Across the banking sector, AI is emerging as both a transformative tool and a workforce disruptor, reshaping how institutions operate and interact with clients. Citigroup’s Citi Wealth division has rolled out Advisor Insights and AskWealth, AI platforms designed to give advisors rapid access to market insights, portfolio data, and client-specific information. Piloted with Citigold and Citi Private Client teams, these tools streamline workflows, save staff time, and allow for more informed, high-touch client interactions.
Similarly, BNP Paribas highlights that while AI excels at rapid data processing and automating routine tasks, it cannot replace the human judgment, trust, and empathy essential for personalized financial advice. The French bank advocates a hybrid human-AI model, where efficiency and automation are balanced with personal understanding, emotional intelligence, and relationship management.
At the same time, AI’s adoption is prompting broader workforce considerations. Juniper Research, commissioned by UK fintech Zopa, estimates that generative AI could displace up to 27,000 banking jobs in the UK by 2030, even as it promises to save 187 million labor hours. In response, Zopa has launched Jobs 2030, a five-year reskilling campaign aiming to train 100,000 bank staff in AI disciplines, including coding and generative AI skills.
Taken together, these stories illustrate a sector in flux: AI offers unprecedented capabilities to enhance productivity, client experience, and insight generation, but banks must simultaneously invest in human-AI collaboration and workforce reskilling to ensure technology drives value without eroding trust or opportunity for staff. The convergence of AI tools, hybrid advisory models, and targeted upskilling underscores a critical theme: the future of banking hinges on pairing technological innovation with human expertise.
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Citigroup harnesses AI for wealth management
Citi Wealth has launched AI platforms Advisor Insights and AskWealth to enhance engagement, deliver insights, streamline workflows, and expand its wealth management services globally.
In sum – what to know:
Advisor Insights – tailored dashboard providing market updates, portfolio alerts, and in-house insights; piloted with Citigold services, expanding in late 2025.
AskWealth – generative AI assistant enabling staff to quickly access market and client portfolio information; now live globally after initial rollout in Asia.
Banking impact – tools save staff time, improve customer experiences, and strengthen the firm’s tech capabilities – to drive deeper client connections.
Citi Wealth, the wealth management arm of US banking firm Citigroup, has introduced two new AI platforms to drive deeper engagements and better insights with clients. The two solutions, called Advisor Insights and AskWealth, will help its bankers and advisors to make “faster and deeper connections” with its clients.
The first, Advisor Insights, is presented as a “tailored dashboard” with “timely messages about market turns, portfolios, and current events”. The idea is to avail client-facing staff with “useful content and alerts”, tapping into its Chief Investment Office, its strategic centre for investment guidance across its wealth management platforms.
Advisor Insights is currently in pilot with advisors in the Citigold and Citi Private Client North America business. Usage will be expanded to North America Citi Private Bankers and international colleagues in Q4 2025 and Q1 2026. AskWealth is now available to Citi Wealth colleagues around the globe following a successful launch in Asia.
It is in pilot at its premium-level wealth management services Citigold and Citigold Private Client (Citi Private Bankers in North America), pitched to affluent and high net-worth (HNW) individuals. It will expand to its ultra-high net-worth (UHNW) service, Citi Private Bankers, in North America and international markets in late 2025 and early 2026.
The second, AskWealth, is a conversational generative AI assistant, geared to help staff find answers and insights. It is already live globally following an initial rollout in Asia. It allows service teams to access rapid-fire answers across its data repositories – ranging from market insights to client-specific portfolio data.
Joe Bonanno, head of data, analytics and innovation, said: “These platforms are pivotal steps forward in the expansion of Citi Wealth’s AI, data and technological capabilities. They will save hours of time for our advisors, bankers, and service teams while reinforcing the personal and high-touch experience that is a tradition at our firm.”
Andy Sieg, head of wealth, said: “These AI-powered tools are gamechangers for Citi Wealth. They give advisors sharper insights, streamline how we work, and open new possibilities for serving clients with speed and precision. We’re excited about the impact AI will have on our clients and colleagues alike as we continue to lead the industry into the future.”
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BNP Paribas touts hybrid human-machine AI model
France-based BNP Paribas says AI excels at rapid data analysis, but banking requires human trust and empathy. A hybrid model combining AI efficiency with human understanding – such as it is pursuing, it says – ensures meaningful and personalized financial advice.
Computer brain – AI is good at processing lots of data quickly, says BNP Paribas, but it cannot replace human judgment in banking decisions.
Human touch – trust and empathy are essential for personalised financial advice, particularly in life-impacting investments decisions.
Hybrid model – the bank advocates a hybrid model, combining automation for efficiency with human interaction for context-sensitive understanding.
Artificial intelligence (AI) is great, says France-based BNP Paribas, the second largest bank in Europe; it is brilliant at sifting masses of data for rapid answers. But in the highly emotive and highly personal world of banking, it needs a human touch if all of its magic and tricks are to be made relevant and valuable. Because borrowing and saving and investing, and all the rest of it, is based on a service relationship, between a bank and a client, which is based on trust. And trust is earned – in the minutiae of human conversation and human understanding, and then in advice.
This is the takeaway from a new blog post by Renaud Dumora, deputy chief operating officer of BNP Paribas. AI is creeping into all aspects of banking,he says – to the point it is even redefining the fundamentals of customer relations. He writes: “We are just starting out. AI’s influence is already evident in the way we code, serve customers, work and communicate, although it is not yet widespread.” But for it to go further and deeper in the banking sector, it must be properly harnessed to the essential human interactions at the heart of banking,
“Technology cannot fully replace humans, but the two can complement each other in a highly beneficial way,” says the blog post. “Provided that an ethical framework is established and a fundamental principle is cultivated: trust.”
The blog includes an anecdote about how smartphones – and everywhere-broadband and -applications – have changed the consumers’ expectations. People want information instantly, it says – including responses from insurance companies when issues arise, says the example. “This is typically a situation where AI can really make a difference.” Quick informed financial decisions – at your fingertips. The article goes on: “Thanks to automated diagnostics and recognition of common issues, the response time can be less than five seconds.”
It goes on: “The efficiency is remarkable; but is this enough to justify AI’s widespread application in various fields of finance?” And then explains: “While AI is excellent at handling emergencies, it soon reaches its limits when it comes to decisions with strong patrimonial or emotional impacts, such as retirement planning or investing in a family project. Investing is not just a financial transaction. It is a decision for a life project. Investing is a forward-looking act for individuals and, sometimes, their families. It is not just a financial transaction. It is a decision for a life project”
Dumora, also deputy chief operating officer for the company’s IPS division, says an “environment of trust” for some kind of “human-AI hybridisation” in banking should be built on three principles: data security, so sensitive information is protected against intrusion or breach; transparent decisions, so actions can be explained; and emotional understanding, which incorporates some conscious version of context.
He says: “There is a balance to be struck between the complexity of the models, which are increasingly holistic, precise and sophisticated, and the clarity of the explanations – in other words, the educational approach we can provide. Devoid of any consciousness, an algorithm fails to grasp the nuances of personal and cultural contexts and situations where questions are as much about emotion as reason. Real trust comes from the right combination of artificial and human intelligence.”
Apparently, according to the blog post, BNP Paribas has opted for a hybrid model – “in an era where interfaces sometimes replace human contact”. Dumora remarks: “Our automated processes must incorporate safeguards: customers must be able to speak to a real person at any time if they wish. We must maintain this connection. The real challenge is not to make AI increasingly powerful, but rather to find a balance with humans to preserve what machines cannot simulate: attention, understanding and relationships.”
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UK banks‘ £1.8bn AI spend could cost of 27,000 jobs
Up to 27,000 UK banking jobs may be displaced by generative AI, according to Juniper Research. UK fin-tech Zopa Bank has launched a five-year bid to reskill 100,000 bank staff, offering AI training, coding, and support tools.
In sum – what to know:
Job losses – in total, AI could cost the UK banking sector 27,000 jobs as UK banks look to invest £1.8bn by 2030
Work hours – but AI could save 187m back-office labour hours, creating cost savings equal to total investment.
Skills scheme – fin-tech firm Zopa has a five-year campaign to reskill 100,000 bank staff in AI disciplines.
Up to 27,000 banking workers in the UK could face displacement as generative AI reshapes the financial sector, according to a new study by Juniper Research, commissioned by UK financial technology company Zopa Bank. UK banks are projected to invest £1.8 billion in generative AI by 2030, the report suggests. They are targeting productivity gains, cost reductions, and improved customer experience.
Juniper Research estimates that AI deployments could save 187 million labour hours, with 82 percent from back-office and compliance functions, generating cost savings equivalent to the total investment.
In a cover note for the research report, Peter Donlon, chief technology officer at Zopa Bank, said: “Generative AI is no longer a distant concept – it is here, and it is already reshaping jobs, industries, and entire economies at remarkable speed. In the years ahead, few aspects of our professional and personal lives will remain untouched by its influence. Nowhere is this shift more consequential than in financial services.
“The banking sector in particular, long known for its resilience and ability to adapt, is now at the forefront of the gen AI revolution. As the industry embraces this new wave of innovation, understanding its full implications has never been more important… The opportunity is tangible… [and] ushers in a once-in-a-generation opportunity to re-skill and reimagine the workforce that powers our financial system.”
Zopa Bank has unveiled a five-year campaign, Jobs 2030, to reskill 100,000 UK banking staff in AI. The scheme initially targets fin-tech professionals such as engineers, analysts, and operations leads. Early training modules will be piloted internally with Zopa employees before wider rollout. The campaign will expand to include a generative AI engineering programme for advanced technical upskilling and the launch of a coding academy.
It has also rolled out 1,000 enterprise-grade generative AI licenses, giving all employees access to tools like ChatGPT, alongside OpenAI-led training on prompt writing, engineering best practices, and building custom GPTs.
Donlon said: “This evolution also raises valid and urgent questions – about jobs displacement, the future of human-machine collaboration, and how the sector can ensure that the benefits of AI are inclusive, ethical, and sustainable.”
