Job Roles Shifting

Salesforce didn’t just promote AEs with AgentForce. They took Solutions Engineers—some of them second-line leaders—and moved them into quota-carrying sales roles. That wasn’t just a hiring decision. It was a signal. For years, SaaS has been built around strict role segmentation. AEs sell. SEs validate. CS retains. Every function has its swim lane, and every team has its handoff. Now it appears Salesforce is collapsing those lanes entirely. If this model works, sales orgs will look completely different in a few years. SEs and technical specialists won’t just support revenue, they’ll own it. AEs will be expected to go deeper on technical execution. Comp plans will shift from closed-won to adoption-driven incentives. Buyers are already losing patience with sellers who don’t understand their own product. This move also eliminates another buyer frustration: countless handoffs to yet another support person. Instead, it gives them one person who can sell them the solution and make sure it actually works If Salesforce is making this move, mid-market SaaS will follow. The question isn’t whether the AE role is changing. It’s whether companies can adapt before they get left behind.

Data Scientists, Engineers, Analysts—these roles are exploding, with data science jobs projected to 𝐠𝐫𝐨𝐰 𝟑𝟔% 𝐛𝐲 𝟐𝟎𝟑𝟏, according to BLS—one of the fastest-growing professions. Meanwhile, according to Gartner 𝟔𝟏% 𝐨𝐟 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 are evolving their data strategies to keep up with AI-driven disruption. But let’s be honest: job titles don’t tell the full story. Here’s what these roles actually do: • 𝐃𝐚𝐭𝐚 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬 – 𝐓𝐡𝐞 𝐁𝐥𝐮𝐞𝐩𝐫𝐢𝐧𝐭 𝐃𝐞𝐬𝐢𝐠𝐧𝐞𝐫𝐬 They design the structure that makes everything else possible—data lakes, warehouses, and pipelines that ensure information moves efficiently and securely. Without them, data would be a tangled mess. • 𝐃𝐚𝐭𝐚 𝐀𝐥𝐜𝐡𝐞𝐦𝐢𝐬𝐭𝐬 – 𝐓𝐡𝐞 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐂𝐫𝐞𝐚𝐭𝐨𝐫𝐬  They don’t just analyze data; they extract value from it. Using machine learning, statistical modeling, and predictive analytics, they turn raw data into business-changing insights. • 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐯𝐞𝐬 – 𝐓𝐡𝐞 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝐅𝐢𝐧𝐝𝐞𝐫𝐬 They specialize in uncovering trends, correlations, and anomalies. Whether it’s identifying fraud, optimizing operations, or finding revenue opportunities, their job is to make sense of the noise. • 𝐃𝐚𝐭𝐚 𝐖𝐡𝐢𝐬𝐩𝐞𝐫𝐞𝐫𝐬 – 𝐓𝐡𝐞 𝐀𝐈 𝐇𝐚𝐧𝐝𝐥𝐞𝐫𝐬  They prepare data for AI, ensuring it’s clean, structured, and optimized for machine learning models. Because feeding bad data into AI is like training a GPS with a 10-year-old map. • 𝐃𝐚𝐭𝐚 𝐎𝐫𝐚𝐜𝐥𝐞𝐬 – 𝐓𝐡𝐞 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭𝐬  They predict what’s coming next—market trends, customer behavior, risk factors. Using historical data and predictive models, they help businesses make proactive decisions. • 𝐃𝐚𝐭𝐚 𝐒𝐮𝐫𝐠𝐞𝐨𝐧𝐬 – 𝐓𝐡𝐞 𝐂𝐥𝐞𝐚𝐧-𝐔𝐩 𝐂𝐫𝐞𝐰  They fix bad data, remove errors, and ensure consistency. Because even the best algorithms are useless if they’re working with garbage. • 𝐃𝐚𝐭𝐚 𝐏𝐡𝐢𝐥𝐨𝐬𝐨𝐩𝐡𝐞𝐫𝐬 – 𝐓𝐡𝐞 𝐄𝐭𝐡𝐢𝐜𝐬 & 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲 𝐆𝐮𝐢𝐝𝐞𝐬  They ask the big questions: Should we use this data? Is it biased? Does it comply with privacy laws? They ensure data-driven decisions are also responsible ones. With Chief Data Officers now overseeing AI strategy at 58% of organizations, the importance of these roles is only growing. So, which one best describes what you do? Or do you have a better title for your role? Drop it in the comments! 𝐅𝐨𝐫 𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐚𝐧𝐝 𝐝𝐞𝐞𝐩𝐞𝐫 𝐝𝐢𝐯𝐞: https://lnkd.in/eM6c3FkG ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

A new wave of AI‑driven roles is emerging across the workforce, and the titles alone tell the story of how fast things are changing: Decision Designer. AI Experience Officer. Digital Ethics Advisor.     These may sound futuristic, but they’re already appearing inside forward‑looking organizations. These roles blend AI expertise with psychology, ethics, organizational design, and workflow thinking.     Business Insider reports that these roles are growing rapidly as companies move from experimentation to scaled AI adoption. But it’s not only new jobs being created. Existing roles are also being redefined:     • HR leaders are becoming AI strategists, bridging people, technology, and data.  • Product managers are evolving into orchestration leads for agent‑powered workflows.  • Marketers and service teams are learning to design for AI‑mediated channels.  • Technical and business roles are blurring as the demand for interdisciplinary fluency grows.     All of this underscores a larger shift. As AI rewrites tasks, processes, and decision loops, we’ll see more roles that don’t map cleanly to traditional org charts. Titles will evolve. Skills will shift. Entire job categories will emerge focused on making sure AI is safe, transparent, ethical, and effective.     Read more here: https://lnkd.in/gMa4rm9f

We are undergoing a minor crisis in marketing. Hubspot and G2 have seen their SEO traffic drop 80%. The problem? Marketers are focusing on how to CREATE content using LLMs - when they need to MARKET content to LLMs. Unless you start creating content for LLMs as one of your PRIMARY audience, your reach will collapse and your visibility will vanish. Your buyers are now using LLMs and AI answers to find you. Search engines are coping with this change and changing algorithms. There is a new playbook. Adapt or disappear. 2000-2025: RISE OF SEO AND CONTENT MARKETING If the search engines couldn’t find you - you did not exist. Here’s the traditional playbook to get noticed by Search engines: - Thought leadership content: Unique insights developed for target audience to position the brand as a trusted expert - Content optimized for organic keyword discovery: carefully crafted high intent keywords to rank high on search engines and drive inbound traffic - Authority and backlinking: build high quality backlinks via guest posts or strategic partnerships - Long form articles that sparked discussions: Optimized for social discovery, engagement and conversations - SEO excellence: ensure fast loading, mobile friendly pages with strong internal linking for better indexing 2025 AND BEYOND : RISE OF LLMs AND AI In future - If the LLMs cannot find you, you do not exist. Here’s an emerging playbook to get a favorable presence in LLMs. - SEO is evolving to include LLM content discovery - Content optimized for LLMs to better position you against competitors - Make your support docs, use case docs and knowledge base public for LLMs to crawl. More content and case studies leads to better positioning.  - Thought leadership content and social engagement still works - Optimize for AI overviews while still pursuing organic authority - Your brand is more than just your website or search engines. Every podcast, YouTube video, blog post, and Reddit comment will be parsed by LLMs to shape your company knowledge graph.  - GEO Excellence: Master Generative Engine Optimization (GEO) to stay ahead. - LLMs are evolving. Use them to your advantage. Monitor brand perception, track competitors, and feed the right content to shape your narrative. GEO programmatic tools and agencies are coming - but don’t wait. Your buyers are already searching for you on ChatGPT. Run the same searches and manage your presence on LLMs. Ensure you stand out against your competitors and if you don’t, find a way to feed the right content to LLMs.  TAKEAWAY: SEO evolution is already happening whether you like it or not. Your buyers will increasingly use LLMs to find you. Your organic reach is now getting decentralized. Control your narrative or let AI control it for you. 

Work is changing faster than your org chart—and that’s not a prediction; it’s what I’ve witnessed doing AI-based deployments for 15+ years across Fortune 100's. Did you know that by 2030, AI is expected to automate 45% of current work activities? That sounds terrifying—until you realize that nearly every role I’ve led has changed completely every 2–3 years anyway 🤯 . 🛍️ Let me take you inside a retailer you know. They adopted AI to optimize their supply chain: predictive restocking, dynamic pricing, and warehouse robotics. Yes, automation changed the roles - but it didn’t eliminate them! 💡 The planners became simulation analysts. 💡 The merchandisers became AI auditors. 💡 And those freed from manual grunt work? They started tackling the backlog of work that had been pilin gup. AI didn’t reduce the workforce — it redefined it, and with redefinition comes opportunity – if we choose to take it! (topic of my 3rd #TEDx talk, releasing in May) Here’s the funny, slightly tragic truth: One executive told me they were “fully embracing AI.” When I asked how, he proudly said: “We bought 200 ChatGPT licenses.” That’s like preparing for a tsunami with a kiddie pool. 🤯 The companies winning in this next era aren’t just using AI — they’re training their people to thrive with it. Operative phrase: “training their people” So here’s how to prepare your workforce for what’s next: 🚀 Assess the now. Map roles and skills most likely to be disrupted or augmented. 🚀 Invest in reskilling. Don’t wait for the job to vanish. Train ahead of the curve. 🚀 Foster a learning culture. Create space (and incentives!) to experiment, fail, and evolve. Use AI responsibly. Don’t just optimize. Humanize. Ethics are part of your product now. One last thought: We’re not competing with AI. We’re competing with people who know how to use AI better than us. What steps are you taking to prepare your team? Share below. #FutureOfWork #AI #Leadership #DigitalTransformation #WorkplaceInnovation #SkillDevelopment #EthicalAI #SolRashidi #TEDx

Pointed statistics on the reskilling imperative. Leaders see substantial overcapacity in legacy roles due to AI, as well as dramatic AI skills shortages. The pace of the shift in workforce capabilities required means that organizational capacities for reskilling will be fundamental to success. Hiring will not be sufficient, not least due to the exceptional demand for relevant talent. Focusing on reskilling will be a massive enabler for attracting and retaining talent. I consistently argue that talent is becoming more - not less - important, and that this will be driven by explicit and implicit leadership attitudes. I'm very glad to see that "human-AI collaboration specialists" are specifically mentioned as being in demand. This points to the recognition that Humans + AI organizational redesign is critical. This is absolutely not just about changing the skills mix. It is about how human skills are applied and integrated with AI capabilities. I'm sure some will say that many of those who are in the "overcapacity" group are not able to be reskilled to develop the required AI skills. From a narrow view, not everyone will be readily able to shift into specific specialist roles. But if we look at the broader scope of the emerging high-value roles, the potential for reskilling is likely significantly higher than might be immediately evident. Work design and talent need to be reworked. Job roles, workforce planning structures, decision rights, accountability, training, reporting structures, and more need to evolve to enable more rapid shifts in developing and applying the skills required for the future organization.

I’ve been in the room when FMCG boards reviewed the final shortlist for a CMO role. Over the last 12 months, something remarkable has happened in those rooms: the most debated profiles aren’t traditional brand marketers from legacy CPG houses, they’re growth leaders from tech. Leaders from Spotify, Uber, TikTok, Amazon, Klarna. They’re not coming in with 20 years of experience managing heritage brands across grocery channels. But they’re fluent in another language altogether: data-led storytelling, performance-driven growth loops, real-time consumer signals, and omni-channel acquisition that doesn’t require above-the-line muscle. And suddenly, for global consumer companies that have struggled to keep up with how consumers discover and engage with brands, this “outsider” language is exactly what they’re craving. -76% of consumers now expect brands to anticipate their needs and behaviors, not just respond to them. (Salesforce, State of the Connected Customer, 2023) - Personalization and real-time relevance aren’t just “digital priorities”, they’re growth levers. -And for Gen Z consumers, brand loyalty is no longer built in-store or through TV spots. It’s earned through value-driven storytelling, digital community engagement, and consistent online presence across formats. The traditional FMCG CMO was a master of category management, retail activation, and brand architecture. That role still matters. But the emerging CMO, the one most in demand today looks a little different: → They think in funnels, not channels. → They test, learn, and optimize daily. → They’re equally comfortable briefing creators for TikTok as they are building full-funnel attribution models. → They manage marketing like a product team: agile, cross-functional, data-literate. I’ve seen this play out firsthand in executive search mandates. The world of consumer goods has changed and the skill sets needed at the top are evolving too.It’s no longer just about knowing the category. So, if you’re leading a consumer brand and hiring for its future, here’s my question: Are you searching for someone who knows your brand’s history? Or someone who can build its future? Let’s talk. #FMCG #MarketingLeadership #ExecutiveSearch #DigitalTransformation #ConsumerGoods #CMO #Hiring #FutureOfMarketing

👨💻👷♂️👩🔬 Data Analyst, Data Engineer or Data Scientist? Each role plays a unique and vital part in turning raw data into business value. 📊 Data Analyst Translates data into actionable insights to support decision-making. 🛠️ Tools & Skills: SQL, Excel, Power BI / Tableau, basic statistics 📌 Responsibilities: Create dashboards, analyze trends, organize data 👷♂️ Data Engineer Builds and maintains the data pipelines and infrastructure that make analytics possible. 🛠️ Tools & Skills: Python, SQL, dbt, Airflow, Spark, BigQuery, Snowflake, cloud platforms (GCP, AWS, Azure) 📌 Responsibilities: Build ETL/ELT pipelines, manage data lakes/warehouses, ensure data quality & reliability 🧠 Data Scientist Uses data to develop predictive models and uncover advanced insights. 🛠️ Tools & Skills: Python / R, Scikit-learn, TensorFlow, PyTorch, SQL, Jupyter, MLFlow, advanced statistics 📌 Responsibilities: Build ML models, run experiments, deliver predictions and recommendations ✨ As the data landscape evolves, new roles are emerging too: 🔹 Analytics Engineers – bridging the gap between analysts and engineers, often using dbt, SQL, and version-controlled data transformations. 🔹 Machine Learning Engineers – focusing on deploying, monitoring, and scaling machine learning models in production environments. 💡 No matter where you fit in, the key is collaboration. Together, these roles power data-driven innovation. Which role are you in — or aiming for? #DataEngineer #DataAnalyst #DataScientist #AnalyticsEngineer #MLEngineer #DataCareers #DataTools #TechRoles #LinkedInLearning #CareerGrowth

PR is becoming the new marketing. I know, I'm biased. But we're witnessing a fundamental shift in how companies get discovered, and I'm confident most businesses aren't prepared. LLMs are rewriting the rules of business visibility. Here's what's happening: When someone asks ChatGPT, Claude or [insert AI assistant] about solutions in your industry, these models aren't crawling your keyword-stuffed landing pages. They're drawing from trade publications, press releases, industry reports, and authoritative media coverage to determine which companies to recommend. Think about it - when I ask Siri to look something up, she automatically asks if I want to use ChatGPT for the search. And most of the time, I do. This isn't a "5 years in the future" situation - it's happening NOW. This means the companies that will thrive are those building genuine thought leadership, earning media coverage, and establishing credibility through PR rather than trying to game search algorithms. Your press mentions, industry awards, expert commentary, and feature stories are becoming your new SEO. The old playbook of keyword optimization and paid ads is giving way to something more authentic. What matters now? Building real relationships with journalists, contributing meaningful insights to industry conversations, and earning recognition through substance rather than strategy. The question isn't whether this shift will happen. It's already here. Is your team ready?

On my first day at an elite strategy consultancy, my boss told me: Shut down your computer and get a notepad. Thinking is a skill and you need to know how to do it right. That moment humbled me. I went from freshly minted MBA confidence to the humility of an apprentice. I spent years learning through repetitive work, pattern recognition, and countless mistakes that eventually became judgment. That apprenticeship model is now disappearing. AI isn't just changing entry-level work; it's eliminating the traditional first rung entirely. Young workers are seeing employment decline as 66% of enterprises reduce entry-level hiring due to AI adoption. The paradox we're living through: AI is simultaneously raising the floor and lowering the ceiling for entry-level talent. It's harder to get in, but those who do get in are positioned to create impact faster than any previous generation. Here's how to prepare for the AI-shaped career: 👉🏼 Build a hybrid skill stack Pair AI literacy with domain expertise (marketing, finance, product) and strong interpersonal capabilities. 👉🏼 Prioritize real experience early Internships, apprenticeships, and project-based work are no longer optional. They are essential for overcoming rising entry barriers. 👉🏼 Use faster learning pathways High-quality certificates, bootcamps, and non-degree credentials deliver job-ready skills faster than traditional degrees. 👉🏼 Practice visible, portfolio-based work Public projects, case challenges, writing samples, and tangible outputs break through automated screening filters. 👉🏼 Learn to collaborate with AI Treat AI as a copilot. Use it to amplify your output while sharpening your judgment, creativity, and strategic thinking. 👉🏼 Invest in networks and mentors As traditional apprenticeships fade, intentional mentoring and professional communities become your competitive advantage. 👉🏼 Commit to lifelong reskilling Mirror organizational adaptability by continuously learning and reskilling as technologies and business models evolve. Your career is no longer a ladder. It's a portfolio of capabilities you build, test, and recombine throughout your life. Are you building the skills that make you irreplaceable? ♻️ Share this post, especially with anyone entering the workforce. 🔔 Follow me, Nikki Barua, for insights on navigating change in the AI age.