The Importance of Human Agents in AI Support

Friends, while everyone races to implement the latest AI tools, there's one secret the top performers already understand: 𝗛𝘂𝗺𝗮𝗻 𝗮𝗴𝗲𝗻𝗰𝘆 𝗺𝗮𝗸𝗲𝘀 𝗔𝗜 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲—𝗻𝗼𝘁 𝘁𝗵𝗲 𝗼𝘁𝗵𝗲𝗿 𝘄𝗮𝘆 𝗮𝗿𝗼𝘂𝗻𝗱. After training thousands of professionals across higher education and industry, one pattern is crystal clear: People who bring purpose and ownership to their use of AI consistently figure out how to capture and create more value from AI. These individuals aren't passively using AI—they're actively engaging with it and even shaping it. Here's the thing: • AI systems don't have agency. They have capabilities, constraints, and contexts—all of which depend entirely on human expertise to shape.  • Your domain expertise is irreplaceable; it's precisely what makes AI effective. 𝙍𝙚𝙖𝙡 𝘼𝙄 𝙩𝙧𝙖𝙣𝙨𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙙𝙚𝙥𝙚𝙣𝙙𝙨 𝙤𝙣 𝙥𝙚𝙤𝙥𝙡𝙚 𝙬𝙝𝙤: • Feel genuine purpose and ownership of outcomes • Collaborate intentionally, not passively, with AI • Know their unique human contribution can't be automated • Amplify their domain expertise using AI, instead of replacing it The companies leading the AI revolution aren't necessarily those with the flashiest technology. They're the ones investing equally in human potential and AI capabilities—creating environments where people flourish alongside AI. 𝗥𝗲𝗺𝗲𝗺𝗯𝗲𝗿: 𝗛𝘂𝗺𝗮𝗻 𝗔𝗴𝗲𝗻𝗰𝘆 > 𝗔𝗜 𝗔𝗴𝗲𝗻𝗰𝘆. Your AI doesn't care about outcomes. Your people do. Invest in both, and you’ll outpace others. I’d love to hear your thoughts—what role do you see human agency playing in your AI initiatives?

Hot take: AI will never fully replace humans in customer support. Not now. Not ever. Yes, AI can crush basic support tickets. But let’s be clear: efficiency ≠ trust. The Cursor incident is but the latest example (Reference: https://lnkd.in/gHCbutAi). Sam - Crusor’s AI support agent - confidently gave users the wrong answer. That single, hallucinated response set off confusion, cancellations, and a loss of trust. It wasn’t a policy change. It wasn’t a product decision. It was automation—unmonitored. The lesson? AI doesn’t just need prompts. It needs partners. Human-led training, real-time oversight, and context-aware judgment aren’t nice-to-haves. They’re mission-critical. Because customers don’t just want answers. They want to feel heard. Here’s the paradox no one wants to admit: The more AI we use, the more human our systems need to become. Why? Because judgment, empathy, and nuance don’t scale with compute. The future of support isn’t AI vs. humans. It’s AI & humans—working side by side to create smarter, faster, and yes, more human experiences. If you’re building support ops and you think full automation is the goal… you’re solving for the wrong outcome.

AI in customer support is often reduced to metrics: resolution time, cost per ticket, deflection rates. But the real promise of AI goes far beyond efficiency. The most exciting opportunity isn’t just about doing things faster — it’s about doing them better. Smarter AI agents are now handling the repetitive, predictable tasks that once drained time and energy from support teams. But the real shift? It happens when those same teams finally have the space to focus on what makes them exceptional: empathy, creativity, and context. This isn’t about replacing people — it’s about elevating them. If technology is meant to bring us closer, then the real value of AI in CX lies in how well it deepens human connection. What do you think?

Must read for anyone thinking about or working alongside AI today ⬇️ A recent study from Stanford University introduces a novel framework to assess how AI agents can be integrated into the U.S. workforce, emphasizing worker preferences and human agency. Key Highlights: Human Agency Scale (HAS): A five-level scale (H1-H5) quantifying desired human involvement in tasks, moving beyond the binary view of automation. Worker Preferences: Out of 844 tasks across 104 occupations, 46.1% of tasks are favored by workers for AI automation, primarily to offload repetitive, low-value work. Desire-Capability Mismatch: The study identifies four zones based on worker desire and AI capability: “Green Light,” “Red Light,” “R&D Opportunity,” and “Low Priority.” ‼️Notably, 41% of current AI investments focus on areas with low worker desire for automation. Evolving Skill Demands: As AI handles more information-processing tasks, there’s a shift in demand towards interpersonal and organizational skills. This research underscores the importance of aligning AI development with worker preferences to foster effective human-AI collaboration. 📄 Read the full paper here: https://lnkd.in/e8NQfJMs #futureofwork #AI

Let’s get one thing straight: human agents are not the problem. The problem is that we’ve spent decades training them to be robots—forcing them to follow rigid scripts, measure success by handle time, and repeat the same conversations day in and day out. And then we wonder why attrition is sky-high. 💙 What if we gave them challenging conversations to solve? 💙 What if we empowered them to use judgment and creativity instead of a script? 💙 What if we stopped treating them as an interchangeable workforce and started investing in their expertise? With AI automating the repetitive and mundane, we can redefine what it means to be a customer service agent. Those who embrace this shift will see something surprising—agents staying longer, more engaged, and enjoying their work. The future of customer service isn’t about fewer agents. It’s about better agents.

AI agents were never designed to replace entire organizations but rather to support existing teams for better and more scalable decision-making. This is the path where machines augment humans with proper controls rather than replace them. Check out the recent experiment from Carnegie Mellon, where researchers created a fake company fully staffed by AI agents, which resulted in some obvious challenges. This outcome shouldn't surprise us. When we create businesses, we build them for humans with human intuition, connections, and understanding. Technology has always been meant to enable these human elements, not substitute for them. As we continue advancing AI capabilities, let's remember that the most powerful applications come from human-AI collaboration, where each contributes their unique strengths. This partnership approach will likely yield far better results than attempting to remove humans from the organizational equation entirely. The future isn't about agents managing agents (at least in the short to medium term); rather, it's about humans managing agents and guiding them. Check out this fake agent company: https://lnkd.in/gm3eiSWE

A new study finds that leaders expect their teams will be training (41%) and managing (36%) AI agents within 5 years. This research underscores a significant shift in the future role of HR leaders, requiring them to proactively develop strategies for workforce training and management that incorporate AI agents as integral team members. HR will need to create training programs not only for employees to effectively utilize AI tools in their work but also to equip them with the skills to train and oversee the performance of AI agents, ensuring alignment with organizational goals and ethical guidelines. HR will be instrumental in redefining team structures, performance management systems, and job roles to accommodate this human-AI collaboration, fostering a culture of adaptation and continuous learning within the organization to maximize the benefits of an AI-augmented workforce. https://lnkd.in/ehtkczM2

Will the future be agent or human? Spoiler alert: it’s both! And the fastest way to get hands-on and see what AI can do for you right now is to learn how to Think with AI. What AI agents will be able to do for us is super exciting (agents are systems designed to make and execute decisions independently), and their capabilities will advance rapidly in 2025. It’s important to know, however, that since we’re still learning how to best use AI, many use cases rely on what’s called “human-in-the-loop.” This means that AI informs decision-making, but people remain in charge of interpreting results and driving actions, rather than trusting the system to act on its own (yet). This is why forward-thinking organizations are discovering that success lies not just in implementing AI systems, but in helping their teams to Think with AI. It’s a fast path to give your people experience with AI—and ensuring everyone on your team has direct experience with AI’s capabilities is absolutely crucial for any organization hoping to really leverage this technology. Thinking with AI is collaborating 🤝 with AI to amplify our human performance so we can achieve something we aren’t capable of on our own. It inherently emphasizes human-in-the-loop: we are using AI as a cognitive enhancer—to help us think smarter and better—rather than as a replacement. It’s an ideal way to jump in NOW, get firsthand experience with the technology, and build AI muscle across an organization. Don’t wait for the agentic future to be clear to get familiar with AI. This is an approach you can use now, so as the agent space takes shape, you’ve already built your AI muscle and are ready to race. I’ve put some links to resources in the comments below. ____________ 👋 Hi, I'm Alison McCauley, and focus on how to leverage AI to do better at what we humans do best. I’ll be sharing more about how to Think with AI, and use the power of AI to boost our brainpower. Follow me for more, and share your thoughts below! #aiagents #agents #agenticfuture

Gartner predicts that generative AI will be a workforce partner for 90% of companies globally by the end of this year (ICYMI, we're still in 2025). And, just in 5 years, by 2030, we could see 92 million jobs lost, and 𝟭𝟳𝟬 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 jobs created, according to the latest World Economic Forum report. The same WEF report forecasts a global job churn of 22% by 2030. And it got me thinking, why is it important to retain the human component when working with #AI? The graphic breaks down AI roles into a spectrum: from must-haves like: - Model Managers - AI Architects - Heads of AI, and to emerging ones like - Prompt Engineers - Knowledge Engineers - AI Ethicists. It even maps out a collaborative cycle involving Data Scientists, Software Engineers, Business Owners, and more—highlighting how AI isn't just tech; it's a human-machine symphony. In the CPG and digital commerce space, where personalization, supply chain optimization, and #eCommerce experiences are king, these roles aren't optional—they're essential for survival and growth. If, by the end of this year, #GenAI will be a workforce partner for 90% of companies globally as Gartner predicts, for big CPG brands like Procter & Gamble or The Coca-Cola Company or Nestlé, that means deploying AI agents to predict consumer trends in real-time, automate inventory forecasting, or even craft hyper-personalized digital ads that boost conversion rates by 20-30%. That's already on our AI Maturity research findings, which we shared a few days ago. In #CPG & #FMCG, we're seeing explosive demand for roles like AI-augmented UX Designers (to revolutionize our digital storefronts), Prompt Engineers (to fine-tune GenAI for consumer-facing chatbots), and Decision Engineers (to blend human intuition with AI-driven insights for ethical supply chain decisions). Moving beyond simple outputs, these systems can act autonomously—think an AI agent optimizing our eCommerce logistics across 180 countries, flagging ethical risks in data usage, or collaborating with human teams on product innovation. With open-source tools like LangChain democratizing access, even mid-sized CPG brands can experiment without massive R&D budgets. Humans should remain the North Star: evaluating AI outputs, providing context, and making those conscience-driven decisions that build trust in consumer brands. ______________________ For more on AI, Data Science, and digital commerce, you can check my previous posts and upcoming ones. Mert Damlapinar 𝗧𝗼 𝗮𝗰𝗰𝗲𝘀𝘀 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗹𝗹𝗼𝘄 ecommert® 𝗮𝗻𝗱 𝗷𝗼𝗶𝗻 𝟭𝟱,𝟳𝟬𝟬+ 𝗖𝗣𝗚, 𝗿𝗲𝘁𝗮𝗶𝗹, 𝗮𝗻𝗱 𝗠𝗮𝗿𝗧𝗲𝗰𝗵 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝘄𝗵𝗼 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲𝗱 𝘁𝗼 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝘁® : 𝗖𝗣𝗚 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. #ArtificialIntelligence #Jobs Nike Mars Henkel Bayer Kenvue Haleon Philips Signify Schneider Electric Stryker Abbott GE HealthCare