How Salespeople can Use AI for Client Insights

Microsoft’s wake-up call to Sales Harry Stebbings shared in a tweet today the reality of sales in 2025: “Microsoft’s layoffs weren’t a ‘replaced by AI’ story; they were a ‘replaced by better people’ story.” Facts… Microsoft (and many other companies) can’t afford sending generalist sales reps to get deals done. Especially big deals. Doesn’t work. They kept the solution engineers who knew the product inside and out, and partnered with strategic sales professionals. This isn’t about technology taking your job. It’s about your job evolving faster than you are. Too many AE’s get blindsided because they thought showing up with a feature dump and a smile would still work. That approach now carries massive risk. High chance of no deal, and if you do win, it’s probably a tiny one with a high probability of churn. Not likely you’ll achieve your quota that way. The AEs who survived operate differently - They stopped slinging software and started studying their prospects & customers business. The markets they play in. The ones still standing are: • Reading customer 10-Ks and earnings calls (not relying on legacy CRM notes) • Understanding business constraints, not just pain points • Engaging with the entire team of stakeholders-business group, operations teams, and executives - not just their primary contact • Partnering with SEs as strategic advisors, not just demo drivers. Sales is the “why”and “why now” - in business terms SEs show the “how it’s done” - in business terms • Speaking ROI and business outcomes, not feeds and speeds Here’s where AI plays a key role. Top AEs leverage technology to: • Analyze customer financials faster than ever • Prepare for calls with deeper insights • Research stakeholder backgrounds and priorities • Generate business case scenarios based on customer and market data • Free up time for the high-value conversations that matter Sales leaders are using these tools to: • Identify which AEs are engaging strategically vs. just staying busy. • Lead scoring and routing • Automating low-value tasks • Team composition That visibility is the foundation for optimizing GTM. Provides opportunities to coach and help mitigate risks. Transforms savvy managers into strategic leaders. (Follow Kyle Norton and Kevin "KD" Dorsey - bosses on how to leverage AI). Your job isn’t safe if you’re still operating like it’s 2019. But it’s (more) secure if you’re willing to become what customers actually need: A business advisor who happens to sell software, not a software seller who happens to know some business. The generalist spray-and-pray approach just got expensive. Microsoft proved that. The question isn’t whether this shift is coming to your company. The question is: Are you ready? What did I miss? What are you seeing in your market? Are the fundamentals of selling really changing this fast?

Inspired by a post from Vin Vashishta, I decided to comment on it a genAI use case we've been tackling lately, which seemed to have sparked some thoughts with others who have then reached out asking further questions. I believe that AI notetakers are by far the biggest 2025 secret weapon to uncovering VALUABLE generative AI use cases, and scalable agentic workflows (and I'm shocked that more companies haven't fully realized this, yet...) below is a simple playbook/diagram that will explain my thoughts on why: → Build a proprietary AI notetaker: Invite it to every internal and external meeting. Let it capture every insight, question, and feedback point. Store all transcripts in a backend database with encryption and configured data usage rules for deeper analysis. → Train a company-specific LLM: Funnel these transcripts into your LLM, fine-tuned for pattern detection and insights. For a sales use case, tag your transcript uploads by signaling outcomes like which meetings led to closed deals and which did not. Let the LLM uncover blind spots—like overlooked objections, key phrases that resonate, or missed opportunities in your proposal readouts. → Discover transformative insights: Find patterns in question sequences, objection handling, and narrative structures that convert clients. Enrich your dataset w/ personas to your dataset, learning exactly what your clients really want. And also... assess your workforce lol how skilled are the consultants that you're paying ($$$) for in real-time? Where can they improve? → Build a scalable, agentic workforce & iterate: Deploy agents that can be available 24/7 to your clients, agents that can train your junior staff and prepare them for more senior level roles/projects. Focus on creating that feedback loop powerhouse, continuously improving and delivering what clients need and what your workforce needs and your business will evolve, amplifying human performance and driving growth. 💡If anything, just remember this..... 1) AI notetakers are the ears. 2) Documentation transcripts are the memory. 3) AI agents are the brain. In 2025, companies who adopt this methodology will lead BIG TIME. Those who don’t... well, I think they will be wondering how they fell behind. Curious to hear others thoughts on this. #AI #AgenticAI #Agents #ArtificalIntelligence #GenAI #GenerativeAI #LLMs #UseCase #LLM

Most people building GTM tooling are obsessing over third-party data. But, there is a goldmine of information in every company’s systems already: customer conversations, emails, and meeting transcripts. The problem is - this data sits dormant (becoming less useful over time as it collects dust in the corners of the CRM or CDW or otherwise) and is distributed across disparate systems and “objects.” Attention is activating this data. Mining for the interesting nuggets and then operationalizing them, in real-time. That’s the vision they’re realizing, by building a system of AI agents that don't just capture sales conversations—they automate the work traditionally done by the best enablement analysts, RevOps specialists, and top performers. The goal? Help GTM orgs achieve 10x results with just 10% of the workforce. This is super exciting to me, which is why I was stoked to spend some time with Anis Bennaceur, Co-founder & CEO of Attention, recently. And I put together a deep dive post on The Signal. I agree with Jeff Bezos' analogy of AI being like electricity ("it will be everywhere, in every application"). For example, here are 9 ways a GTM team could leverage AI/Attention: 1/ One-click sales collateral generation: After a discovery call, automatically create a tailored sales deck that incorporates the prospect's specific pain points, business goals, and objections mentioned during the conversation. 2/ Competitive intelligence automation: Receive weekly reports on competitors mentioned in deals, including how they're perceived, their positioning, and the frequency of mentions—all without manual analysis. 3/ Closed-won/closed-lost analysis: Instead of spending days manually reviewing won and lost deals, get comprehensive insights in minutes on why deals are succeeding or failing. 4/ Automated call scoring: Evaluate rep performance based on best practices without requiring managers to listen to hours of calls. 5/ Cross-selling opportunity identification: Automatically identify and route opportunities mentioned in conversations that might be relevant to other teams or products. 6/ Business case generator: The agent compiles a comprehensive business case document based on all conversations with an account, extracting the specific pain points, quantifying the impact, and building a compelling ROI model. 7/ Content gap analysis: Identify questions from prospects that reps struggle to answer effectively, highlighting needs for new content or training. 8/ Outbound signal detection: Extract compelling events from prospect conversations to inform outbound strategies, like "Company X just lost their growth marketing manager and needs to get pipeline back in order." 9/ Brand perception tracking: Monitor how your positioning against specific competitors evolves over time, with insights drawn directly from customer conversations. The possibilities are endless. Check out the full article now: https://lnkd.in/g85JNmdj

We hear from customers who are interested in using the power of AI to help their sales team scale their business. Internally, AI is one of the tools that Amazonians use daily to improve our productivity and do things faster and more efficiently. In that vein, our latest ML blog gives a great inside look at how AWS sales teams are using Account Summaries—one of our first production GenAI use cases built on Amazon Bedrock. Account Summaries help us stay customer obsessed by generating 360-degree views of an account, available on demand and delivered proactively ahead of meetings via Slack. They integrate both structured and unstructured data, including key metrics, real-time web data, ML insights and AI-driven recommendations. Since its internal rollout last year, more than 100,000 summaries have been generated by our sellers, saving them 35 minutes per briefing. Check out our ML blog to learn how Account Summaries are helping our field teams scale and deliver better customer outcomes. https://lnkd.in/gTee4agv Here’s part of a sample output from Account Summaries:

LinkedIn's new Sales Navigator updates are transforming the sales process. Lead IQ and Enhanced Account IQ are perfect examples of how AI is becoming essential for modern sales teams. These tools are practical and powerful: Lead IQ provides personalized insights for decision maker. Account IQ offers key account updates to refine your strategy. I've been leveraging these features primarily to: Prepare for pre-call notes, saving time before crucial discovery or intro calls. Summarize insights in my CRM, ensuring I'm ready for follow-ups and future conversations. Here's the reality: AI in sales isn't slowing down. Over the next 5-10 years, these tools will become indispensable for sales and revenue leaders looking to scale smarter and faster. It's no longer a question of if you should adopt AI, but how quickly you can integrate it into your processes. The teams that embrace these technologies now will have a significant advantage in the coming years. They'll be able to move faster, close deals more efficiently, and provide better value to their clients. Have you tried Lead IQ or Account IQ in Sales Navigator? I'm curious to hear how you're using them and what impact they've had on your sales process. Share your experiences in the comments. Let's learn from each other and stay ahead of the curve in this rapidly evolving landscape.

Navigating AI tools can be daunting, especially for those who are new to it. Many of our clients have shared their struggles in adopting GenAI models for new business development. Their blockers range from psychological barriers, such as fear of the unknown, to privacy and security concerns to simply not knowing where to start. If you're feeling the same way, trust me, you're not alone. If you're not leveraging AI for sales yet, let's fix that! 🌟 I want to share a very simple, practical step for B2B sellers to dip their toes into AI. Start by using AI to research your prospective clients. Here's how: **Use AI for client research** Pick any AI model that you have an account with —ChatGPT, Perplexity, Gemini, or Claude—and ask it to create a comprehensive profile of "Company XYZ" including a brief history, mission, values, key products or services, market position and recent news or developments. Review the response. If it's not what you are looking for or if it's not useful to you, redirect the model with follow-up questions. Ask it to dive more deeply into a particular area you are interested in. The beauty of these models is that they don't get tired or annoyed by multiple iterations. You can refine and adjust until you get the information you need. Start small, stay curious, and most importantly, have fun with it! Here's to kicking off your AI journey. 🚀 #AI #Sales