Preparing for AI-Driven Changes in Company Culture

💬Now is the time for leaders to rethink job descriptions. Many believe that updating job descriptions every 3-5 years is sufficient. 🐌 Those days are gone. ⏩ You should be reassessing jobs every 4-6 months. Focus on the human elements that Al cannot replicate: ✅ creativity ✅ strategy ✅ interpersonal skills Then, thoughtfully redesign roles to use Al's strengths so that there’s more time to apply those human elements! This is not about replacing jobs, but reimagining them to foster innovation and drive business growth. What does this practically look like? 🖥️ IT As AI takes over routine coding and troubleshooting tasks, IT professionals can focus on designing complex, strategic IT architectures, cybersecurity innovations, and facilitating the integration of new technologies within the company. 📊 Finance AI can handle data analysis and report generation. Finance experts can shift towards interpreting this data for strategic decision-making, focusing on financial forecasting and advising on investment opportunities leveraging AI-driven insights. 🤝 Sales With AI handling initial customer inquiries and lead qualification, sales representatives can dedicate more time to understanding client needs, building relationships, and developing customized solutions that truly resonate with each customer. 🔄 Operations As AI streamlines logistics and inventory management, operations personnel can concentrate on optimizing supply chain strategy, vendor relations, and sustainability practices. 👥 HR AI can manage payroll, benefits administration, and resume screening. HR professionals can then focus on employee engagement strategies, professional development programs, and fostering company culture. 🎨 Marketing With AI taking on market analysis and targeted advertising, marketers can pivot to crafting more compelling brand narratives, innovative campaign strategies, and engaging content that speaks to human emotions and experiences. ⚖️ Legal AI can assist in document review and due diligence processes. Legal professionals can focus on complex negotiations, strategic counseling, and providing personalized legal advice where human judgment is critical. 📦 Supply Chain AI could handle demand forecasting and inventory optimization. Supply chain experts can then work on strategic partnerships, resilience planning, and exploring new market opportunities. —- The savviest employees have learned new ways of working already. How about you? Have you told anyone that you no longer work the same way? Share how you’re working differently now 👇🏻 #Innovation #Growth #AI #management #FutureOfWork

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

Recent research from Indeed Hiring Lab indicates that while GenAI is unlikely to fully replace human workers, it will provide significant augmentation to human capabilities. Their analysis of over 2,800 skills shows that GenAI best handles repetitive and knowledge-based tasks, allowing humans to focus on core skills requiring ingenuity, hands-on application, and interpersonal interaction. In a separate analysis, Kyla Scanlon introduces the concept of "friction" as a lens into the AI landscape. She states that while the digital world seeks to eliminate friction for the user, it often transfers that friction to the physical world (underfunded infrastructure, overworked labor). This redistribution of friction potentially devalues traditional skills and credentials. I've been digging into a concept I refer to as skills flux -- a period in which workers will use their existing skills while needing to learn new ones as their jobs change due to automation and AI. Both the Indeed research and Kyla's paper illustrate this transitional period as an opportunity to redefine the basic tenets behind "reskilling" or "upskilling" (I would love to retire those two words from our lexicon). Our focus in L&D needs to be on deeply understanding how automation and AI changes the nuances of jobs (yes, to the task level) and to then develop training that facilitates the workforce to learn new GenAI-specific skills as complementary to their existing skills. L&D's role is to drive a programmatic approach to rapidly develop the workforce while balancing the tension of this period of skills flux. If we do this right, we relieve the company from large workforce displacement and enable the metrics important to the business as the integration of automation and AI evolves -- it's expensive and time-consuming to continually buy skills. This means we change our focus from traditional "reskilling" and "upskilling" programs to enable more dynamic skills strategies. I recommend these two steps to get started: -- Identify the enterprise critical roles across the company -- Conduct a job architecture inventory in alignment with the business to excavate how automation and AI changes the jobs (and, yes, AI can be used to scale this process) This enables a strategy for L&D to be in service of the most critical aspects of business continuity. For the first time in L&D's history, we face the daunting task of simultaneously preparing the workforce to execute strategies resulting from automation and AI while preventing the instability that a skills flux brings to the business and the workforce. Here are links to these two reports: -- Indeed Hiring Lab: https://lnkd.in/grF2C2-E -- Kyla Scanlon: https://lnkd.in/gAkcj4Qi

For me, this is still the go to playbook for how to engage your people team around the goal of creating a company culture that embraces AI. A couple of years back, excited by the potential of AI, Gianna Driver encouraged the People Team at Exabeam to “figure out AI”. She said it was a broad directive to find AI applications within HR by their next monthly meeting. However, excitement turned to disappointment when the next month rolled around and no progress had been made. Realizing the need for a more structured approach, the team paused their AI endeavors. This break allowed them to reconsider their strategy without the pressure of producing immediate results or deliverables. About a year and a half ago, they picked it back up, this time with smaller, more focused experiments. One of their first successes was using AI to craft job descriptions. Instead of waiting for hiring managers to specify what they needed, the talent team used AI to generate robust and inclusive job descriptions proactively. This shift not only sped up the hiring process but also impressed hiring managers, opening their eyes to the practical benefits of AI in streamlining HR tasks. 🔄 Identifying More Opportunities for AI: Motivated by their early wins, the leadership team started to evaluate other tasks that could benefit from AI, focusing on those that were repetitive and time-intensive. This strategic move freed up the team to engage more in high-level, strategic work rather than getting bogged down in mundane tasks. 📚 Revamping the Employee Handbook: Traditionally, updating the employee handbook every year has been a cumbersome task, driven by changing laws and internal policies. Gianna’s team introduced AI to this process, using the technology to provide a preliminary update, which was then refined with the essential human touch. 📊 Automating the Merit Process: Their journey didn’t stop there. The team looked at automating their merit process, a task that involves considerable data analysis and decision-making based on various metrics like market deltas and performance scores. By collaborating with their AI-savvy product team, they developed a tool that automated many of the manual steps involved, encapsulating the logic in streamlined AI-driven processes. We're excited to see the great to work that Gianna does at Lattice! ____ 🔔 Get more insights like this delivered directly to your inbox. Sign up for our weekly newsletter in the comments. #HR #CHRO #Peopleleader #chiefpeopleofficer #podcast #hrpodcast #AIHR #AI

Your employee learning systems won’t just train people anymore — they’ll train your AI Agents. Your corporate university will become an LLM fine-tuning hub. The implications are big: • 𝗬𝗼𝘂𝗿 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗮 𝗱𝗮𝘁𝗮𝘀𝗲𝘁: onboarding docs, sales playbooks, support transcripts, and internal wikis will shape your AI’s behavior and outputs. • 𝗬𝗼𝘂𝗿 𝘀𝘂𝗯𝗷𝗲𝗰𝘁-𝗺𝗮𝘁𝘁𝗲𝗿 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗯𝗲𝗰𝗼𝗺𝗲 𝗔𝗜 𝗺𝗲𝗻𝘁𝗼𝗿𝘀: their expertise won’t just teach people anymore; it will calibrate intelligent systems across your org. • 𝗬𝗼𝘂𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘆𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗲𝗱𝗴𝗲: companies that invest in tuning will have AIs that sound like them, think like them, and scale them. It’s a cultural transformation. Your AI will only be as smart as what (and who) it learns from. 👉 How are you thinking about training both people and AIs in your company?

“If you want to make the world a better place, take a look at yourself and then make a change.” Michael Jackson, “Man in the Mirror” The message I keep repeating in boardrooms and leadership retreats, especially when the conversation turns to “rolling out AI” is that they need to include their team in the mindset. Too many companies treat AI like it’s a plug-and-play solution. Add a few pilots. Buy a few licenses. Sprinkle in a chatbot or two. Then sit back and wait for transformation. Or they just give it to everybody in their company, without a clear understanding of their needs or challenges, expecting them to figure it out. But here’s the uncomfortable truth: no matter how advanced the technology, it won’t move the needle if your team isn’t ready to work with it. You are starting with failure and then expecting success. If you don’t have the clarity or the understanding of what your business objectives are and where your challenges are, then AI won’t help you or your team. If you don’t know how AI fits in your company, then your employees won’t know how it fits in their role. Don’t think that AI competency is giving your team ChatGPT and hoping for the best. You need to build fluency across every layer of your business. It starts in the boardroom and extends to the front line. Leaders need to understand risk and governance. HR and change agents need to shape the culture. SMEs need to translate real-world problems into AI-ready inputs. And yes, technical teams need deeper skills in modeling and deployment. But beyond roles, it’s mindset that makes or breaks AI readiness. Are your people curious or cautious? Open or overwhelmed? How they feel about AI directly impacts how well they’ll adopt it. The companies that get this right? They’re the ones investing in strategic, role-based training. They’re developing fluency, and creating trust with their team. And it’s working. IBM launched an internal AI academy. Pfizer built AI fluency across departments. The result? Real capability. Faster innovation. Practical impact. So if you’re serious about AI, don’t just invest in technology. Invest in your people. Link to the full article in the comments. #AILeadership #TalentStrategy #AICompetency #FutureOfWork #ChangeManagement #SharkFramework #KevinJDean

A new study finds that leaders expect their teams will be training (41%) and managing (36%) AI agents within 5 years. This research underscores a significant shift in the future role of HR leaders, requiring them to proactively develop strategies for workforce training and management that incorporate AI agents as integral team members. HR will need to create training programs not only for employees to effectively utilize AI tools in their work but also to equip them with the skills to train and oversee the performance of AI agents, ensuring alignment with organizational goals and ethical guidelines. HR will be instrumental in redefining team structures, performance management systems, and job roles to accommodate this human-AI collaboration, fostering a culture of adaptation and continuous learning within the organization to maximize the benefits of an AI-augmented workforce. https://lnkd.in/ehtkczM2