Effects of AI Acquisitions on Customer Experience

Klarna replaced 700 customer service workers with AI chatbots, leading to significant cost savings but also a $40 billion drop in valuation. While AI improved efficiency, the leadership realized that the lack of a human touch negatively impacted customer satisfaction and trust. Key Takeaways: 1. Lack of EQ – AI still struggles with empathy and nuanced human interactions, which are crucial in customer service. 2. Over-Reliance Leads to Customer Frustration – Automated responses can fail to resolve complex issues, leading to dissatisfaction. 3. Trust & Brand Perception – Customers often prefer human agents for sensitive matters, and AI-only solutions can erode trust. 4. AI’s Limitations in Judgment – While AI excels at handling routine queries, it still may falter in ambiguous or high-stakes situations. Why the Human Touch Still Matters: - Humans provide emotional connection and critical thinking that AI cannot replicate (yet). - Hybrid models (AI + human support) often deliver the best balance of efficiency and customer satisfaction. Klarna’s experience highlights that while AI can streamline operations, completely replacing human interaction risks damaging customer relationships. Businesses should integrate AI thoughtfully, ensuring human oversight remains where it matters most. https://lnkd.in/gm4rQ-H3

Think AI will cut contact center staff? If you’ve been reading the headlines, you’ve seen plenty of predictions that AI will reduce contact center—and overall customer service—staffing. The logic seems simple: AI can handle customer interactions directly, so organizations won’t need as many people. Add to that AI tools that help agents retrieve information, document cases, and shorten handling time, and the argument looks even stronger. But the assumption that contact center work will decline across the board? That’s misleading. I am first to put my hand up when there are opportunities to improve efficiency and effectiveness—and there almost always are. But there are also many factors adding to contact center workload: Unmet demand. In too many cases, customers can’t even get through quickly. As organizations improve experiences, that suppressed demand surfaces. Product and service complexity. Think connected devices, customized financial advice, challenges in the insurance sector, changes in healthcare ... you get the gist, this list could go on and on. More channels. These can include phone, text, email, chat, messaging apps, social media, video, et al. As any experienced contact center manager will tell you, adding channels rarely replaces old ones—it just adds to the mix. The self-service paradox. The more you automate the more defined interactions, the tougher ones land with your team. Proactive outreach. Organizations are starting to use AI to reach out—wellness checks, customer retention, and others. That’s more contacts overall, not fewer. Regulation and compliance. Especially in healthcare, finance, and utilities, oversight is increasing, adding to review work, including of decisions and summaries made by AI. Security and fraud. Scams are escalating in sophistication—often using AI. Detecting deepfakes, verifying identity, and resolving disputes are high-stakes responsibilities that require experienced humans. Business change. New products, subscription models, mergers—these always generate customer questions. Differentiating on experience. Customer experience is one of the most powerful (and few remaining) ways to stand out. Think concierge service, retention specialists, account advisors—roles that depend on skilled people. AI will play a powerful role in service delivery. But the real story is a redefinition and rebalancing of work. Don’t assume AI will magically erase demand. The headlines may scream “AI is cutting contact center jobs,”—don’t buy it. Customer expectations are only going up. Meeting them will require both the best of AI and the best of us.

Yesterday, I posted a conversation between two colleagues, we're calling Warren and Jamie, about the evolution of CX and AI integration. Warren argued that the emphasis on automation and efficiency is making customer interactions more impersonal. His concern is valid. And in contexts where customer experience benefits significantly from human sensitivity and understanding — areas like complex customer service issues or emotionally charged situations — it makes complete sense. Warren's perspective underscores a critical challenge: ensuring that the drive for efficiency doesn't erode the quality of human interactions that customers value. On the other side of the table, Jamie countered by highlighting the potential of AI and technology to enhance and personalize the customer experience. His argument was grounded in the belief that AI can augment human capabilities and allow for personalization at scale. This is a key factor as businesses grow — or look for growth — and customer bases diversify. Jamie suggested that AI can handle routine tasks, thereby freeing up humans to focus on interactions that require empathy and deep understanding. This would, potentially, enhance the quality of service where it truly mattered. Moreover, Jamie believes that AI can increase the surface area for frontline staff to be more empathetic and focus on the customer. It does this by doing the work of the person on the front lines, delivering it to them in real time, and in context, so they can focus on the customer. You see this in whisper coaching technology, for example. My view at the end of the day? After reflecting on this debate, both perspectives are essential. Why? They each highlight the need for a balanced approach in integrating technology with human elements in CX. So if they're both right, then the optimal strategy involves a combination of both views: leveraging technology to handle routine tasks and data-driven personalization, while reserving human expertise for areas that require empathy, judgement, and deep interpersonal skills. PS - I was Jamie in that original conversation. #customerexperience #personalization #artificialintelligence #technology #future

“Let me explain the issue again…I was saying…” Does this sound familiar? We’ve all been there: stuck on the phone or chat, explaining the same problem to a new support agent for the third, fourth, or fifth time, feeling unheard. But customer service isn’t just about solving problems. It’s about making people feel heard. Yet, far too often, support interactions feel robotic, cold, and disconnected. You’re bounced between departments. Asked to repeat yourself again and again. Given a ticket number instead of a real solution. And the worst part? No one seems to remember your last conversation. This isn’t just inefficient; it’s deeply frustrating and exhausting, and it shows a lack of empathy. Customer service must go beyond transactions. It should tap into attentive empathy, truly listening to customers, acknowledging their frustrations and cognitive empathy, and offering relevant solutions based on past interactions and emotional context. So how do we do that at scale? OpenAI’s latest update is a step in that direction. ChatGPT can now remember past conversations across sessions. This simple upgrade unlocks a smarter, more empathetic future for customer service. Imagine this: • Your support agent already knows what you’ve been through • They pick up right where you left off • They tailor responses to your preferences and pain points This is what modern, emotionally intelligent service should feel like. And the data speaks volumes: 🔹 76% of customers say repeating themselves is their #1 frustration 🔹 81% prefer brands that personalize the experience With AI memory in play, customer service teams can now: • Offer personalized support journeys • Reduce friction in every interaction • Proactively engage based on past pain points • Build long-term trust through seamless continuity For businesses, this means: • Smarter, AI-powered systems that improve with every touchpoint • Consistent journeys that feel human even when powered by machines • Stronger retention through empathy-led engagement If you’re a forward-thinking company, here’s what to do: • Invest in AI tools with conversational memory • Redesign support flows to feel continuous, not fragmented • Train agents to collaborate with AI as empathy amplifiers • Prioritize data transparency and privacy to build lasting trust Because when customers feel understood, they don’t just stay, they advocate. #AI #ChatGPT #customerexperience #CX #KSA #SaudiArabia

Every delightful customer interaction begins with the marketer, and it can only be as powerful as the #CRM and #metadata underpinning it. With agents supporting them at every step of the customer journey creation process, marketers and #customerengagement teams can now create superior experiences shaped by intelligent and emotionally resonant conversations. At a cognitive level, the human brain no longer perceives AI as a “chatbot.” It perceives a relationship. This emotional shift fundamentally changes how consumers relate to brands, fostering deeper loyalty and trust. When customers interact with agents in a way that feels natural, their engagement deepens. The implications go far beyond engagement. Every AI-driven interaction generates a wealth of contextual data, far richer than what brands could ever collect from a single web form or survey. In one conversation, an agent can gather insights about a customer’s preferences, behaviors, and intent, building a more complete, dynamic customer profile. This continuous intelligence loop allows brands to maximize the value of every interaction. Let’s bring this to life with an example... Imagine Melanie, one of your many potential customers. She’s been thinking about joining Posh Fitness, a popular gym chain in her city. Instead of filling out a form, she decides to engage with the agent on their website. As they chat, it quickly feels more like a friendly exchange than a transaction. Melanie shares her fitness goals, whether she wants to lose weight, gain muscle, or improve flexibility, and the agent listens closely, asking the right questions to understand her needs and intent. The agent gathers valuable insights through this conversation that a simple web form could never capture. Melanie mentions her dietary restrictions, her preference for a supportive personal trainer style, and that she loves outdoor workouts but needs a flexible schedule due to her busy life. In just a few minutes, the agent collects a wealth of data about Melanie: her goals, preferences, and availability—all essential to crafting a personalized experience. And because the conversation feels human-like and emotionally resonant, it creates an immediate connection to Posh Fitness. By collecting this richer data early in the relationship, Posh Fitness can offer tailored recommendations and build Melanie’s loyalty well before she signs up. This isn’t just about closing a sale. It’s about building trust and delivering personalized experiences that evoke emotions and feel deeply human. Brands that will thrive in the era of #Agentic #AI are those that recognize the shift from transactional interactions to relationship-driven engagement. This isn’t just about personalization; it’s about creating experiences and dialogues that feel alive—where AI and marketers co-create journeys that adapt in real time, amplifying the impact of every customer moment.

𝐓𝐡𝐞 𝐛𝐢𝐠𝐠𝐞𝐬𝐭 𝐬𝐡𝐢𝐟𝐭 𝐢𝐧 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐢𝐬𝐧’𝐭 𝐭𝐡𝐞 𝐜𝐡𝐚𝐧𝐧𝐞𝐥. 𝐈𝐭’𝐬 𝐭𝐡𝐞 “𝐰𝐡𝐨.” We often talk about how CX evolved — from voice to email, chat, social, and a growing number of digital touchpoints. But through every evolution, one thing stayed constant: Behind the conversation, there was always a 𝐡𝐮𝐦𝐚𝐧. Now that’s changing. Today, the first interaction a customer has is increasingly with an 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭. And that single change forces a much bigger realization: #𝐀𝐈 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐚 𝐭𝐨𝐨𝐥 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐢𝐧𝐠 𝐂𝐗. 𝐀𝐈 𝐢𝐬 𝐛𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚 𝐧𝐞𝐰 𝐩𝐞𝐫𝐬𝐨𝐧𝐚 𝐰𝐢𝐭𝐡𝐢𝐧 𝐢𝐭. • A persona that sets the #tone. • A persona that represents your #brand. • A persona that decides whether a #customer feels guided… or lost. And once AI becomes a persona, three things inevitably change. First, 𝐡𝐨𝐰 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬 𝐠𝐞𝐭 𝐛𝐮𝐢𝐥𝐭. Product teams can now use AI internally to accelerate the basics — drafting PRDs, building early prototypes, compressing iteration cycles. But more importantly, it pushes an 𝐀𝐈-𝐟𝐢𝐫𝐬𝐭 𝐦𝐢𝐧𝐝𝐬𝐞𝐭: designing features where AI isn’t an add-on at the end, but part of the product’s core value from the start. Second,𝐡𝐨𝐰 𝐯𝐚𝐥𝐮𝐞 𝐠𝐞𝐭𝐬 𝐦𝐞𝐚𝐬𝐮𝐫𝐞𝐝. When AI is the one delivering the experience, customers don’t think in terms of “features.” They think in terms of results. That’s why we’re seeing a shift toward consumption and outcome-driven models, paying for successful resolutions, meaningful detections, and tangible impact. And third, the most human question of all: 𝐰𝐡𝐞𝐫𝐞 𝐝𝐨𝐞𝐬 𝐞𝐦𝐩𝐚𝐭𝐡𝐲 𝐟𝐢𝐭? AI can learn patterns of empathy through conversational and domain-specific data. It can get better at intent, tone, and context. But empathy isn’t just language, it’s judgment. Which is why humans will continue to be essential in emotionally complex moments and high-stakes decisions. That’s the real future of CX: not humans vs AI, but 𝐡𝐮𝐦𝐚𝐧𝐬 𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐀𝐈 𝐩𝐞𝐫𝐬𝐨𝐧𝐚, and humans augmenting it where it matters most. If AI is now the first “personality” your customers meet…what principles are you designing it with? #CustomerExperience #AI #ConversationalAI #ProductLeadership #CXStrategy #DigitalTransformation #Innovation #NiCE #FutureOfWork

What CTOs in Banking Should Do with AI for Customer Experience A few months ago, I sat with the CTO of a major bank who shared a familiar frustration: “We’ve invested millions in AI, but our customer experience hasn’t improved the way we expected.” I asked a simple question: “Are you using AI to solve real customer pain points, or are you using it because it’s expected?” That conversation led us down a path that many banking leaders are navigating today—leveraging AI not just for efficiency, but to truly enhance customer relationships. AI and the Future of Banking Customer Experience The global AI in banking market is expected to reach $130 billion by 2030, growing at a CAGR of 32% (Allied Market Research). This isn’t just about chatbots or fraud detection anymore; AI is redefining how banks engage with customers at every touchpoint. McKinsey reports that banks effectively using AI can increase customer satisfaction by 35% while reducing operational costs by up to 25%. The challenge, however, is execution—CTOs must ensure AI is seamlessly integrated into both digital and human interactions. How Leading CTOs Use AI for Customer Experience 1- Hyper-Personalization Example: JPMorgan Chase uses AI to analyze customer behavior and provide real-time loan and investment suggestions, increasing engagement by 40%. 2- AI-Powered Virtual Assistants Example: Bank of America’s Erica, an AI-powered assistant, has handled over 1.5 billion interactions, offering personalized financial insights. 3- Predictive Analytics for Proactive Engagement Example: A European bank using AI-driven insights reduced customer churn by 22% by proactively addressing financial concerns. 4- AI-Enhanced Fraud Detection Example: Mastercard’s AI-based fraud prevention has reduced false declines by 50%, improving trust and security. A Real-World Impact: AI in Action One of our banking clients struggled with high customer complaints about slow loan approvals. By integrating AI-driven document verification and risk assessment, approval times dropped from 5 days to 5 minutes. The result? A 30% increase in loan applications and a significant boost in customer satisfaction. The Human-AI Balance in Banking Despite AI’s capabilities, customers still value human interaction. 88% of banking customers want a mix of AI-powered convenience and human support when dealing with financial decisions (PwC). The key for CTOs is to balance automation with empathy—ensuring AI enhances, rather than replaces, the personal touch. The Road Ahead AI is no longer a futuristic concept in banking—it’s a strategic necessity. CTOs who embrace AI for customer experience, not just efficiency, will lead the industry forward. At Devsinc, we believe the future of banking isn’t just digital—it’s intelligent, personalized, and deeply customer-centric. The question is, are we using AI to replace transactions, or to build trust? Because in banking, trust isn’t just a feature—it’s the foundation.

What happens when the AI hype meets real-world customer expectations? Klarna’s recent journey offers a powerful lesson for every business leader navigating automation. Last year, Klarna made global headlines by replacing much of its customer support team with an AI chatbot, claiming it could do the work of 700 people and handle 75% of all customer chats. The promise: - faster service, - lower costs, and - a bold leap into the future of fintech support. But the reality was more complicated. Customers quickly noticed the difference. While the AI handled simple queries efficiently, it struggled with nuance, empathy, and complex issues. Many users felt like they were talking to a filter, not a helper. The result? - Klarna’s CEO admitted that the aggressive push for automation “went too far” and led to a drop in service quality. - Now, Klarna is hiring human agents again, piloting a flexible, remote model and making a public commitment: there will always be a human available if you need one. The lesson? AI is a powerful tool, but it’s not a panacea. Automate the routine-but never underestimate the value of human connection, especially when trust, emotion, and complexity are at stake. The future isn’t about humans or AI. It’s about finding the right balance, using technology to empower people, and always putting the customer experience first. Know of any AI Automation story - successful or not ? drop a comment below. #AI #CustomerExperience #Leadership #Automation #Klarna #CX #Fintech

A Zendesk study in 2024 revealed something striking: 83% of leaders in India believe traditional customer experience will be largely replaced by AI-driven interactions within the next three years. 𝐇𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐭𝐡𝐢𝐧𝐠, 𝐭𝐡𝐨𝐮𝐠𝐡: 𝐀𝐈 𝐚𝐥𝐨𝐧𝐞 𝐢𝐬𝐧’𝐭 𝐭𝐡𝐞 𝐮𝐩𝐠𝐫𝐚𝐝𝐞. 𝐑𝐞𝐥𝐞𝐯𝐚𝐧𝐭, 𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐛𝐥𝐞 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐢𝐬. For years, customer experience in financial services has been built around information and standardisation. Early digital efforts focused on moving physical workflows online. Over time, the shift moved to digital CX itself. Being a regulated industry meant familiarity often took precedence over creativity, and personalisation rarely went beyond addressing a customer by name. With AI, that lens begins to change. Financial institutions already sit on large volumes of data about customer behaviour. The real opportunity lies in making sense of that information and translating it into relevant actions. This is the next wave of personalisation that AI can support. AI has the ability to interpret signals around behaviour, timing, history, intent, and even hesitation and convert them into interactions that are meaningful. Done well, this moves systems from being reactive to being anticipatory. It was with this thinking, and a clear intent to make finance simpler for customers, that we launched AI Nudges on the ABCD App. Each nudge translates data into an insight, a financial tip, and a relevant next action. SimpliFi, our AI assistant on the ABCD App, responds to customers and nudges them toward healthier financial habits. You can experience this across our Spend, Health, and Credit tracks, a live example of moving from information to interaction. As fintech continues to adopt AI, the winners won’t be the ones who automate the most. They’ll be the ones who use context to help customers make better choices, at the right moments. 𝐁𝐞𝐜𝐚𝐮𝐬𝐞 𝐢𝐧 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐩𝐡𝐚𝐬𝐞 𝐨𝐟 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞, 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐰𝐨𝐧’𝐭 𝐛𝐞 𝐚𝐧 𝐞𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭. 𝐈𝐭 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐭𝐡𝐞 𝐞𝐱𝐩𝐞𝐜𝐭𝐚𝐭𝐢𝐨𝐧. #ABCD #AI #Fintech #CX