Digital Coaching Methods

Many people believe live trainings work better simply because people can talk to each other face‑to‑face, but that’s not the real reason. In reality, their effectiveness comes from something else entirely, they naturally follow a powerful learning rhythm. Great offline trainings follow one simple logic: action → reflection → understanding → application. This is Kolb’s Cycle. And it’s incredibly powerful. The problem? It was almost impossible to implement it in online learning. That’s why 90% of online courses look like “interactive lectures”: nice slides, videos, quizzes. But that’s content consumption, not transformation. And now - the unexpected twist. For the first time, online learning has caught up with offline experiences. Because AI removed the main barrier: it finally allows learners to get experience, reflection, and practice in a personalized way. Here’s how Kolb’s Cycle looks in modern learning design: 1️⃣ Concrete Experience — action Essence: the learner must do something, live through a situation, face a task — ideally experiencing difficulty or making a mistake that shows their current model doesn’t work. How online: role-based dialogue, scenario simulation. 2️⃣ Reflective Observation — reflection Essence: pause and think — what happened, what actions were taken, and why the result turned out this way. How online: interactive reflection prompts; AI coach provides feedback based on performance and the learner’s own reflections. 3️⃣ Abstract Conceptualisation — understanding Essence: form a new behavioural model — concepts, principles, algorithms that explain how to act more effectively. How online: short video lecture, model breakdown, interactive frameworks, checklists, interactive infographics. 4️⃣ Active Experimentation — application Essence: try the new model in a safe environment and observe the result. How online: AI-based simulation, situational exercise, case-solving with the new approach; AI coach supports and adjusts. The outcome? Online learning stops being “content” and becomes a behaviour tracker. A course becomes a training simulator, not a film. Kolb’s Cycle finally becomes real in digital learning. Do you use this framework? What results have you seen?

Most coaches & consultants don’t have a time problem. They have a systems problem. AI doesn’t fix chaos. It scales whatever system you already have. Here are 5 AI tools that actually plug into your daily workflow (with real use-cases): 1. ChatGPT: Use it to think, not just write. Daily integration: Pre-call: Generate 5 sharp questions based on client background Post-call: Convert notes into insights and next steps Sales: Practice objection handling before discovery calls Example: “Here are my client notes → identify blind spots and suggest 3 tough questions for next session.” 2. Notion AI :Your second brain for client delivery. How to use: Create client dashboards with auto summaries Maintain SOPs for your programs Turn session transcripts into insights + next steps Example: Upload session notes → “Summarize key breakthroughs + assign action items” Your client gets clarity instantly. 3. Descript: Content creation without the headache. How to use: Edit podcasts/videos by editing text Remove filler words automatically Repurpose long-form content into shorts Example: Record a 20-min coaching insight → Cut it into 5 LinkedIn videos + 10 reels in under an hour. 4. Otter.ai.: Never miss what your client actually said. Daily integration: Record and transcribe coaching calls Highlight key patterns across sessions Build a repository of client insights over time Example: Spot recurring phrases like “I feel stuck” and use that language in your next session to go deeper. 5. Make: Where everything connects. Daily integration: Auto-send session summaries after calls Connect forms to CRM, email, and task managers Build end-to-end onboarding flows Example: Client fills a form, gets a calendar link, books a call, receives a prep doc, and you get a summary. All automated. Here’s the shift most people miss: Don’t ask, “Which AI tool should I use?” Ask, “Which part of my workflow is still manual?” That’s where AI fits. Because the goal isn’t to use more tools. It’s to free up more thinking time. What’s one task in your workflow you’d love to automate right now?

From chatbots that personalize microlearning to systems that predict who’s likely to disengage, artificial intelligence (AI) is changing how we train and learn. AI opens new opportunities to improve on some of the challenges with traditional training models such as scalability, personalization and real-time feedback. Core AI applications in the L&D space can be broken down into four categories: Artificial Intelligence (AI) Platforms: These tools tailor difficulty, pacing and topics in real time. An AI-enhanced platform can tailor the content to the learner based on their performance trends. Natural Language Tools: These are used to summarize content, create quizzes and provide conversational coaching. These applications can reduce time spent on administrative tasks and increase the focus on building relationships and delivering value. Predictive Analytics: This category of tools help learning leaders identify skills gaps and forecast learner success. Virtual Coaches and Chatbots: These tools reinforce knowledge through spaced repetition and feedback loops. AI-Powered Learning: A Case Study Streamline Services is a fifth-generation plumbing, electrical and HVAC company that handles up to 200 calls a day and serves thousands of customers each month. The company is using AI to not only coach employees but also identify areas where the team needs skills development or training. Streamline adopted an AI-powered virtual ride along platform to help transform everyday customer interactions — both in the field and in the call center — into powerful, data-driven learning opportunities. Traditionally, managers and trainers could only coach based on a handful of ride alongs or recorded calls each month. With AI, every service visit and customer conversation has become searchable, analyzable and coachable. AI highlights key themes including customer concerns, missed opportunities and tone shifts, allowing trainers to see real patterns instead of isolated incidents. The training team and managers use this knowledge to design training and structure coaching for individual needs. Because AI is deepening Streamline’s understanding of customer needs, the L&D team can develop targeted training that improves customer service and empathy across the company. Streamline’s experience illustrates how AI is fundamentally changing the learning process — from reactive coaching based on limited observation to proactive, personalized development powered by real data. This case study showcases how technology can elevate human performance rather than replace it. AI offers the ability to provide more learning opportunities and personalized learning across roles and industries. L&D professionals need to embrace this change and evolve alongside the technology. The future of learning isn’t artificial — it’s intelligently human. #LearningandDevelopment #AI #FutureofLearning

Not the safe list. The honest one. If I were restarting my coaching education tomorrow, here's what I'd invest in: → Learn to coach someone who's already been coached by AI: Your client in 2026 has already talked to ChatGPT before they sit down with you. They arrive with the reframe. The action plan. The five-step model. And they haven't shifted at all. If you can't work with that, you'll spend entire sessions chasing insights they already have. → Develop yourself as the instrument — not just read the client: We train coaches to read the client's body, energy, patterns. But what about yours? What's happening in your own nervous system that's telling you something about the field? → Read the system, not just the person: Your client goes back into an organization that's now using AI to send its own signals. AI-generated feedback. AI development plans. AI nudges. The system around your client is changing. If you're only coaching the person and ignoring what the system is telling them, you're working with half the picture. → Master integration — the skill between insight and change: AI can get someone to the insight faster than you can. The gap that's about to blow wide open isn't the insight. It's what happens after. The messy, deeply uncomfortable space between "I see it" and "I've actually changed." Almost nobody is training for this. And it's where coaching lives or dies. → Get comfortable using AI yourself: Not as a threat. As a tool. Let AI handle session notes, pattern tracking, progress mapping. Then walk into the room with nothing but presence and full attention on what's alive in the space. Stop defending your value from AI. Start multiplying it. →  Stop being the expert. Start making it messy: The best development doesn't come from frameworks. It comes from live practice — coaches learning through each other, not through one person. If your growth only happens when someone else sees what you can't, that's a ceiling. → Move from sensemaking to possibility: Most of the coaching world right now is mapping what AI can and can't do. But it's only half the work. The other half: What becomes possible for me as a coach now that AI is handling the surface? That's the question that changes how you show up. Some of these are my blind spots too. Sensemaking without action is just another way of staying safe. The coaches who thrive will be the ones who went deeper — including into the skills they hadn't mastered yet. The deeper you go, the more human the work becomes. That's not a limitation. That's the whole opportunity. What would be on your list? I want to hear what I'm missing. I'm going deeper on each of these. Follow along if this hit.

Important new AI coaching research published: Which coaching approach works “best” in an AI coaching chatbot: GROW, Solution Focused or CBT?   According to existing research it doesn’t matter what coaching approach a human coach uses, the outcomes are all similar (https://lnkd.in/d9JDDt_9). This is quite a statement given all the various claims made in popular press about the superiority of certain coaching approaches over others.  It is of course very difficult to conduct such research because you need large sample size (many human coaches) and control for coach variability among others.   As I have stated before, AI coaching chatbots provide a wonderful simulation laboratory to investigate these difficult-to-study human coaching aspects. This notion inspired the present study where we created 3 AI coaching chatbots that each used one of the three most popular coaching approaches: GROW, Solution Focused and CBT. We conducted the “gold-standard” randomized controlled study using close to 600 participants.  We measured goal attainment, working alliance and technology adoption over two time points 1 week apart.   The results show that the CBT-based chatbot outperforms the other two, even though it arguably demands high cognitive engagement from the user and works on a deeper level. To me this suggests that people are willing to engage on deeper levels with AI than we thought. I also love the fact that we now have more and important empirical evidence to guide the way we design AI coaching chatbots. And the fact that this study adds to our understanding of how AI coaching differs from human coaching. I think this finding can potentially shape the way AI coaching chatbots are designed going forward.   Keep in mind that all studies have limitations and that all results and findings must always be interpreted within the limitations and scope of a study.   Thank you to EMCC Global for sponsoring this study and to my co-researchers Rebecca Rutschmann and Jonathan Reitz, MCC, ACTC . With more sponsorships and collaborations like this we can more rapidly expand our current limited understanding of AI coaching.   Let’s keep researching!   You can read the paper open access here:   https://lnkd.in/dsBzHukC International Coaching Federation EMCC UK Stellenbosch Business School Stellenbosch University

🤖 𝐀𝐈 𝐂𝐨𝐚𝐜𝐡𝐢𝐧𝐠 𝐓𝐨𝐨𝐥𝐬 𝐖𝐨𝐧’𝐭 𝐑𝐞𝐩𝐥𝐚𝐜𝐞 𝐘𝐨𝐮… 𝐁𝐮𝐭 𝐓𝐡𝐞𝐲 𝐂𝐚𝐧 𝐒𝐮𝐩𝐞𝐫𝐜𝐡𝐚𝐫𝐠𝐞 𝐘𝐨𝐮 🚀 Let’s be honest: AI is everywhere. Your inbox. Your LinkedIn feed. Your calendar. And now—it’s showing up in sales coaching. Some sales leaders lean in. Others lean back. But here’s the truth: ignoring AI coaching tools means leaving results (and revenue) on the table. The Old Way vs. The New Way ❌ Old way: Weekly pipeline reviews where managers spend 80% of the meeting just trying to understand the numbers. ❌ Old way: Coaching “from the gut,” hoping your instincts are right. ❌ Old way: Sales reps keeping their struggles hidden until it’s too late. ✅ New way: AI-powered dashboards surface exactly where deals are stuck. ✅ New way: Call analysis tools flag missed cues in real time. ✅ New way: Personalized coaching insights go straight to the rep—every day, not once a week. ↳ Which one do you think drives faster growth? 𝐖𝐡𝐲 𝐈𝐭 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 AI tools aren’t about replacing coaches. They’re about amplifying coaching impact. Imagine this ⇢ Instead of chasing down spreadsheets, you walk into a one-on-one already knowing: - Where a rep loses momentum in discovery calls 🎯 - Which deals are at risk because of stalled next steps ⚠️ - Who is thriving and ready for the next challenge 🏆 That’s not guesswork. That’s coaching with precision. 𝐇𝐨𝐰 𝐭𝐨 𝐓𝐚𝐤𝐞 𝐅𝐮𝐥𝐥 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞 Here’s where most leaders stumble: they get the tool, but don’t change their process. AI only works if you work it. Here’s the play: 𝟏. 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞, 𝐝𝐨𝐧’𝐭 𝐢𝐬𝐨𝐥𝐚𝐭𝐞. ↳ Don’t let AI sit in a corner. Build it into your weekly rhythm. 𝟐. 𝐂𝐨𝐚𝐜𝐡 𝐭𝐡𝐞 𝐜𝐨𝐚𝐜𝐡. ↳ Managers need training on reading AI insights and translating them into action. 𝟑. 𝐊𝐞𝐞𝐩 𝐢𝐭 𝐡𝐮𝐦𝐚𝐧. ↳ AI gives data, but people create trust. Balance cold numbers with warm conversations. 𝟒. 𝐂𝐞𝐥𝐞𝐛𝐫𝐚𝐭𝐞 𝐩𝐫𝐨𝐠𝐫𝐞𝐬𝐬. ↳ When AI shows a rep improving their talk-to-listen ratio, call it out. Wins fuel momentum. 𝐓𝐡𝐞 𝐇𝐮𝐦𝐚𝐧 𝐒𝐢𝐝𝐞 Here’s the thing nobody tells you: reps actually want this. Why? Because AI tools take the mystery out of performance. No more “I think you’re not asking enough questions.” Instead ⇢ “The system shows you asked 2 discovery questions in 15 minutes. Let’s work on getting that to 5.” Clear. Actionable. Fair. That builds trust. And when trust grows, performance skyrockets. 💡 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: AI coaching tools are not a threat. They’re a multiplier. The leaders who embrace them aren’t just keeping up—they’re pulling ahead. The reps who use them aren’t just improving—they’re accelerating. The future of coaching isn’t AI or human. It’s 𝐀𝐈 + 𝐡𝐮𝐦𝐚𝐧. That’s where the magic happens. ✨ 👉 What about you? Are you experimenting with AI coaching tools yet—or still skeptical?

So What’s next? How do we address the challenges I’ve discussed over the past few weeks? 💡 AI could be the answer! 💡 Yes, the very tool that some coaches fear could actually be the key to showcasing a coach’s true impact. 📍 Track Language Shifts: AI tools can analyze client conversations to identify “change talk”—phrases that signal a shift in mindset, such as “I think I could start walking more” or “Maybe I should start eating healthier.” These subtle language cues can help measure a client's movement through stages of change. 📍 Evaluate Behavioral Changes: AI can also track behavioral shifts in the program such as engagement levels in the app, data entries, or interactions with content. For example, if a client starts logging their daily activity or reading content on healthier habits, these actions signal progress even if clinical outcomes like weight loss haven't occurred yet. 📍 Comprehensive Progress Tracking: By analyzing both language and behavior, AI provides a more complete picture of a client’s progress—helping coaches gauge readiness and effort beyond just the clinical metrics. 📍 Redefining Success: AI allows us to move beyond focusing solely on short-term clinical outcomes and create more meaningful, holistic metrics. This approach provides a more accurate representation of a coach's true impact and helps organizations better understand the value of coaching over the long term. 📍 Scaling Caseloads: AI tools can help scale caseloads by efficiently analyzing client interactions, language and behaviors, making it easier for coaches to manage larger caseloads while maintaining personalized coaching support. Also allowing Operational Leaders to better understand workload for coaches and utilization. 📍 Improving QA Efficiency: AI could also support QA work by automatically reviewing coaching interactions and client progress, allowing coach leaders to perform quality assurance more effectively and uniformly. It can identify coaching strengths and areas for improvement, reducing the time spent on manual reviews and ensuring consistency across the team. As AI continues to evolve, it has the potential to revolutionize how we measure progress—providing a more nuanced understanding of the client’s journey, enabling scalable caseloads, and streamlining QA processes. ✅ By measuring these insights, we can develop more effective performance metrics! 👉 I understand that many start-ups may not yet be in a position to implement AI tools into their product, but that doesn’t mean we can’t take some action. 🌟 In my next post, I’ll talk about some manual strategies to accomplish the above goals and how we can overlay this information with long-term health outcomes to better demonstrate true coach impact and ROI. Stay tuned!

Personalized 1-on-1 coaching is powerful but virtually impossible to scale. AI can close this gap by delivering fast feedback, unlimited retries and zero performance anxiety.   This award-winning research by Ishita Chakraborty, Khai C., Dr. Howard Dover and K Sudhir found that AI could detect a human’s persuasion skills from a conversational video, improving feedback by 40%, or 67% when working with a human expert. Better still, it highlights the why: interactivity (active listening), body language (open posture) and focus (customer’s needs instead of product features).  Most companies use this for 𝘴𝘢𝘭𝘦𝘴 𝘤𝘰𝘢𝘤𝘩𝘪𝘯𝘨 given strict state and EU-level regulations on AI for interviews. Some key watchouts for leaders:  • 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Users will behave differently if the AI will influence reviews or pay.    • 𝗕𝗲 𝘁𝗿𝗮𝗻𝘀𝗽𝗮𝗿��𝗻𝘁 𝗮𝗻𝗱 𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰: Explain what the AI is watching, how it will and won’t be used.  • 𝗣𝗮𝗶𝗿 𝘄𝗶𝘁𝗵 𝗵𝘂𝗺𝗮𝗻𝘀: AI coaches lack market nuances that managers bring. Done well, AI + human coaching can create a continuous, data-driven development cycle for sales teams. #Coaching #SalesTraining #SalesEnablement #Persuasion #FutureOfWork

In exploring paths for coaching, virtual coaching is a newer and unexpected force delivering substantial benefits beyond simple convenience. On the latest episode of The Future of Teamwork, my guest Reggie Jeffries, M.A. and I delved into how virtual coaching platforms are revolutionizing learning by providing efficient and accessible opportunities for diverse groups from various companies and industries. The secret to successful virtual coaching? Engaging and interactive sessions. Aim for a coach who fosters active participation by leveraging creative technology and innovative session designs, ensuring every participant is involved. Reggie does this by innovating beyond traditional webinars. He integrates real-world case studies into breakout rooms, employs interactive tools like word clouds, and schedules 'brain breaks' to maintain high energy levels. This strategy fights virtual disengagement and significantly enhances the learning process. Reggie’s journey to redefine virtual coaching is driven by a commitment to offer experiences that are both informative and engaging, pushing the limits of traditional learning environments. What are your thoughts and experiences with virtual coaching and training? How do you make your sessions stand out? Share your ideas and questions below! #VirtualCoaching #Teamwork #Innovation #Engagement #Learning