Implementing AI While Maintaining Human Touch

While everyone's talking about AI replacing human agents, something more interesting is happening: technology and humans are forming a powerful partnership that's transforming customer experience. AI isn't stealing your agents' jobs – it's making them superheroes. At Callzilla - The Quality-First Contact Center, we've been implementing Agent Assist tools that give agents real-time support during customer interactions. The results speak for themselves: • Agent gets asked an impossible question? AI whispers the answer • Customer mentions an uncommon tech issue? Relevant articles appear automatically • Agent struggling to categorize the call? AI suggests the perfect reason code • About to make a mistake? AI catches it before it happens This creates a 'best of both worlds' scenario where technology handles routine tasks while agents focus on what humans do best: • empathy • genuine connection • creative problem-solving When to Automate vs. When to Humanize: • Let AI Handle: Repetitive tasks, basic info lookups, initial problem identification • Keep It Human: Complex problems, emotional situations, VIP customers who expect the red carpet treatment Pro tip: Give customers choice. Instead of forcing one path, ask: "We can have an agent available in 5 minutes, or you can chat with our AI assistant now who handles most issues. What works better for you?" Your tech should be: • Serving up answers faster than expected • Reducing agent cognitive load, not adding to it • Supporting natural conversation, not rigid scripts • Suggesting solutions, not just documenting problems AI doesn't replace your agents – it creates 'super agents' who resolve issues faster, with less effort, and greater accuracy. It's not about choosing between humans OR technology. It's about humans AND technology working together. The companies seeing the best results have figured out this perfect pairing – and their customers can't get enough. What's your experience with human-AI partnerships in CX?

Generative AI has been making waves in the industry for over two years, revolutionizing how businesses engage with customers. In this blog, the Engineering team at Noom shares how they developed their AI-powered customer support solution. Noom is a digital health company offering a subscription-based mobile app that helps users achieve their wellness goals, and it relies heavily on its chatbot for customer interactions. While directly leveraging ChatGPT-4 for customer chats was a promising first step, the team identified several challenges: issues with hallucinations, a lack of customization to user needs, and a mismatch with Noom's unique communication style. To address these challenges, the team developed a customized solution. They started by using Prompt Instruction with GPT-4 to form the foundation of their AI assistant. Next, they implemented Prompt Augmentation with Noom's Knowledge Base (RAG), Dynamic Prompts based on user data, and JSON Format Responses. These elements enabled the system to accurately process user messages, understand their needs, and deliver tailored responses. Furthermore, recognizing the importance of human connection, the team integrated classification models with LLMs to identify when a human touch was needed, ensuring users felt understood and valued. This approach is a great example of companies leveraging generative AI to create customized solutions that address their unique challenges. #datascience #machinelearning #generative #LLM #chatGPT #customer #chatbot – – –  Check out the "Snacks Weekly on Data Science" podcast and subscribe, where I explain in more detail the concepts discussed in this and future posts:    -- Spotify: https://lnkd.in/gKgaMvbh   -- Apple Podcast: https://lnkd.in/gj6aPBBY    -- Youtube: https://lnkd.in/gcwPeBmR https://lnkd.in/gvJg5tMK

Most AI implementations can be technically flawless—but fundamentally broken. Here's why: Consider this scenario: A company implemented a fully automated AI customer service system, and reduced ticket solution time by 40%. What happens to the satisfaction scores? If they drop by 35%, is the reduction in response times worth celebrating? This exemplifies the trap many leaders fall into - optimizing for efficiency while forgetting that business, at its core, is fundamentally human. Customers don't always just want fast answers; they want to feel heard and understood. The jar metaphor I often use with leadership teams: Ever tried opening a jar with the lid screwed on too tight? No matter how hard you twist, it won't budge. That's exactly what happens when businesses pour resources into technology but forget about the people who need to use it. The real key to progress isn't choosing between technology OR humanity. It's creating systems where both work together, responsibly. So, here are 3 practical steps for leaders and businesses: 1. Keep customer interactions personal: Automation is great, but ensure people can reach humans when it matters. 2. Let technology do the heavy lifting: AI should handle repetitive tasks so your team can focus on strategy, complex problems, and relationships. 3. Lead with heart, not just data (and I’m a data person saying this 🤣) Technology streamlines processes, but can't build trust or inspire people. So, your action step this week: Identify one process where technology and human judgment intersect. Ask yourself: - Is it clear where AI assistance ends and human decision-making begins? - Do your knowledge workers feel empowered or threatened by technology? - Is there clear human accountability for final decisions? The magic happens at the intersection. Because a strong culture and genuine human connection will always be the foundation of a great organization. What's your experience balancing tech and humanity in your organization?

2025 will NOT be all about VoiceAI Agents in Customer Service. 𝗜𝘁 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗮𝗯𝗼𝘂𝘁 𝗮 𝗛𝘆𝗯𝗿𝗶𝗱 𝘄𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲 𝗼𝗳 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗛𝘂𝗺𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝘀. Yesterday, we spent a full day with the executive team of a large Auto Insurance company showing them the future of VoiceAI Agents and how it can transform their business. It became clear to them that VoiceAI agents can handle most of their interactions. But are they in a position to transition 100% of all their interactions to VoiceAI agents tomorrow? Not really. They needed to think about things like API readiness, risk tolerance, complexity of interactions, LLM hallucination risk, sensitivity of the interaction (emotional quotient), and more. These are core elements of what we call our 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀 𝗥𝘂𝗯𝗿𝗶𝗰. Using our 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 product, we analyzed their past customer service interactions. For every interaction type, we measured readiness factors and generated an 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀 𝗦𝗰𝗼𝗿𝗲. Clearly, some interaction types had a very high score, and some had very low scores. It became clear to them that 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝗮 𝗷𝗼𝘂𝗿𝗻𝗲𝘆. They will start moving high-score interactions to AI agents while the human agents still take the low-score calls. In parallel they will do the work to improve the AI Agent readiness score for the remainder for the interaction types. 2025 will be the year where enterprises that can balance AI agents and Human agents will win. Enterprises that know when to use AI agents and when to use Human agents. Enterprises that can transition seamlessly between Human and AI agents. 2025 𝘄𝗶𝗹𝗹 𝗯𝗲 𝘁𝗵𝗲 𝘆𝗲𝗮𝗿 𝗼𝗳 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝗔𝗴𝗲𝗻𝘁𝘀 (𝗛𝘂𝗺𝗮𝗻 𝗮𝗻𝗱 𝗔𝗜).

The AI-infused workforce is here. You can't just implement a chatbot, reduce your team size, and expect to keep meeting customer expectations. You have to reimagine the whole customer experience team. You need to think about both humans + technology and how they work together. What does this mean? ⭐ 𝐕𝐨𝐢𝐜𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐜𝐚𝐧 𝐫𝐚𝐭𝐞 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐬𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐀𝐍𝐃 𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐢𝐧 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞. These platforms can monitor 100% of tickets in real time - far superior than the current method of combining CSAT & QA. But they have to be managed properly. You can't just set it and expect the insights to flow in. Which leads us to.... ⭐ 𝐍𝐞𝐰 𝐫𝐨𝐥𝐞𝐬 𝐚𝐫𝐞 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠. These include: 𝘊𝘰𝘯𝘷𝘦𝘳𝘴𝘢𝘵𝘪𝘰𝘯 𝘔𝘢𝘯𝘢𝘨𝘦𝘳. This is a role that Intercom has created on their own internal support team. The focus is managing the whole customer experience journey, as customers flow from the bot to human agents. 𝘒𝘯𝘰𝘸𝘭𝘦𝘥𝘨𝘦 𝘔𝘢𝘯𝘢𝘨𝘦𝘳. Another role pioneered by Intercom, this person is responsible for keeping the knowledge base up to date and making sure it's written not just for humans to understand, but for computers to understand. 𝘝𝘰𝘪𝘤𝘦 𝘰𝘧 𝘵𝘩𝘦 𝘊𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘈𝘯𝘢𝘭𝘺𝘴𝘵. VOC analysts will replace QA analysts. Instead of completing audits they'll be monitoring VOC systems for trends and insights that will be used to drive trainings and process improvements. 𝘈𝘐 𝘊𝘢𝘭𝘪𝘣𝘳𝘢𝘵𝘪𝘰𝘯 𝘚𝘱𝘦𝘤𝘪𝘢𝘭𝘪𝘴𝘵. Someone who will be in charge of continually monitoring performance of the AI bot, as well as other automations, to ensure they are doing their job. ⭐ 𝐏𝐨𝐝𝐬 𝐨𝐟 𝐬𝐮𝐛𝐣𝐞𝐜𝐭 𝐦𝐚𝐭𝐭𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐭𝐬 𝐰𝐢𝐥𝐥 𝐫𝐞𝐩𝐥𝐚𝐜𝐞 𝐭𝐞𝐚𝐦𝐬 𝐨𝐟 𝐠𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐬𝐭𝐬. AI will take on the simpler tickets, and what's left will be increasingly complex. According to Declan I., the VP of Support at Intercom, the best way to manage this complexity is to upskill agents so they have particular areas of expertise, which is what Intercom has done. ⭐ 𝐘𝐨𝐮 𝐧𝐞𝐞𝐝 𝐧𝐞𝐰 𝐊𝐏𝐈𝐬 Your AI and automation tools need their own KPIs, like AI Resolution Rate. More on this in a future post. ⭐ ... 𝐀𝐧𝐝 𝐦𝐮𝐜𝐡 𝐦𝐨𝐫𝐞 Agents will need different schedules and breaks to avoid burnout. More and better training is needed for agents. And so on. ⭐ ⭐ ⭐ ⭐ 𝐈𝐍 𝐒𝐔𝐌𝐌𝐀𝐑𝐘 ⭐ ⭐ ⭐ ⭐ AI tools aren't "set it and forget it." You need to reshape your team, and then you need multiple people on your team who can monitor your AI KPIs and recalibrate the technology when KPIs start to slip. You can do this internally, or partner with a #bpo who can do it all for you. But not all BPOs can or will. If you're already working with a BPO partner, ask them about it. We have an upcoming podcast episode with Declan I., all about the lessons Intercom has learned deploying its AI technology on its internal support team. Stay tuned!  

Just had an fascinating interaction with ŌURA support that highlights a critical lesson about AI and customer trust... I reached out about a lost ring and received what appeared to be a wonderfully empathetic response: "I'm truly sorry to hear that you've lost your Oura ring. I understand how disappointing this must be for you..." The tone was perfect. Human. Compassionate. Then came the plot twist at the end: "This response was generated by Finn, Oura's Virtual assistant." Here's why this matters for anyone building AI into their customer experience: The response itself wasn't the problem. It was actually quite good. The problem was the setup - it felt like being led to believe you're talking to Sarah from customer support, only to discover it's AI after you've opened up about your situation. It's a bit like someone wearing a convincing mask through an entire conversation, then dramatically pulling it off at the end. Even if the conversation was great, you still feel... weird about it. So when they sent me their customer satisfaction survey, I decided to have some fun. I used ChatGPT to write my responses and signed it off, "This response was generated by ChatGPT, Nate's Virtual assistant." But there's a serious point here: Transparency about AI usage isn't just an ethical choice - it's a strategic one. When customers discover they haven't been talking to the human they thought they were, it erodes trust. And trust, once lost, is incredibly expensive to rebuild. The lesson? If you're using AI in customer service: - Be upfront about it from the start - Let customers know they're talking to AI before the conversation, not after - Keep the empathy (AI can be both transparent AND compassionate) Your customers will appreciate the honesty, and you'll build stronger relationships because of it. PS - I love my ŌURA ring and previously they went above and beyond replacing a defective ring at no cost to me.

“𝗧𝗮𝗹𝗸 𝘁𝗼 𝗛𝘂𝗺𝗮𝗻.” The 3 words no AI company wants to hear, but every customer keeps typing. It’s ironic. We’ve never had more powerful AI, yet the number one thing users want from chatbots is to bypass them entirely. Why? Because efficiency without empathy leads to frustration. Sure, AI-powered customer support handles 80% of cases flawlessly. Fast. Scalable. Cheap. But what about the other 20%—the edge cases, the complex issues, the moments when a human touch makes all the difference? When AI can’t help, and there’s no easy path to escalate to a person, trust erodes. And once you lose a customer’s trust, it’s game over. This isn’t purely a tech problem—it’s a problem of focus. AI isn’t the enemy here; it’s how we’re positioning it. The real opportunity isn’t about replacing humans—it’s about designing systems where AI handles the routine, and humans step in when complexity, nuance, or empathy is required. The magic lies in knowing when to seamlessly transition from automation to human interaction. The businesses that get this balance right? They’ll win. They’ll be the ones who use AI to enhance—not replace—the human experience.

As I’ve shared our vision about Customer Success 5.0 (CS5.0), people often ask whether I believe AI will replace CSMs. My answer? NO. AI will amplify the impact of great CSMs, empowering them to deliver deeper, more personalized value to each customer. This is how I think about the impact of AI in customer success. Legacy CS = (EQ + IQ) Before AI, we relied heavily on the relationship skills (EQ) and smarts (IQ) of CSMs to build deep relationships with customers and ensure we delivered the outcomes they expected. Often, CSMs had to dedicate extraordinary time and effort juggling a wide range of tasks just to keep up – prepping for and summarizing meetings, finding updates, analyzing data, writing emails, answering product questions, and more. Yes, these efforts worked in most cases but often demanded heroic contributions from CSMs just to sustain customer relationships, let alone grow them. Now the CS5.0 equation redefines our approach: CS5.0 = (EQ + IQ) * AI With AI as a significant accelerator, collaborator, and multiplier, we're able to reimagine customer success across: 1. The Heart (EQ) ❤️ Emotional Intelligence (EQ) remains at the core of customer success. It’s about understanding, empathizing, and connecting with our customers on a human level. Building lasting relationships and anticipating customer needs requires empathy, active listening, and authenticity. 2. The Brain (IQ) 🧠 Human Intelligence (IQ) emphasizes data-driven decision-making and strategic thinking. Leveraging our ability to interpret complex data and solve critical challenges in the context of each customer relationship is essential—what I call “contextual intelligence.” IQ drives operational excellence and execution, ensuring our solutions are thoughtful, contextual, and aligned with customer needs. 3. The Multiplier 🤖 AI is the multiplier that elevates our efforts. In customer success, AI is not here to replace human interactions but to enhance them. AI-driven tools (like our SmartCS AI) assist CSMs by managing a significant share of repetitive tasks—automatically summarizing meetings, surfacing key updates, analyzing customer data, and drafting responses. By offloading these tasks to AI, CSMs can focus on high-value activities—solving strategic customer challenges, anticipating needs, and providing tailored solutions. They become much more consultative vs. transactional. AI enables CSMs to focus on what they do best—building relationships (EQ), driving smart solutions (IQ), and delivering impactful results. Where do you see the greatest opportunity for AI to empower CSMs in delivering exceptional customer experiences?

At Salesforce, we believe #agentic #AI is about augmenting human potential and developing AI in service of humans — and that’s what we’re doing with #Agentforce. I had the pleasure of speaking with the wonderful Nichol Bradford on @SHRM’s AI + HI Podcast about how it’s critical for businesses to combine the strengths of both humans and AI for what I call “complementary intelligence.” When we craft human-AI partnerships well, we harness AI strengths (like making mountains of data accessible, at-speed) alongside more human strengths (like contextual judgement, relationship building, and thinking about future innovation). Agentic AI takes this a step further by reasoning through requests, helping execute them on behalf of humans. This is brought to life through our customers like Wiley. Before each school year when customer requests surge, the Wiley team uses Agentforce to seamlessly transition routine requests to an AI agent, so they can focus on cultivating customer relationships and elevating difficult cases for human judgement. This type of system makes the experience more manageable and less stressful for employees, allowing them to focus on the highest value issues. Listen more here: https://lnkd.in/gj_Ty8uv

AI is a powerful tool— but it won’t replace empathy (3 ways to leverage AI, without losing the human touch) Over the weekend, I had a tech support exchange that reminded me just how important it is to balance AI with the human touch. After asking a simple question about my data usage, I was met with an oddly worded and irrelevant response. Curious, I asked, "𝗜𝘀 𝘁𝗵𝗶𝘀 𝗮𝗻 𝗔𝗜 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲?" The answer? “𝗡𝗼, 𝗜 𝗮𝗺 𝗮 𝗿𝗲𝗲𝗹 𝗺𝗮𝗻.” Safe to say, I wasn’t entirely convinced 😉. While AI can streamline customer interactions, it should never replace the empathy and adaptability of real people. 3 Strategies for Using AI Without Losing the Human Touch: 1. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝘁𝗵𝗲 𝗥𝗼𝘂𝘁𝗶𝗻𝗲, 𝗡𝗼𝘁 𝘁𝗵𝗲 𝗥𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽: Use AI for simple, repetitive tasks—like handling basic inquiries or routing requests to the right department. Free up human agents to focus on complex, high-empathy situations where they can make a real difference. 2. 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗦𝘂𝗴𝗴𝗲𝘀𝘁 𝗛𝗲𝗹𝗽𝗳𝘂𝗹 𝗔𝗰𝘁𝗶𝗼𝗻𝘀: Let AI recommend responses, solutions, or next steps, but give agents the final say. This keeps interactions efficient while ensuring the response fits the specific situation and customer. 3. 𝗦𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗲 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗦𝗲𝗮𝗺𝗹𝗲𝘀𝘀 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗶𝘁𝘆: Use AI to generate quick summaries of past interactions, so team members can pick up where the last conversation left off. This helps keep interactions smooth and personal, without making the customer repeat their story. AI is here to make things easier, but let’s not forget the importance of human understanding and adaptability. 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻: Have you experienced an AI interaction that felt a little too “robotic”? Share in the comments ⤵ ---- ♻️ Repost and share these leadership tips ➕ Follow me, Ashley VanderWel, for more