation, cost, rising client expectations and talent constraints. In client facing operations, that plays out in choices about AI chatbots, AI receptionists, virtual agents and outsourced communication partners. Do you treat AI as a way to replace human contact, or as a way to route, augment and support people so they can deliver a more human experience where it matters most?
The organisations that will thrive are the ones that use AI to strengthen, not hollow out, their value proposition, invest in people as much as platforms and are brave enough to redesign journeys for a hybrid brave new world.
The advice story taught financial services something vital. Technology is rarely the villain and almost never the whole hero. The real value lies in how humans and technology are combined.
Just as the burst of the dot com bubble did not mean the end of the internet, any cooling of speculative enthusiasm around AI will not mean the end of AI. It will expose which organisations built shallow, hype driven projects and which ones invested in thoughtful human plus AI models that stand up to real world use.
For senior leaders, the invitation now is to:
The robo-advice experience suggests that new technology rarely replaces human expertise entirely. Instead, it reshapes roles. In customer communication, AI is well suited to handling routine queries, data capture and routing. Human receptionists and PAs remain essential for complex, sensitive or high value conversations where empathy, judgement and relationship matter most. The most effective model is a blend where AI takes care of repeatable tasks and your people focus on the interactions that need a human touch.
Used well, AI can make your service feel more personal, not less. For example, AI can gather key details, understand intent and surface relevant information before a call or chat reaches a person. That means your receptionist, adviser or case handler can pick up the conversation already knowing who they are speaking to and what they need. Clients experience shorter wait times, fewer hand offs and more joined up conversations, while still benefiting from human warmth and reassurance when it counts.
No. The same human plus AI principles apply whether you run a national brand, a professional services firm or a growing consumer service business. Larger and regulated organisations often feel the pressure first, but smaller businesses face similar challenges around capacity, rising client expectations and the need to make every interaction count. A hybrid model allows you to offer quick, consistent responses at scale while still giving clients access to named people who understand their situation.
Moneypenny’s AI Voice Agent is designed to sit alongside real people, not replace them. It can answer common questions, capture key details, route calls and provide instant responses out of hours or during busy periods. When a conversation is complex, sensitive or high value, the AI Voice Agent can hand over to a Moneypenny receptionist or to your in house team with full context. That way, AI handles volume and availability, while humans stay focused on the moments where their judgement and empathy make the biggest difference.
At Moneypenny, we already help thousands of organisations build exactly this kind of hybrid model to elevate customer experience. Our Telephone Answering Services, Outsourced Switchboard and AI Voice Agent support combine real people with AI powered tools so every call, message and enquiry is handled as if we were based inside your own team.
For many businesses, the sweet spot is a blend of an AI voice agent for instant response, backed up by highly trained Moneypenny receptionists for complex, high value or sensitive conversations. Routine queries are handled quickly and consistently, while your clients still get human warmth and judgement when it matters most.
Whether you need a fully outsourced telephone answering service, overflow cover for busy periods, a virtual receptionist for out of hours calls, or an AI receptionist with seamless hand off to real people, we can help you design a human plus AI approach that fits your business needs and your longer term growth plans.
Whether you are running a professional services firm, a national brand or a growing consumer service business, the same human plus AI principles apply.
If the advice story and the dot com bubble show anything, it is that the future rarely belongs to the loudest predictions. It belongs to the organisations that quietly, deliberately and thoughtfully design a world where humans and technology work together seamlessly.
That is the opportunity in front of you now: to build a human plus AI model that strengthens your proposition, protects your people and delivers enhanced experiences for every client who calls, clicks or chats with your business. Whether you are curious about the first steps or ready to explore what this could mean for your organisation, we are here to help you get started. Discover how our AI Voice Agent blended with our expert Telephone Answering Service could transform your customer experience.
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