Future Work Strategies Using Generative AI

How might generative AI support nonprofit workplace learning and upskilling? When OpenAI introduced ChatGPT Study and Learn Mode, it addressed a common concern in education: that AI makes it too easy for students to skip the thinking and jump to the answers. Study Mode turns ChatGPT into a learning buddy designed to help users articulate goals, reflect, and build skills step by step. Study Mode helps students explain what they know, identify where they’re stuck, and engage in a guided learning process. These same principles translate powerfully into nonprofit workplace learning. For example, a program manager preparing a theory of change can use Study Mode prompts to encourage deeper reasoning: "What assumptions are built into your model? How would you measure success?" By replacing instant answers with reflective dialogue, ChatGPT Study Mode discourages shallow thinking and could help staff strengthen strategic instincts. It’s a smart way to reinvest the time saved through AI automation. Nonprofit staff facing increased pressure to do more with less often turn to AI for automation to save steps on drafting content, summarizing meeting notes, or analyzing reports.AI can and should make our work more efficient.  But they’re only one way to collaborate with generative AI. Nonprofits also need to use AI augmentation or working with it collaboratively to support human intelligence.  AI can be a thinking partner, not just a productivity hack. When used well, generative AI can: Encourage staff to reason through problems Support learning through adaptive feedback Create space for deeper planning, strategy, and interpersonal connection Generative AI is primarily valued for speed and being frictionless. Cognitive offloading may save time in the short term, but over-reliance can dull strategic instincts and reduce our ability to make meaning across complex situations. In a sector where human judgment, pattern recognition, and values-based decision making matter deeply, that’s a risk we can’t afford. We have an opportunity to use generative AI tools to support upskilling strategies that enhance staff capability alongside human-to-human learning such as mentoring, team dialogue, and on-the-ground practice. AI isn’t a replacement, but it can be a partner in nonprofit workplace learning. https://lnkd.in/gs_rzEtR #AIAugmentation #HumanAICollaboration #AIskilling #Upskilling #humanskills #learning #workplacelearning Philip Deng Rachel Kimber, MPA, MS Meenakshi (Meena) Das Tim Lockie Kaz McGrath John Kenyon Chantal (Coco) Forster

“Generative AI has demonstrated the potential to significantly outperform human CEOs in strategic decision-making by excelling in data-driven tasks like product design and market optimization. In an experiment simulating the automotive industry, AI models outpaced human participants in market share and profitability but faltered in handling unpredictable disruptions, leading to faster dismissals by virtual boards. While AI’s ability to analyze complex data sets and iterate rapidly could revolutionize corporate strategy, it lacks the intuition and foresight required to navigate black swan events. Rather than fully replacing human CEOs, AI is poised to augment leadership by enhancing data analysis and operational efficiency, leaving humans to focus on long-term vision, ethics, and adaptability in dynamic markets. The future of leadership will likely be a hybrid model where AI complements human decision-making.”

Incisive piece by the The New York Times Steve Lohr on first of its kind research by The Burning Glass Institute and SHRM on the likely impact of Generative AI on employment. Initial analyses, including our hear at Harvard Business School Project on Managing the Future of Work have identified important a number of likely outcomes. This report drills down deep, confirming many of those hypotheses. The core of the report is The Burning Glass Institute identifying the 200 occupations that are most likely to be affected by Generative AI (GAI). It isn't going to wipe out jobs wholesale. GAI will displace some tasks altogether and speedup others. It will make people more productive-- a huge boon to the U.S. economy, given lackluster productivity growth in recent years. That productivity growth will lead to companies reducing their staff or hiring needs. The biggest impact will be on classic, white collar jobs-- marketers, business and financial analysts, supply chain managers and purchasing agents, auditors, attorneys, etc. Industries will be affected asymmetrically with professional services, banking and tech. In some industries that will be less affected, specific competitors may be more vulnerable. A retailer like Tiffany's might only restructure marginally; a retailer like Williams-Sonoma with a significant web presence much more so. So, what should executives do? One, develop a strategy. Huge value is on the table and, if your competitors get out in front of you, the consequences will be significant. Companies that slide down the learning curve faster have the prospect of gaining a significant, even insurmountable data-drive advantage. Two, start demystifying GAI for your workforce. Too many companies are holding their cards close to their vests. Left to their own imaginations, workers are increasingly likely anxious and skeptical. That will undermine future reskilling initiatives. Three, start thinking about future job design. If GAI is going to unburden many white collar workers of 40%, 50%, even 60% of their current tasks, what should they be directed to do. What upskilling or reskilling should we be undertaking? How should job descriptions change? What about incentives and metrics? Start probing these questions now, don't wait and find yourself trying to change the engines on the plane while you're flying at 30,000 ft. Four, use tools like this to evaluate your organization's current design. How much disruption is coming your way? How can you start preparing for it now, such as reining in hiring for positions that are likely to be substantially transformed in the next year or two. Five, revisit your talent pipeline strategies. Where will the talent you need in the GAI world come from? Seems implausible that your talent suppliers from the pre-GAI world will all be perfect fits for the what's coming. #artificialintelligence #workforcetransformation #generativeai

The Local Test. Hector, the Wall Builder: A strategic way to think about artificial intelligence and human creativity The next decade will not be human versus machine. It will be human taste paired with machine range. New tools widen the search for ideas. People decide which ideas matter. Hector, the wall builder This weekend a local contractor named Hector installed wall panels in my home. I asked if he was worried about artificial intelligence. He surprised me. He said he loves it. Here is what he does. He asks a prospective client to send a few photos of their space. He uses a phone and a simple design tool to generate concept images of what their walls could look like. He runs a few small ads that show these concepts. People text him back. He replies with two or three variations, still by text, and he gives a price and a start date. In minutes the client sees the idea, feels the idea, and agrees to the job. He told me he is now booking more work than he has hours for. “Send me two photos of your room. I will text back three ideas and a price. Most people decide in minutes.....I use Google Gemini and ChatGPT to create the designs and write the messages. It helps me win the work and serve more clients.” See his work: PopWallDesigns on Instagram For the data junkies: + 58% of small businesses now use generative AI (up from 40% last year). Among those, 82% increased hiring in the past year. + In measured work, artificial intelligence boosts output: +15% productivity in customer support and 40% faster completion on professional writing tasks with higher quality. + People answer text: research shows high engagement and opt-in rates for business SMS, with stronger click-through than email. + Seeing is believing: big retailers already let customers scan a room and drop designs into real photos in seconds, cutting decision time. Hector is not waiting for a perfect future. He is using today’s tools to lower the cost of trying ideas and to raise the speed of selling those ideas. That is what a creativity engine looks like in real life. I wrote a one week plan any small business can run here: https://lnkd.in/gyJ3Tng4 PS: I received his consent before posting. If you need work done in the Bay Area, hit his DMs and tell him I sent ya.

Is generative AI just another tech bubble, or the next game-changer after mobile and cloud? The truth is, it doesn't matter - you need a strategy. Now. Here's why: Tech revolutions wait for no one. There was a period of rapid experimentation, and ultimately, clear winners and losers. Success came to those who experimented early. Those who hesitated (e.g. Windows Mobile) got left behind. History's about to repeat itself with AI. Let's rewind and learn from the past: Internet Revolution (Late '90s/Early '00s): ✅ Amazon: From online bookstore to e-commerce empire ✅ Google: Revolutionized how we access information ❌ AltaVista: Web portals as comprehensive starting points for web browsing declined with the rise of search engines. ❌ Webvan: Early online grocery flop (but the idea lived on) Mobile/Cloud Revolution (Late '00s/2010s): ✅ App Stores: Apple and Google created new digital ecosystems ✅ Uber & Lyft: Transformed global transportation ❌ Google Glass: A premature leap into AR ❌ OnLive: Cloud gaming pioneer that crashed and burned With a possible AI revolution, how do you avoid being tomorrow's cautionary tale? 1. Experiment Aggressively:    • For Individuals: Master tools like ChatGPT or Midjourney and explore how to make your daily work better with AI.    • For Companies: Form AI tiger teams. Explore use cases. Fail fast, learn faster. 2. Deliver Real Value:    • Don't just slap "AI-powered" on everything.     • Focus on genuine user benefits and seamless experiences.    • While there have been early wins in chatbots and code generation, the field is wide open. 3. Ethics as a Competitive Edge:    • Design for and address bias, privacy, and consent head-on.    • Turn responsible AI into your market differentiator. Take action now: 1. Identify one process in your work that AI could enhance. 2. Experiment with an AI tool this week. How are you experimenting with the Gen AI rage?

🌐 Staying Human Is the Ultimate Career Moat in an AI-First World AI isn’t “taking our jobs” so much as dissecting them. The latest Future-of-Jobs research shows that only 42 % of business tasks are expected to be automated by 2027—down from 47 % forecast just three years ago. Routine work is moving to machines; uniquely human capabilities are gaining value. Five data-backed principles shaping how I future-proof my own career: 1. Double-down on what AI can’t master. Creativity, empathy, nuanced judgment, and real-world dexterity remain stubbornly human. 2. Treat AI as a co-pilot, not a rival. Generative AI could unlock $2.6 – $4.4 trillion in annual value, mostly by amplifying human productivity. 3. Build “prompt fluency.” Organizations whose leaders actively upskill in generative AI are seeing promotion rates jump by a factor of four. 4. Narrative beats numbers. Data alone is noise; storytelling moves decisions. Productivity gains from AI are projected to add 1.5 percentage points to annual growth—but only if leaders translate insights into action. 5. Invest in network capital. A warm referral still trumps algorithms: candidates introduced by insiders are about 4× more likely to land the job than cold applicants. Bottom line: Degrees age, models update, but trust, imagination, and ethical judgment compound. In an AI-first economy, the most strategic move is to stay deeply human—while letting the machines scale your impact. #AI #Leadership #FutureOfWork #DigitalTransformation #CareerGrowth #GenerativeAI #NetworkCapital

The Future of Generative AI in Enterprise Decision Making Generative AI has moved from novelty to necessity. Beyond content creation, it is reshaping how executives make decisions, allocate capital, and manage risk. Boards must understand where this technology is heading and how it will transform governance and strategy. Generative AI as a Decision Partner Generative AI is evolving into a decision support layer that synthesizes complex data, generates scenarios, and surfaces tradeoffs aligned to executive workflows. Rather than replacing judgment, it accelerates insight when paired with clear human‑in‑the‑loop controls, shortening the path from data to decision while preserving accountability. Strategic Use Cases Emerging Now Four high‑impact use cases are moving rapidly from pilot to production: 1. Board Reporting & Insights: AI can synthesize large volumes of operational and financial data into concise, decision‑ready summaries, improving the quality of board discussions. 2. Scenario Planning:  Leaders can test “what if” scenarios across supply chain, pricing, workforce, and M&A, enabling faster iteration and continuous contingency planning. 3. Policy Simulation:  AI can model the downstream effects of regulatory or geopolitical shifts, helping boards stress‑test strategy under multiple regimes. 4. Customer & Market Intelligence:  Real‑time analysis of market signals and sentiment helps leadership detect inflection points earlier and align capital allocation accordingly. Risks Boards Must Anticipate Generative AI introduces material governance risks: 1. Hallucinations that require verification 2. Model bias that can reinforce blind spots 3. Data leakage from poorly governed integrations 4. Over‑reliance on automation that erodes accountability Boards must ensure AI‑augmented decisions remain transparent, auditable, and aligned with the enterprise risk framework, supported by documented data lineage, versioned models, human approval gates, and routine audits. Case Example: Strategic Planning with AI A global logistics company embedded generative AI into planning and forecasting, achieving faster scenario modeling, more accurate demand projections, and stronger cross‑functional alignment. The key insight: when paired with strong data pipelines and governance, AI turns planning into a continuous strategic capability with 30% faster model scenario cycles. What Boards Should Do Now Boards should require: 1. A clear Generative AI governance framework 2. Explicit human‑in‑the‑loop decision guidelines 3. An integration roadmap across planning, forecasting, and reporting 4. Regular model performance and risk reporting Executive Takeaway Within the next 24–36 months, generative AI will become a core component of enterprise decision making. Organizations that combine disciplined data, strong governance, and sustained human oversight will gain a durable advantage in speed, insight, and strategic agility.

Please author your own future. There are quite a few reports circulating about the future of work in the age of AI. Jobs on the rise, jobs on the decline - framings like that. I recommend that you read them, file them away, and not expend too much energy trying to decipher your position in the "coming wave" of AI adoption. We can begin to see the fuzzy edges of the future if we just look in the right way. Surveying jobs on the rise, I posit, is not the right way. Instead, look at the capabilities of AI, today and in the future, and map them over your sector, your role and your career goals. Create your own map and follow it. The best framework I've found for understanding AI capabilities is from Paul Roetzer / SmarterX. AI is, fundamentally, built to excel at tasks that are REPETITIVE, DATA CENTRIC, PREDICTIVE, GENERATIVE. So what does that mean for you? REPETITIVE: AI excels at tasks that follow consistent patterns and rules - not just simple automation, but entire workflows and complex processes. It learns from repetition, optimizes systems, and scales solutions across organizations. Think about roles heavy in manual data entry, quality control, or basic customer service - these aren't disappearing, they're evolving into positions that design and oversee these automated systems. DATA-CENTRIC: When it comes to processing and analyzing vast amounts of information, AI is transforming how we find insights. It's not just about big data anymore - it's about connecting dots across databases, documents, and diverse information sources in real-time. Analysts and researchers will evolve into insight architects who know how to ask the right questions and interpret complex patterns. PREDICTIVE: AI's ability to forecast trends and identify patterns is reshaping how we make decisions. From market analysis to risk assessment, these systems can process countless variables and suggest likely outcomes. Traditional forecasting roles are shifting from number-crunching to scenario planning and strategic interpretation of AI-generated predictions. GENERATIVE: Perhaps the most misunderstood capability, AI can now create content, code, and designs based on learned patterns. But rather than replacing creative professionals, it's becoming a powerful collaborator. Designers, writers, and developers who learn to leverage these tools are finding they can explore more possibilities and focus on higher-level creative direction. What about #Agents? Those digital employees of the future? They're not ready to take your job yet. If you follow the breadcrumbs I've left above, you'll make yourself indispensable to the employer or the industry looking to augment their business with agentic help. Say it with me: My career isn't at the mercy of AI. I will adapt and thrive. #AI #CareerStrategy #FutureOfWork #Innovation

Unlocking Business Transformation with a Generative AI Strategy  Generative AI is reshaping industries, making it imperative for leaders and managers to adopt a structured approach. Here's a five-pillar framework for integrating GenAI seamlessly into your organizational fabric: 1️⃣ Business Strategy: Prioritize business objectives aligned with OKRs. Identify GenAI use cases to meet goals and manage innovation portfolios. 2️⃣ Technology Strategy: Decide whether to buy or build GenAI solutions. Invest in infrastructure, security, and MLOps for sustainable innovation. 3️⃣ GenAI Strategy: Map use cases to business objectives and pilot solutions. Establish a Center of Excellence (CoE) for scalable GenAI adoption. 4️⃣ People Strategy: Gain leadership support and manage change effectively. Build skill development paths to create a learning ecosystem. 5️⃣ Governance: Implement accountability mechanisms and enable regular reviews. Ensure compliance with security, ethics, and responsible AI practices. 💡 Why It Matters: A well-executed GenAI strategy empowers organizations to drive innovation, enhance decision-making, and remain competitive in the evolving tech landscape.

Generative AI is revolutionizing go-to-market strategies, making it crucial for those in GTM roles to explore and adopt today’s AI-powered tools. Embracing these technologies can significantly boost your impact and help you stay ahead as the workplace evolves. We’re witnessing a paradigm shift from traditional, manual methods to data-driven, scalable, and personalized customer interactions. This transformation enhances efficiency and improves the ability to meet and exceed customer expectations with tailored experiences and innovative solutions. As generative AI technology advances, its role in GTM strategies will expand, providing ever more sophisticated tools for engaging and capturing market share. Sales Ops and Marketing Ops will increasingly need to integrate into a unified tech stack, creating a centralized intelligence hub. This integration may blur the lines between the CRO and CMO roles, necessitating collaboration or even unification into a single function. Regardless of organizational structure, leaders must cultivate a deep understanding of how generative AI and other technologies can propel success. We're already seeing that Generative AI is transforming GTM strategies in multiple dimensions: Sales and Marketing Optimization - AI-driven personalization of content and outreach - Automated lead generation and qualification - Dynamic content creation for emails and social media - Targeted customer segmentation Customer Interaction and Support - 24/7 engagement through AI chatbots and assistants - Smart support tools for quick query resolution - Predictive services that anticipate customer needs - Multilingual support via generative AI Product Development and Innovation - Faster market research with AI insights - Rapid prototyping using generative design - Enhanced competitive intelligence - Accelerated documentation and technical writing Sales Enablement - AI-generated sales scripts and conversation guides - Real-time coaching and team performance optimization - Automated pitch deck and proposal generation Content Strategy - Scalable content creation across channels - AI-enhanced SEO optimization - Rapid localization of marketing materials - Continuous content personalization Customer Experience - Hyper-personalized user interactions - Predictive customer journey mapping - Enhanced recommendation systems - Adaptive product interfaces Operational Efficiency - Lower customer acquisition costs - Faster time-to-market for products and campaigns - Efficient resource allocation - Reduced manual work in repetitive tasks Just to name some examples and this is just the beginning. There's never been a more exciting time to build businesses! #generativeAI #CRO #CMO #GTM #businesstransformation #genAIrevolutionizingGTM #genAI #ai