AI In Professional Roles

The Mastering Technical Sales Future Sales Engineer Report is now available (link in comments below). A huge thank you to the SE leaders based across the globe who contributed their time and insights to help shape this report. Across the in-depth interviews, one theme stood out: the Sales Engineer role is evolving faster than ever. Customers are more informed, buying cycles are more complex, and AI is transforming how SEs prepare, research, and engage customers. In the report, we propose that tomorrow’s SE will be: 𝗔 𝗩𝗮𝗹𝘂𝗲 𝗖𝗼 𝗖𝗿𝗲𝗮𝘁𝗼𝗿 – designing 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘪𝘷𝘦 solutions with customers, the customer had previously not thought was possible (or perhaps about!) 𝗔 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗜𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝗿 – orchestrating 𝘤𝘰𝘭𝘭𝘢𝘣𝘰𝘳𝘢𝘵𝘪𝘰𝘯 across the customer, internal teams, and partners 𝗔 𝗧𝗿𝘂𝘀𝘁𝗲𝗱 𝗔𝗱𝘃𝗶𝘀𝗼𝗿 – one of the final decision points for customers, when everyone can sound intelligent in an AI world, 𝘢𝘶𝘵𝘩𝘦𝘯𝘵𝘪𝘤𝘪𝘵𝘺 becomes a differentiator. The report covers: • How customer buying behaviour is changing and the impact on the SE role • What high-performing SEs do differently • AI and the evolving SE role • The Top 10 things SEs should stop doing (𝘩𝘢𝘷𝘦 𝘧𝘶𝘯 𝘸𝘪𝘵𝘩 𝘵𝘩𝘢𝘵 𝘰𝘯𝘦!) • What SE leaders are prioritising for 2026 and beyond • The skills and behaviours that will define the future-ready SE If you have reflections on the findings, we would love to hear them in the comments below. If you are exploring how to build future-ready SE capability, we would be glad to connect. #salesengineer #thefuturese Up 2 Speed

If you use GenAI… I want to hold you… accountable. As AI becomes a key tool in legal practice, ensuring ethical use is critical. This condensed framework is based on ABA guidelines and other regulatory standards, balancing efficiency with accountability. 1. Competence Lawyers must understand AI’s capabilities and risks, such as inaccuracies or biases. Regular training is crucial for staying updated. 2. Confidentiality Client data must be protected when using AI tools. Anonymize sensitive data and ensure AI systems are secure. 3. Transparency Lawyers must inform clients about AI use, particularly when it impacts legal services or fees, fostering transparency and trust. 4. Verification of Outputs AI-generated outputs must be reviewed for accuracy to avoid errors like false citations, ensuring the integrity of legal work. 5. Reasonable Fees Fees must be reasonable and reflect the actual work performed. When using AI, this means that lawyers can charge for tasks like inputting data into AI tools and verifying the AI-generated results. However, lawyers should not bill clients for time saved due to AI’s efficiency, unless the client has specifically agreed to this arrangement in advance. This ensures transparency and fairness in billing practices. 6. Addressing Bias Firms should actively mitigate AI biases that could lead to unfair outcomes, particularly in sensitive legal areas . 7. Supervision Supervisory lawyers must ensure that AI use complies with ethical standards, implementing policies and training to manage AI responsibly.

At this rate, court documents could end up looking like all our Linked In feeds within the month (that is, mainly AI-generated nonsense). This time, Google Scholar conjured up fictitious case citations and the solicitor who used the tool didn’t verify them. The supervising principal also failed to check the work before filing. ✅ Result? A costs order ❌ But no further disciplinary process. 🔍 Key takeaways 1️⃣ AI governance is key in law firms This isn’t just about banning AI. AI governance means setting up clear internal guardrails around how lawyers, particularly juniors, can use AI tools. That includes: ⭐ Clear policies and procedures ⭐ Role clarity around who can use AI for what ⭐ Staff training on AI risks ⭐ Defined review and sign-off protocols ⭐ Escalation processes for uncertain outputs 2️⃣ Professional obligations don’t vanish Lawyers have duties of competence, honesty and candour, including ensuring any submission to a court is accurate and properly sourced.Using AI to assist drafting? Absolutely. Relying on it uncritically and skipping verification? Not acceptable. AI is a tool, not an excuse. 3️⃣ Supervision is critical Let’s be fair: junior lawyers (and senior ones mind you!) will make mistakes. It’s how they learn. That’s exactly why the LPUL places a strong emphasis on the duty of supervision. This case invites reflection on how that duty is exercised in practice. Are our current systems, workloads, and expectations set up to support meaningful supervision, especially when new technologies are involved? It’s not about blame, but about ensuring we’re creating an environment where quality, accountability and professional development can all coexist. 4️⃣ Integrity and the message we send matters A key aim of the LPUL is to uphold public confidence in the legal profession. As AI becomes more embedded, we’ll increasingly need to grapple with how to respond when things go wrong, especially in court settings. This isn’t about being heavy-handed. But it’s worth reflecting on what message is conveyed when fabricated material makes it into court documents. Even when unintentional, these incidents raise questions about how we maintain professional standards in an AI-enabled world. 5️⃣ Don’t ban AI, govern it AI can support efficiency, reduce costs and improve access to justice. I’m a strong advocate for responsible adoption. But as we see more examples of AI being misused, it raises questions about how we ensure appropriate safeguards and accountability across the profession. Good AI governance isn’t about stifling innovation. It’s how we make innovation sustainable, ethical, and fit for purpose. Final thought: AI isn’t the threat. But how we manage it might be. This is a reminder that we need systems, guidance, and expectations that reflect the very real risks AI brings. Plenty for the profession and the regulators to reflect on. #AIGovernance #LegalEthics #ProfessionalStandards #ArtificialIntelligence #LegalInnovation

Are you verifying and critically evaluating the output of AI before accepting it? A recent study by Carnegie Mellon University and Microsoft Research that focused on knowledge workers and how they interact with AI-generated content in the workplace found that using AI can lead to diminished critical engagement – but only for certain workers and certain kinds of tasks. ➡️   For routine or lower-stakes tasks, 62% of participants engaged in less critical thinking when using AI. ➡️   Those who had greater confidence in their expertise were 27% more likely to critically assess AI outputs instead of accepting them at face value. “More likely to critically assess” means: 💡 𝐅𝐚𝐜𝐭-𝐜𝐡𝐞𝐜𝐤𝐢𝐧𝐠 𝐀𝐈 𝐨𝐮𝐭𝐩𝐮𝐭𝐬 by cross-referencing external sources. 💡 𝐀𝐧𝐚𝐥𝐲𝐳𝐢𝐧𝐠 𝐛𝐢𝐚𝐬𝐞𝐬 that may be present in AI-generated information. 💡 𝐄𝐝𝐢𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐫𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐀𝐈-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐜𝐨𝐧𝐭𝐞𝐧𝐭 to better align with context and objectives. 💡 𝐔𝐬𝐢𝐧𝐠 𝐀𝐈 𝐚𝐬 𝐚 𝐛𝐫𝐚𝐢𝐧𝐬𝐭𝐨𝐫𝐦𝐢𝐧𝐠 𝐭𝐨𝐨𝐥 rather than a definitive answer generator. Employing less critical thinking meant AI-generated content was copied and used without verification, or relied upon decision-making without questioning logic. In these cases, users were assuming accuracy without contextual understanding. 𝑾𝒉𝒂𝒕 𝒅𝒐𝒆𝒔 𝒕𝒉𝒊𝒔 𝒎𝒆𝒂𝒏? 🚨  Knowledge workers who use AI when junior in their careers, and especially when engaged in lower value work without understanding its context, are more likely to rely on it without verifying or questioning output. 📖 Those who are senior enough to understand the context and have confidence in their own knowledge will verify and check AI output before using it or relying on it. 𝑾𝒉𝒂𝒕 𝒅𝒐𝒆𝒔 𝒊𝒕 𝒎𝒆𝒂𝒏 𝒇𝒐𝒓 𝒕𝒉𝒆 𝒍𝒆𝒈𝒂𝒍 𝒊𝒏𝒅𝒖𝒔𝒕𝒓𝒚? Training and education is more important than ever before. Junior lawyers will be disproportionately more affected by this shift in critical thinking. The fact is they will be using AI for work whether or not your workplace has a policy in place or even whether it has licensed an AI solution. To ensure responsible use of AI, and encourage independent thought in your lawyers: ✅ Provide regular education on why verification, analysis, and refinement of AI output is necessary (and write this into your policies on AI use), ✅ Don’t sleep on lawyer training that reinforces the importance of understanding context and asking good questions, ✅ Train senior lawyers to evaluate junior work more critically, recognizing that AI may have a played a part in its creation. ✅ Encourage supervisors to share context with juniors when instructing them. ✅ Regardless of your seniority, if you are a lawyer or legal professional engaged in routine tasks, remind yourself to remain critically engaged if you're using AI. This applies to small firms or legal departments just as it does to large. Link to study in comments. #law #artificialintelligence #GenAI #lawyers

I asked Chat GPT 4.1 to create an outline for young lawyers on how to use AI: Outline: How Young Lawyers Can Use AI in Legal Practice I. Introduction • What is AI? • Brief explanation (tools that simulate human reasoning and language skills). • Why use AI? • Improve speed, accuracy, and efficiency. ⸻ II. AI Basics Every Lawyer Should Know • Common AI Tools for Lawyers: • Legal research platforms (e.g., Westlaw Edge, Lexis+ AI tools) • Drafting tools (e.g., contract and brief generators) • E-discovery and document review tools • Practice management AI (e.g., calendaring, billing, client management) • Generative AI (e.g., ChatGPT, Copilot, Harvey) ⸻ III. Everyday Uses for AI in Law Practice • Legal Research • Fast answers to legal questions • Summarizing cases and statutes • Drafting and Reviewing Documents • First drafts of motions, contracts, discovery • Spotting errors or inconsistencies • Client Communications • Drafting routine emails and letters • Case Strategy • Timeline generation • Identifying case trends or weak points • Litigation Support • Analyzing discovery responses • Predictive analytics for settlement or trial outcomes ⸻ IV. Ethical and Practical Considerations • Confidentiality • Never share client names or sensitive details with public AI tools • Accuracy • Always check AI work—don’t rely blindly • Bias • Understand and watch for possible algorithmic bias • Disclosure • Know when you must disclose AI use (check your state bar rules) • Billing • Be transparent if you use AI to save time on a client file ⸻ V. Getting Started • Start Small • Pick one or two tools and get comfortable • Ask for Training • Most firms and vendors offer free tutorials • Experiment on Non-Client Work • Try AI on research, outlines, or your own tasks first • Build Good Prompts • Ask clear, specific questions • Review Output Carefully • Edit and fact-check all AI results ⸻ VI. Pitfalls to Avoid • Blind Reliance • Never submit AI work product without review • Ethical Traps • Don’t upload confidential information • Avoid overbilling for AI-assisted work • Outdated Law • Verify all legal authorities and citations ⸻ VII. Looking Ahead • Stay Updated • Follow developments in AI and legal tech • Get Involved • Join bar committees or groups on technology and AI • Embrace Change • Be a resource for your team on new tools ⸻ VIII. Conclusion • AI is a tool, not a replacement • Use it to enhance—not replace—your legal skills and judgment • Continuous learning is key

⚖️ Will AI Replace Junior Lawyers—or Redefine Their Role? A recent Fortune article cuts to the heart of a question many in legal are quietly asking: as tools like Harvey become more capable, what happens to the junior lawyer? The short answer? It depends on what we choose to value. Harvey and other legal AI platforms are quickly becoming fluent in tasks traditionally handled by associates — case summarization, contract analysis, even drafting. These aren’t just productivity tools anymore; they’re reshaping workflows. But rather than declare the death of the junior associate, this moment invites a reframing: what should the entry point to legal practice actually be? Historically, junior lawyers spent countless hours on repetitive tasks as a rite of passage. But if AI can absorb that work, there’s a chance to accelerate meaningful development — more strategic thinking, client interaction, and judgment-building earlier in a career. Of course, that only works if law firms and legal departments invest in that shift. Otherwise, AI just becomes a cost-cutting measure and talent pipeline risk. For in-house teams, this change is even more immediate. We’re already leaning on leaner teams and expecting more from our tools. But we must also ask: are we mentoring the next generation, or just outsourcing the ladder they were supposed to climb? The future of junior legal talent isn’t written by AI. It’s shaped by how we integrate it. Full article: https://lnkd.in/dUcz4uaF Comment, connect and follow for more commentary on product counseling and emerging technologies. 👇

🤖 AI isn’t coming for tech sales — it’s already here. But it’s not replacing people. It’s replacing and automating sales processes — and multiplying what great sellers and leaders can do. Here’s what’s already rapidly changing: ⚙️ AI-driven SDRs that research, personalise, and qualify prospects at scale. 🧠 Reps now have “AI solution engineers” in their corner — copilots that can demo products and answer technical questions in real time. 🎯 Forecasting is moving from guesswork to predictive accuracy. 🗣️ And leaders are using AI-powered role-play to practise high-stakes conversations and sharpen their coaching. The result? Less admin - more impact. Less firefighting - more foresight. I wrote about how AI is redefining the future of tech sales — and what great leaders are doing about it. What’s your take — is AI an opportunity or a threat to sales leadership as we know it?

AI won’t fully replace Solutions Engineers, but I’m convinced it will advance the role in 3 ways: 1. Knowledge Mgmt - as the connector between sales, customers, customer success, marketing, and product…we get a lot of data points. Sometimes it gets documented, other times it’s shared in slack. Little pools of tribal knowledge and scattered documentation prevent SEs from scaling. Feeding and training AI is an easy way for knowledge mgmt to no longer be a massive headache. 2. Pre-Sales OS - think about how much time each week we waste updating notes, salesforce, slack, notion, and 16 other documents…all with the sales information. CRMs were create as the single source of truth for sales, but SE teams need their own workflows and systems (that seamlessly sync to the CRM). AI can easily update notes, create summaries, and even raise risk in POVs early. 3. Coaching - call recording and AI transcription changed the game for sales teams…now AI is advancing enough to the point where it can listen to our demos and provide feedback for us (SEs). Are we hitting the right value points? Did we capture pain points? AI coaching is a great way to help us level up. AI is definitely changing the way we work, but it’s nothing to be afraid of. The next evolution of pre-sales teams are going to use AI to their advantage to reduce wasted time and focus on being more strategic. #sales #presales #cybersecurity #b2bsales

The recent Harvard study on the impact of AI on hiring has significant implications for the legal profession. Starting in Q1 2023, firms adopting generative AI saw a sharp decline in junior employment compared to non-adopting firms. In contrast, senior employment in AI-adopting firms continued to rise. The impact on junior workers from elite institutions (e.g., top-tier university graduates) were less affected. https://lnkd.in/eEZ-xJ8M The impact mirrors my experience with legal analysis and writing. AI can find what you would traditionally have asked a junior lawyer to find for you. But, AI lacks, at least for now, the ability to provide high value insights, provide even basic legal analysis or assess the value and veracity of sources. It certainly cannot write a persuasive brief. (More basic job functions, such as scheduling hotels and flights are still best by people too - but they are not lawyers.) The study's finding mirror those of a recent Stanford study. Canaries in the Coal Mine? https://lnkd.in/en4nwPE5 It will be interesting to watch law firm hiring over the next few years.

My first time using AI for legal work? I thought I'd discovered the holy grail. Picture this: Me, sitting back with my third cup of coffee, watching AI draft contracts while I planned my early retirement. The future had arrived. Then reality punched me in the face. The AI-generated contract had three typos, two missing clauses, and one paragraph that read like my 5-year-old nephew wrote it after too much sugar. That was my wake-up call. But here’s what I learned after that mess: → AI is not magic. It’s a tool. → It can save time, but only if you know where to use it. → Human oversight is still the secret sauce. In my law firm, we started small: - Used AI for document review (not drafting the whole thing) - Piloted tools on real cases before rolling out firmwide - Trained our team so nobody felt left behind I told my staff: “If the AI messes up, blame me. Not the robot. We’re learning together.” One rule always remain: • Always check AI’s work-twice The big shift? Culture. Some people love new tech. Others want to run for the hills. I had to remind everyone (myself included) that AI is here to help, not replace. My takeaways for law firm owners and entrepreneurs: 1️⃣ Start small. Don’t try to automate everything at once. 2️⃣ Train your team. Skills matter more than shiny tools. 3️⃣ Keep humans in the loop. AI is smart, but people are wiser. P.S. The best results I’ve seen came when we mixed AI speed with human judgment. Not one or the other. P.P.S. If you’re waiting for AI to “fix” your business, you’ll be waiting a long time. Use it to build, not to hide. How are you using AI in your practice or business? Let’s swap lessons.