AI Tools For Communication

Should AI Assistants Join Team Check Ins And Decision Reviews? I have been turning this question over in my mind because it looks simple from a distance. Let AI listen. Let it improve decisions. But once I tried it myself, the whole conversation changed. The summary they produce is technically perfect, yet I often feel a strange disconnect. The AI highlights moments I would not have highlighted. It filters silence as irrelevant even though the silence might carry tension. It captures facts, but not the emotional weight. That is when it hit me: AI does not record meetings. It interprets them. Which means it quietly shapes how teams remember what happened. Here is the deeper layer most people miss: • Teams do not act on the meeting itself • They act on the memory of the meeting • And whoever controls the memory, controls the narrative So when AI joins a check in, it does not just help. It becomes the unofficial historian of the team. In my opinion, this changes the entire dynamic. People start speaking in ways that “sound good” in transcripts. Riskier ideas shrink because they look messy when written down. And over time, the AI’s version of reality becomes more influential than the people in the room. What this really means? Once AI becomes the memory of the team, it also becomes the first draft of the team’s meaning. And meaning shapes culture far more than accuracy ever will. So here is what, I believe, leaders should actually do: ✔ Allow AI to attend, but only as a recall tool ✔ Let humans annotate summaries so the emotional context is not erased ✔ Define what the AI should never record, to protect psychological safety ✔ Make it a habit to question the AI’s emphasis, not only its correctness ✔ Keep narrative authority human, even if memory becomes machine assisted In my view, the real question is not whether AI should be present. It is whether we want our teams to think with AI, or eventually think like AI. If AI becomes the keeper of every meeting, how long before teams unconsciously reshape themselves to fit the way the system listens? #FutureOfWork #AILeadership #TeamDynamics #AICulture

Anthropic just shipped Skills, Microsoft 365 integration, and enterprise search for Claude. After talking to dozens of enterprise companies this year, I think they're solving the right problems. 💰Context tax is killing enterprise AI adoption. Most AI tools require you to manually gather information before asking useful questions. You're copying emails, uploading documents, explaining organizational context. The AI might be smart, but you're doing all the integration work. Claude's Microsoft 365 connector changes this. Direct access to SharePoint, Outlook, Teams, and OneDrive means the AI already knows what your organization knows. Ask about Q3 strategy, and it pulls from the actual discussions, documents, and decisions. They also launched Skills — reusable instruction bundles that work across Claude's web app, API, and command-line tool. Think of these as expertise packages—instructions, scripts, and resources Claude loads on-demand. And lastly, the new Enterprise search is a shared project that searches multiple connected tools simultaneously. One query pulls information from HR docs in SharePoint, email discussions in Outlook, and team guidelines from various sources—then synthesizes it into a single answer. Model providers like Anthropic and OpenAI are realizing that enterprise AI needs to be operational, not just conversational. Less chatbot, more sidekick that accesses your actual systems and takes action.

We used to attend meetings to experience the conversation. Now we attend them to receive the summary. That shift is bigger than most leaders realize. AI note-takers, recaps, and action-item generators are popping up every day, changing how organizations communicate. And while the efficiency is undeniable…something important may be getting lost. Because leadership communication was never just about information. It was about: • tension • trust • hesitation • conviction • emotional reactions • what wasn’t said AI captures the words. Humans still interpret the meaning. And when leaders stop experiencing conversations firsthand and start consuming compressed summaries instead…we risk losing contextual intelligence. The ability to: • read the room • sense uncertainty • detect emotional shifts • challenge false alignment This is part of what I call Cognitive Atrophy. Efficiency improves. But nuance quietly disappears. And leadership lives in the nuance. As an executive coach, here’s what I’m increasingly telling leaders in the AI era: Don’t outsource presence. Use AI to document meetings. But don’t let it replace: • active listening • emotional observation • curiosity • healthy tension • real-time judgment Because the most important leadership moments happen between the bullet points. The pause. The facial expression. The shift in tone. The Silence after a question. AI may summarize the meeting. But it still can’t fully summarize the human experience inside it. And the leaders who stay deeply present in conversations while everyone else consumes summaries…will have a massive advantage. Because in the AI era, the rarest leadership skill may become...paying attention. Have you ever relied on an AI meeting summary and later realized you missed something important? #ai #meetings #executivecoaching

🚨 AI Emails From the Full Signal Chain live in Warmly! Problem: Email sequences aren't personalized with signals Solution: Trigger AI emails to prospects if your Inbound Agent fails to convert or based on any signal. Backstory: A few months ago I pulled our own inbound report and watched 4 out of 5 qualified hand-raisers die in a generic nurture sequence written three quarters ago by someone who's not at the company anymore. It's not anyone's fault really. We all need to move fast and our marketing team can only do one thing at a time. The bottle neck is constantly moving, but so are our buyers. B2B email has always been a timing and relevance problem. Our old way of assigning signals to templated emails was too generic and goes stale the next week. A lot of our emails going out referenced the wrong price or a different feature set we no longer supported. Even if we got the signal right and sent the email at the right time, sometimes a generic email at the right moment is worse than no email at all. The high-intent moment is precious. Burn it once with a templated email and the prospect learns to ignore you. I didn't even realize that we "spent" the highest-value moments in our funnel on the lowest-quality messages. So we built AI Emails powered by the full signal chain we've been building for four years. No more templates! Drop the step into any orchestration. Some examples we use: - Inbound chat follow up: a qualified chat engager doesn't book. The AI writes the follow up from the chat log. - Intent Trigger: Bombora flags a research surge about "chatbots." AI outreach references case studies in their industry for optimizing website conversion. - Job change: Head of marketing champion moves to a new role. AI sends a welcome and intro at the new account. - Social engagement: Buyer likes a competitor's social post about website de-anonymization. They get an email about how we have the highest identification rates The agent retrieves the full signal chain on every send: chat transcript (when there is one), every page visited that session, enriched person and company data, CRM stage, and any second or third-party signal already on the account. Then it writes the email. You can see what the agent will spit out before each deploy and iterate on the example scenarios until the email reads the way you'd write. After we started implementing this into our signal orchestrator, our reply rates went from 2% to 6% (3x) Setup: open any orchestration, add the AI Email step, set the filter, write the goal and policy in plain English, test, save. Five minutes. Playbooks for each play dropping in the coming days.

🔬 #ArtificialIntelligence 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴: 𝗧𝗲𝗮𝗰𝗵 𝗬𝗼𝘂𝗿 𝗧𝗲𝗮𝗺 𝗜𝗻𝗯𝗼𝘅 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁! 𝗦𝘁𝗼𝗽 𝗱𝗿𝗼𝘄𝗻𝗶𝗻𝗴 𝗶𝗻 𝗲𝗺𝗮𝗶𝗹. 𝗛𝗲𝗿𝗲'𝘀 𝗵𝗼𝘄 𝘁𝗼 𝘁𝗿𝗮𝗶𝗻 𝘆𝗼𝘂𝗿 𝘁𝗲𝗮𝗺 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝗟𝗟𝗠 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘁𝗮𝗺𝗲 𝘁𝗵𝗲 𝗶𝗻𝗯𝗼𝘅. You know the feeling. 100+ emails a day, half of them need sorting, three need immediate action, and the rest? Noise. Your employees waste hours on inbox triage that an AI could handle in seconds—if they knew how to ask it the right way. That's where Context Engineering for Email comes in. 𝗕𝗮𝗱 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 Most people don't realize that a bad prompt sounds like this: ==> "Organize my emails" 𝗕𝗲𝘁𝘁𝗲𝗿 𝗣𝗿𝗼𝗺𝗽𝘁 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 But a good prompt sounds like this: "Review my inbox and categorize each email as: (1) Urgent—needs response today (2) Action—do this week, or (3) FYI—read later. For each, list the sender and main ask in one sentence. Output as a table." 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 See the difference? The second one tells the AI exactly what you want, how to structure it, and how to deliver it. Start with the 3-step framework: 1.     What: Name the exact task ("Summarize this thread so I only read the key points") 2.     How: Tell the AI how to structure the output ("Use bullet points, max 3 bullets") 3.     Why: Give context so it understands the intent ("I need this to spot action items quickly") Then give them a real-world email prompt they can use today: "I receive 50+ emails a day. Create a daily digest that: lists emails needing my direct response (with sender name and action), groups FYI updates by topic (no more than 3 lines per group), and flags anything urgent in red. Sort by priority. Use a simple table format." 𝗧𝗵𝗲 𝗠𝗮𝗴𝗶𝗰 Your team writes this prompt once, reuses it daily, and suddenly has three hours back each week. They'll see immediately how specificity beats vagueness, how structure beats rambling, and how context beats guessing. 𝗧𝗵𝗲 𝗥𝗲𝗮𝗹 𝗪𝗶𝗻 Once they nail email, they use these same skills for proposals, reports, brainstorms, and customer responses. Prompt engineering becomes a career skill, not a party trick. Start this week. Pick one person on your team, walk them through the framework with their actual inbox, and let them build the prompt together with you. Watch them light up when the AI nails it on the first try because they asked the right way. Please follow me for more tips! T. Scott Clendaniel

I attended an online demo day for an accelerator the other day. There were 50 attendees, but only 10 were human. The rest? AI note takers. You've surely come across Otter.ai, Fireflies.ai, Fathom, Granola and tl;dv - AI Meeting Assistant as they are quietly invading our meetings. They record, transcribe, summarise… 📈 The market is booming: - $2.55B projected for AI notetaking by 2033 - 40%+ of users are students - North America leads with 38% market share But with great convenience comes awkward etiquette and serious questions: 🛑 Who gave the bot permission? 🤖 Is it rude to send a bot instead of showing up? 🧠 Are we trading presence for transcripts? AI notetakers are changing the way we work—but at what cost to trust, connection, and communication? I unpacked the trend, market, and privacy concerns in my latest piece (link in the comments)

Most meetings are still inefficient—AI can help In Adcom's Effective Meetings course, we still focus on the essentials: clear agendas, defined roles, and managing challenging dynamics. The updated program now includes practical ways to use AI during and after meetings to drive alignment and decisions. Most tools can auto-capture transcripts, but instead of treating AI as a passive note-taker, we help teams use it as a thinking partner. If your tool doesn’t analyze the transcript, paste it into Copilot or ChatGPT and try prompts like: ▪︎ Highlight any risks, obstacles, or blockers ▪︎ Flag conflicting statements we should resolve ▪︎ Draft an action plan: owner • action • due date • success criteria ▪︎ Compare today’s decisions with last week’s—what changed and why? Last year Lucas Terk and I launched the LinkedIn Learning course Amplify Your Impact with AI, which introduces the fundamentals of writing and thinking with AI. The tips we highlighted —partnering with AI, providing context, and writing clear prompts—are exactly what make meetings more productive. What are YOU doing to leverage AI in your meetings? 

I built an “AI Decoder Ring” with my son to turn messy Slack threads and vague emails into clear checklists, dependencies, and paste-ready confirmations. The post shares the exact prompts, a copy-and-paste template, and a simple Project setup that keeps everything scoped, private, and consistent. If you’re a creative who struggles with organization, this will help you work calmer and faster—read the full story and steal the system.

The new ChatGPT connectors are really useful! Chat can now access Gmail, Google Cal, and Drive, so it can: -Skim unread emails & give a summary -Summarize threads + draft replies -Pull key info from old convos -Do meeting prep + agendas Before I get into some prompts you can copy, quick reminder that enabling connectors gives ChatGPT view access to your private data. I'm an AI power user and it's part of my job to test everything, so personally, I make the sacrifice for the extra features. But please be careful if your job is data-sensitive! 1. Email Intelligence Get ChatGPT to skim your recent unread emails, give you a summary, and rank them in importance: "Summarize all my unread emails in Gmail that I received over the past 48 hours. Rank it in order of importance." 2. Search & Data Extraction Get ChatGPT to find threads and draft in your tone "Find all my emails with [Jennifer], then compare it to my most recent email from [Jennifer]. Give me the takeaways in bullet points. Then, draft a short reply in my tone based on that context." 3. Inbox Memory Get ChatGPT to pull key info from old convos and compare to recent emails: "When is OpenAI DevDay this year and when was it during the previous years (2023, 2024)? What makes this year different. Use a mix of internet information and my email inbox context" 4. Meeting Briefs / Agendas Get ChatGPT to look at your Google Cal and your email to prep for upcoming meetings "Look at my next Google Calendar event. Give me a rundown of the person and the event with context from my Gmail so I come prepared. Also suggest a meeting agenda." I'm just the surface here on how you can use these connectors, but they've been very useful so far as someone who spends hours in my inbox every day If you enable them, I would love to hear your use cases! Will be featuring the top responses in The Rundown (1M+ readers!)

🤖🎙️ When AI Doesn’t Know When to Stop Listening AI notetakers are changing how we document meetings—but they may be doing more than we bargained for. According to the The Wall Street Journal, these tools are capturing private conversations and small talk without permission, sometimes sharing direct quotes from side comments with everyone in the meeting. That’s not just awkward—it’s a trust issue. As HR leaders, this raises critical questions: 🔒 Where is the line between helpful automation and surveillance? 🗣️ Are employees aware when AI tools are recording? 🤝 How do we protect psychological safety in hybrid and digital-first workplaces? Transparency, consent, and etiquette must evolve just as fast as the tech does. ✅ Create clear policies around AI meeting tools ✅ Communicate when and how recordings happen ✅ Train teams on digital boundaries and respectful use of AI AI should make meetings better—not make employees feel like they’re always being watched. Is your organization drawing the line clearly? Read the full article by Ann-Marie Alcántara - https://lnkd.in/eusdDsdd #AIinWorkplace #HRLeadership #DigitalTrust #PrivacyAtWork #EmployeeExperience #FutureOfWork #WorkplaceEthics #HybridWork #AIEtiquette #MeetingCulture