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The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. For years, banks have known their customer experience needs to catch up to the digital expectations set by tech and retail giants. Now, with AI dominating the boardroom agenda, the temptation is to bolt on yet another tool and call it transformation. But real progress doesnt come from piling on more toolsit comes from using AI to intelligently orchestrate smarter, more connected customer journeys. Recently, Ive spent time with several banking leaders exploring how theyre applying AI across their operations, from servicing and support to fraud detection and lending. What Ive seen confirms a pattern: The most successful organizations arent chasing hype. Theyre focused on orchestration. What AI is really solving for in banking For most consumers, banking is about trust, simplicity, and confidence. They want fast answers, frictionless support, and personalized help when it counts, whether theyre applying for a mortgage, reporting a lost card, or just resetting a password. Too often, those journeys are fragmented. Customers bounce between bots, forms, and phone calls. Agents are left trying to stitch together context. The experience is frustrating for both sides, and every one of those missed moments erodes trust. AI has the potential to fix this. But only if its used in the right way. The real opportunity isnt automation for automations sakeits intelligent orchestration. That means building systems where AI helps guide the customer from start to finish, hands off to a human when it makes sense, and ensures everyone involvedespecially the agenthas the context they need. From automation to orchestration In one conversation, a financial services team showed how they reimagined the mortgage prequalification journey. What stood out wasnt just the AIit was how the experience stayed focused, relevant, and responsive across every interaction. AI agents collected essential details, routed inquiries accurately, and passed full context to human advisors. Customers felt supported. Advisors were prepared. And the whole process moved faster. The shift was clear: not more technology, but better design. AI used not as a standalone fix, but as connective tissue across the customer journey. Its not about replacing peopleits about designing better systems Theres still a lot of fear that AI means fewer jobs. In reality, the best implementations are making people better at their jobs. Human agents become “super agents”equipped with real-time summaries, suggested responses, and full visibility into a customers journey. And this isn’t just about contact centers. Product, compliance, and CX teams are increasingly hands on in designing and refining AI-led experiencesoften without writing a single line of code. Thats a meaningful shift in how organizations move from experimentation to execution. Why connected experiences matter more than ever Consumers now expect connectedness, not just availability. In recent banking demos, AI agents were able to detect user intent more effectively than traditional natural language understanding systems, guide conversations toward specific outcomes, and seamlessly escalate when needed, all while maintaining continuity. In one example, a customer exploring refinancing options asked a mix of basic and advanced questions. The AI not only responded accurately, but also captured key qualifying details and facilitated a warm handoff to a human loan officer. The advisor didnt need to repeat questionsthe context traveled with the customer. Thats orchestration in action. From system of record to system of action Traditional systems were built to store data, not act on it. But modern platforms must be systems of action, capable of interpreting signals and responding in real time. This means using AI to go beyond logging interactions and instead drive proactive engagementsurfacing insights, anticipating needs, and guiding the next best action. Whether its a lost card or a mortgage inquiry, the most successful brands are rethinking the architecture behind the experiencenot just layering AI on top. This is a window of opportunity Retail has already started to rethink how it delivers value through AI. Banking is close behindbut with higher stakes, more regulation, and bigger complexity. That makes clarity even more important. This moment isnt about racing to launch the next chatbot. Its about reimagining how every part of the customer journey connectsand whether it delivers the kind of trust, empathy, and outcomes that consumers expect from their bank. AI is no longer a nice to have in the CX stackits becoming the connective infrastructure. But only if its applied intentionally, not reactively. The gap between brand ambitions and customer expectations is shrinking. And for banks that act now, with a focus on orchestration, that gap becomes a window of competitive advantage. The organizations that get this right wont just modernize. Theyll leadbecause customers will follow the brands that make things easier, safer, and smarter. John Sabino is CEO of LivePerson.
Category:
E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. In just a few short years, generative artificial intelligence has begun demonstrating its tremendous business potential. Stanford Universitys latest AI Index report reveals that global corporate investment in AI grew nearly 45% in 2024 to reach $252.3 billion. With private investment in generative AI up 8.5 times over 2022 levels, forecasts suggest that AI could soon contribute trillions of dollars to the American economy alone. By 2028, agentic AI, the next stage in AIs evolution, could be making at least 15% of day-to-day decisions at work and bring greater efficiency, productivity, and innovation. Were already seeing how AI is creating new businesses, products and services with the potential to expand access to new quality jobs and build new sources of wealth. Today, workers are using AI to inject creativity into their current jobs and start and grow their own businesses. Two-thirds of small businesses that use AI say their own employees are introducing AI tools to the workplace to improve operations, reduce costs and spark innovation. Many organizations are understandably focused on the near-term time- and cost-savings this emerging technology brings about. But pure efficiency wont unlock the true value of AI; that will require tapping into the expertise and creativity of their employees. To fully realize AI’s potential to revolutionize our economy, we need to put workers at the center of the process of deciding where and how it shows up in the workplace. What does that look like in practice? AI training First, organizations should offer more AI trainingfrom basic literacy to implementation. AI usage at work is surging, according to a new study from my team at JFF. Two years ago, only 8% of individuals used AI at work. Today, its 35%. Those who use AI say AI is making them more efficientand their jobs more interestingby reducing the number of tedious tasks and allowing them to focus on more strategic and creative work. More training means more people experiencing these benefits and contributing to decision making around AI. Yet our survey also found wide training gaps. Fewer than one third (31%) of workers say their employers provide training on AI fundamentals or specific AI tools and systems. Slightly more than one third (34%) of employees not receiving AI training at work say they want their employer to offer it. This lack of access to training is creating barriers to the effective implementation of AI at work. Previous JFF research shows that nearly 60% of small businesses cited workforce readiness as the most common barrier to incorporating AI technology into their businesses. To overcome that barrier, organizations can start by providing affordable and practical AI literacy training that help employees learn how to get the most out of AI and become responsible users of this emerging technology. Employee-driven innovation Second, organizations should catalyze employee-driven innovation. Workers are already eager to use AI: according to JFFs recent survey, 20% of employees say theyre taking the initiative to use AI at work in the absence of formal direction from their employers, while nearly 30% of workers are leveraging AI tools for strategic growth and innovation. Theres a good business case to be made for bottom-up transformation. Research suggests that when workers are asked for their input, organizations are more likely to make effective use of AI tools and improve the quality of workers jobs. To unlock growth using AI, businesses should involve their employees in piloting and deploying AI tools and processes across multiple roles and functions throughout an organization. Frontline employeesexperts on their own workflowsare often in the best position to help improve and refine development of AI tools and processes. Theyre the ones companies should call on to find uses of AI that can create value and drive innovation. AI and human collaboration Finally, organizations should reconsider how their employees spend their time, the nature of the work they do, and their unique skills so they can unlock the best parts of collaboration between AI and humans. The immediate goal of AI implementation should be about enabling workers to prioritize work that creates new products, services and value that helps businesses grow. Collaboration between humans and AI has enormous potential. As a Harvard Business School working paper suggests, AI can help professionals significantly boost performance, expertise, and social connectivity in team settings. As AI becomes more capable of making its own decisions and completing complex tasks, humans will spend more time supervising AI, discerning and evaluating AI outputs, and managing interpersonal and collaborative activities with other humans. Weve also seen that AI appears to significantly increase the value of human leadership in interpersonal and highly cognitive tasks like staffing organizations, building relationships, and guiding and motivating teams. Employers have an opportunity to prepare for this shift by designing high-quality jobsand involving their workers in this processthat can get the best out of collaboration between humans and AI. The transformation of work is underway. Businesses seeking to navigate it should support employees in their earnest desire to develop AI literacy and skills, catalyze creativity and innovation throughout the organization, and intentionally redesign jobs to unlock the strengths of both AI and humans. Previous technological revolutions have shown that the benefits of progress are not distributed equally. But if companies keep their employees at the center, they can fulfill AIs potential as a force to expand access to quality jobs and economic opportunity for all. Maria Flyn is president and CEO of Jobs for the Future.
Category:
E-Commerce
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. Every accumulation becomes the means of new accumulation. This is what Karl Marx has to say about capital. He does not get enough credit for being one of the more accurate predictors of capitalism because people understandably do not like his solution. But the truth is, most philosophers do not even present a solution and he understood the problem as well as anyone. We saw more bankruptcies in 2024 than in the last 14 years, and consumer discretionary was the leading bankruptcy sector. This problem will only increase as AI proliferates. And while the linked article cites other reasons, we think the larger reason is Amazon. Amazon has achieved a level of automation and scale through what can only be described as accelerating accumulation. This is the major reason brick and mortar retail has become so tough, and Amazons control of the supply chain makes it harder for online businesses to compete. But why do we think this is just the beginning? We are seeing a clear increase in funding and headcount towards AI. Eighty-seven percent of Y Combinators latest batch of companies focus on AIa huge sign we are only scratching the surface of a move towards automation that can threaten small businesses. Soon it will not just be smaller businesses in the consumer cyclical sector threatened by this concerted push towards automation. But it is not just the startup world seeing this trend. Even our most successful companies are slowing down their hiring; at the same time the top 50 AI startups are accelerating at close to a 200% rate. Big tech hiring slows Live Data Technologies on Big Tech Headcount Growth Source: Live Data Technologies Source: Live Data Technologies Live Data Technologies recent analysis offers insight on the growth and profitability trends of these companies. Contrasting Magnificent Seven companies that lean on AI versus more pure AI plays in the AI 50, you can see the scary trend towards more complete automation. Larger commitments to automation could further acceleration reduction in headcount, especially for engineering positions. Google recently announced that over 25% of its code was written by AI. If some of the most talented engineers in the world at Google can no longer compete with their AI, how much longer do small and medium sized businesses have before, at the very least, their funding environment becomes more difficult as a result, and bankruptcy ensues? Traditionally, small caps have lower profitability but higher growth potential, while large caps are the opposite. But heres what our data found: Companies with a profitability score above 90, typically large or mega caps, are now growing at nearly the same rate as small caps. Its not just a statistical fluke. This pattern has only emerged during past industrial revolutions, when large companies leveraged new technologies, from railroads to oil, to dominate markets. Today, AI is the catalyst, and its the big players like Nvidia that are reaping the benefits. These profitability and growth forecasts are built on analyst predictions and economic simulations, and scaled on a bell curve with about 2,000 other stocks/ETFs. What is even more alarming about these numbers is those of the largest companies. Stocks in the 90th percentile or above in Prospero.ais profitability rating are growing more than 80%. This is strong evidence that even the most profitable companies are not being slowed down by their size. Generally it is easier to grow at faster rates if your company is less mature from a profitability standpoint. The fact that the smallest companies < 10 are also projected to grow at slower rates than <20 is perhaps even more shocking. Companies with the smallest revenue should have the easiest time growing at a faster rate. Moving from $1 million in revenue to $2 million from one year to the next is easier than going from, say, $25 million to $50 million. Profit fuels growth If you are looking for the flagship demonstration of tis idea, look no further than Nvidia. It generates billions of dollars in profit each quarter, while still achieving massive growth. Revenue from fiscal 2025 was up 114%. Looking for a benchmark number led us to Amazon, one of the greatest growth stories of our time. Amazon posted 60.52% growth when comparing Q4 2024 and Q4 2023 quarterly operating income, and posted its best quarter in the last 15 years. And it did that at roughly half of Nvidias revenue. That is what makes the Nvidia story so interesting. In 2023, Nvidia had a 98% market share in data center GPUs. Other domestic and international companies have been trying to compete with them in this market, and they simply cannot. Nvidias financial strength allows it to attract the best talent and develop cutting-edge AI technologies, creating a cycle where profit fuels growth, which then drives more profit. Now what does this mean for small caps? I think the implications are pretty clear. Were seeing the monopolization ramp up, just as we did in past revolutions. Large companies, flush with cash, have the means to capitalize on advantages of scale in ways that small players simply cant match. This makes it harder and harder for small cap companies to compete on the type of growth metrics it takes to attract the needed capital to compete in ever more competitive spaces. The rich get richer, and the competitive gap widens. So, whats the bottom line? AI-driven bankruptcy isnt just a matter of companies failing; its a symptom of an economic shift where capital accumulation accelerates faster than ever before. This isnt just a chapter in bankruptcy law, its a chapter in how AI will redefine capitalism itself. George Kailas is CEO of Prospero.Ai.
Category:
E-Commerce
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