Benefits of Involving Experts in AI Implementation

The places where AI Agents are most beneficial are the places where sourcing the data is harder to find and more costly and time consuming to collect: SME knowledge transfer. Companies around the country have SMEs that are simply overwhelmed by their workflow, don’t have the time for knowledge transfer and require tools to take the repetitive tasks off of their plate so they can be more productive. This is where AI Agents can come in: - They shine where data is scarce and costly to collect - They can handle repetitive tasks, freeing up SMEs for high-value work - They can facilitate knowledge transfer without overburdening experts The challenge? - Data Limitations: SME knowledge is irreplaceable and, as a result, not available online. It’s imperative that devs involve SMEs in the development process while prioritizing the SME’s schedule. Why?  - Calibration is Crucial: AI Agents that do not align with the SME will return irrelevant and useless results wasting time and money. How? - Human-in-the-Loop techniques: Direct SME involvement in calibration yields the best results. Their input fine-tunes AI responses and decision-making. AND - Iterative Improvement: Calibration must be ongoing. Regular feedback loops between AI and SMEs drive continuous enhancement. What does this do? - The AI solution will be built as complement, not replacement, to Human ability:. The goal is to augment SME capabilities, not replace them. This synergy boosts productivity and knowledge sharing. While initial calibration takes time, the long-term gains in efficiency and knowledge dissemination are well worth it. AI Agents can be built responsibly while including our SMEs and improving performance. It takes true engineering and ingenuity to allow AI to move us forward and not replace invaluable talent. 

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?

“Wait… if you’re using AI for audits, why would I pay you $25K?” Real objection. Real conversation. If you’re thinking the same thing, you’re not alone. When we first started integrating AI into our audit process, I had the same internal debate. Was I undermining the value we bring by using AI to assist? But the more we leaned in, the clearer it became: AI isn’t replacing expertise. It’s making room for more of it. Here’s what I mean: ➔ AI can pull KPIs faster. ➔ AI can flag performance marketing trends quicker. ➔ AI can help draft a pre-read faster for client review. But AI cannot prioritize what actually matters for your business. It doesn’t fully understand the big picture. That’s where judgment comes in. That’s where years of operating experience show up. Instead of spending hours chasing down basic metrics, I can now spend those hours doing the things that move the needle: ▪️ Identifying true growth bottlenecks ▪️ Creating measurement strategies that ladder up to business outcomes ▪️ Advising clients on what to actually do next (Not just handing over a 20-page “audit deck” full of useless charts.) This is what clients pay for: Expertise, not speed. Recommended actions, not data dumps. The best agencies (and advisors) will be the ones who use AI as a co-pilot, not a crutch. If you're not using AI to amplify your expertise, you're missing the point. If you're only using AI and removing the human element, you're missing the opportunity.

Generative AI in HR: A Reality Check The buzz around generative AI, like ChatGPT, has been unmissable. But when HR pros put it to the test, the results were eye-opening. Real-World HR Tests: AI vs Human Insight In one corner, Mineral's HR experts. In the other, ChatGPT's AI. The mission? Tackle complex HR and compliance queries. The outcome? A revealing look into AI's strengths and its limitations. Experiment 1: ChatGPT on Trial ChatGPT, across its versions, faced off against tricky HR questions. The verdict? Later versions showed promise, but when it came to nuanced, complex queries, human expertise still ruled supreme. The message? AI's got potential, but HR's nuanced world needs the human touch. Experiment 2: Knowledge Work and AI Harvard Business School and BCG took it further, exploring AI's impact on knowledge work. Surprise finding? While AI boosted some creative tasks, it sometimes hampered performance on complex analytical challenges. The Takeaway: AI's Not a Solo Act What's clear is this: AI, especially in HR and knowledge-intensive roles, isn't a standalone solution. It shines brightest when paired with human expertise, enhancing efficiency and insight rather than replacing it. For those navigating the future of work, it's a blend of AI's rapid processing with the irreplaceable depth of human understanding that'll pave the way forward. Embrace AI, but remember, the human element is your ace card. Stay tuned for more insights on blending AI with human expertise in the workplace. Follow our newsletter for updates. Check out the full article here: https://lnkd.in/gznn43vp #AIinHR #FutureOfWork #HumanAIcollaboration

What does AI in cybersecurity really mean? It’s more than just automation and faster threat detection. While AI is a powerful tool in the cybersecurity landscape, it’s not the whole answer. Here’s why human expertise still plays a crucial role: → AI Isn’t a Silver Bullet AI can analyze vast data sets and spot patterns—but it can’t grasp the nuances that a human can, like detecting complex social engineering attacks or understanding context in real time. → False Positives? AI Needs Human Insight AI often flags benign activities as threats due to its reliance on algorithms. Human analysts are essential to interpret these alerts and separate real threats from false alarms. → Humans See the Bigger Picture Cybersecurity isn’t just about technology—it’s about understanding human behavior and organizational dynamics. Experienced professionals can spot emerging threats AI hasn’t yet recognized. → Evolving Threats Need Human Adaptability Cybercriminals are constantly innovating, and while AI can handle known attacks, humans are better at adapting quickly to new, evolving threats and devising strategies to counter them. → Collaboration is Key AI should enhance—not replace—human decision-making. When used together, AI automates routine tasks, allowing cybersecurity experts to focus on complex, critical issues. The takeaway? AI is a powerful ally, but it’s human intuition and expertise that make cybersecurity truly effective. How is your organization balancing AI with human expertise? Let’s discuss how the combination can strengthen your cyber defense!