How Technology Impacts Business Creation

Thinking about AI's impact on jobs often gets oversimplified. People tend to picture our world operating the same, but with AI stepping in to take over some tasks. This view misses the bigger picture. What really unfolds is that companies gain new abilities through AI. This sparks positive job growth. Historically, there’s been a substantial gap between small and large companies. Big companies typically have all the specialist teams they need—engineers for innovation, marketers for outreach, and legal, supply chain, and compliance experts for issues beyond their core. Smaller companies often can’t compete because they lack these resources. It’s a huge hurdle for starting up or scaling quickly. AI agents level the playing field, giving small businesses access to enterprise-level resources. This means smaller firms can grow faster and experiment more. Startups can now launch marketing campaigns, conduct market research, deliver new features, manage sales, and provide customer support—ways that were hard to afford before. In the past, though some tasks might have been outsourced or done in-house, many either weren't up to par or just didn’t happen. With this boost, small companies will actually create more jobs. They'll need people for roles that AI can't fill, in various support areas. AI isn’t just about replacing jobs; it’s about enabling businesses to do more, leading to job growth in areas AI can’t cover. #ai #jobs

𝗔𝗜 𝗛𝘆𝗽𝗲 𝘃𝘀. 𝗔𝗜 𝗩𝗮𝗹𝘂𝗲: 𝗛𝗼𝘄 𝘁𝗼 𝗰𝘂𝘁 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝘁𝗵𝗲 𝗻𝗼𝗶𝘀𝗲 𝗮𝗻𝗱 𝗳𝗼𝗰𝘂𝘀 𝗼𝗻 𝘄𝗵𝗮𝘁 𝗱𝗿𝗶𝘃𝗲𝘀 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗶𝗺𝗽𝗮𝗰𝘁 We’re living in a time of AI overload.Every day, there’s a new tool, a viral demo, or a promise that AI will transform everything. But for CXOs, the essential question remains: 𝗪𝗵𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝘃𝗮𝗹𝘂𝗲? In my work with Fortune 500 clients leading cloud and AI transformations, one thing is clear: Success with AI doesn’t come from chasing trends. It comes from identifying the 𝑟𝑖𝑔ℎ𝑡 𝑝𝑟𝑜𝑏𝑙𝑒𝑚, having 𝑟𝑒𝑙𝑖𝑎𝑏𝑙𝑒 𝑡𝑟𝑎𝑖𝑛𝑖𝑛𝑔 𝑑𝑎𝑡𝑎 𝑠𝑒𝑡𝑠, and 𝑒𝑥𝑒𝑐𝑢𝑡𝑖𝑛𝑔 𝑖𝑛 𝑡ℎ𝑒 𝑟𝑖𝑔ℎ𝑡 𝑏𝑢𝑠𝑖𝑛𝑒𝑠𝑠 𝑐𝑜𝑛𝑡𝑒𝑥𝑡. Here’s a practical lens I use with executive teams to prioritize AI investments: 𝗧𝗵𝗲 𝟯𝗣 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 – 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 – 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹𝗶𝘁𝘆 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: What specific business issue are we solving? Is it a speed, experience, or insight challenge? 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹: What’s the tangible upside of solving it with AI? Are we talking about revenue growth, New revenue streams, operational efficiency, or improved accuracy? 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹𝗶𝘁𝘆: Do we have the data, skills, and platform to deploy it at scale with the right market timing? Proofs of concept are easy; scalable success is not. 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗶𝗻𝗴 𝗥𝗲𝗮𝗹 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗩𝗮𝗹𝘂𝗲: 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗳𝗼𝗿 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 – 𝗕𝗼𝗼𝘀𝘁𝗶𝗻𝗴 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗶𝗻 𝗟𝗮𝗿𝗴𝗲 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 A Fortune 100 healthcare organization deployed generative AI to surface internal documentation and expert insights. Employees now retrieve critical answers in seconds, not hours—accelerating onboarding and reducing duplication of effort. 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗥𝗲𝘁𝗮𝗶𝗹 – 𝗟𝗶𝗳𝘁𝗶𝗻𝗴 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗥𝗮𝘁𝗲𝘀 𝗯𝘆 𝟭𝟴% A global retailer applied machine learning to personalize product recommendations based on browsing behavior and inventory trends. Customers received more relevant suggestions, and e-commerce conversions jumped by nearly 20%. 𝗔𝗜 𝗶𝗻 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 – 𝗖𝘂𝘁𝘁𝗶𝗻𝗴 𝗘𝘅𝗰𝗲𝘀𝘀 𝗜𝗻𝘃𝗲𝗻𝘁𝗼𝗿𝘆 𝗯𝘆 𝟮𝟱% A manufacturing firm integrated AI-based demand forecasting into its planning cycle. With more accurate predictions, they reduced excess inventory and saved millions in carrying costs. 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲: If your AI project doesn’t move the needle—on revenue, speed, or experience—it’s probably tech theater. AI is here to stay, but 𝘃𝗮𝗹𝘂𝗲 𝗶𝘀 𝘀𝘁𝗶𝗹𝗹 𝘁𝗵𝗲 𝗡𝗼𝗿𝘁𝗵 𝗦𝘁𝗮𝗿. 𝗪𝗼𝘂𝗹𝗱 𝗹𝗼𝘃𝗲 𝘁𝗼 𝗵𝗲𝗮𝗿 𝗳𝗿𝗼𝗺 𝗼𝘁𝗵𝗲𝗿𝘀: 𝑊ℎ𝑎𝑡’𝑠 𝑎 𝑟𝑒𝑎𝑙-𝑤𝑜𝑟𝑙𝑑 𝐴𝐼 𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑡ℎ𝑎𝑡’𝑠 𝑑𝑒𝑙𝑖𝑣𝑒𝑟𝑒𝑑 𝑚𝑒𝑎𝑠𝑢𝑟𝑎𝑏𝑙𝑒 𝑖𝑚𝑝𝑎𝑐𝑡 𝑓𝑜𝑟 𝑦𝑜𝑢𝑟 𝑏𝑢𝑠𝑖𝑛𝑒𝑠𝑠? #AI #Cloud #DigitalTransformation #TheHeartOfProgress

AI Agents Are Reshaping the Economy AI agents are driving massive efficiencies and unlocking new business opportunities today. These intelligent systems are cutting costs, boosting productivity, and accelerating decision-making. 🔹1. AI Agents in Content Creation Example: AI agents now write blogs for <$0.01, as seen with AgentStack & AgentOps, or even curate newsletters, like Jelani Abdus-Salaam’s AI-powered Best of AI newsletter. Economic Impact: Companies can cut content creation costs by 60-80%, scale output 10x faster, and grow their digital presence without hiring more writers. 🔹 2. AI Agents in Legal Lead Qualification Example: Dench(.)com by Mark Rachapoom is an AI-powered legal secretary that pre-qualifies leads for law firms. Economic Impact: Lawyers save 20-30% of their time by automating lead intake, boosting revenue by 15-25% and reducing intake costs significantly. 🔹 3. AI Agents in Web Research Example: Gumloop’s AI Web Research scours the web for answers, while Perplexity AI’s Deep Research Agent analyzes market trends like a McKinsey analyst. Economic Impact: Businesses can cut research costs by up to 90%, process 100x more data, and make faster, data-driven decisions. 🔹 4. AI Agents in E-commerce Optimization Example: AI agents now manage Shopify stores, optimizing product listings, customer support, and inventory. Hertwill even posted the first AI Agent job on LinkedIn. Economic Impact: AI can increase e-commerce revenue by 20-30%, optimize inventory management, and cut customer support costs by 50%. What's more in the future of agents?

AI OPPORTUNITIES FOR FORTUNE 2000 As artificial intelligence reshapes the business landscape, Fortune 2000 companies stand at a pivotal moment. Just as Alphabet's DeepMind trying to revolutionize protein structure prediction, and Amazon's AI transformed retail, enterprises now have unprecedented opportunities to revolutionize their operations and drive innovation. ▪︎ Service and Process Transformation - AI enhances operational efficiency through automation and improved decision-making. JP Morgan's COIN software analyzes commercial loan agreements in seconds rather than the 360,000 hours of lawyer time previously required. UPS uses AI-powered route optimization to save millions in fuel costs. ▪︎ Innovation and Product Development - AI enables creation of new products while enhancing existing offerings. Netflix uses AI to inform content creation decisions, while Tesla continuously improves its self-driving capabilities through AI learning from its vehicle fleet. This leads to first-mover advantages and better meeting of customer needs. ▪︎ Knowledge Management and Organizational Intelligence - AI transforms how organizations utilize institutional knowledge. Walmart analyzes billions of customer transactions for inventory optimization, while Unilever processes employee feedback across global operations for improved workforce management. This enhanced intelligence leads to better strategic decision-making. The potential of AI extends far beyond automation. Companies like Google and Microsoft have demonstrated how AI can create billions in value through enhanced productivity and innovation. By embracing these opportunities strategically, Fortune 2000 companies can position themselves at the forefront of the AI revolution. To capitalize on these opportunities while managing risks, in my upcoming book, ‘TRANSCEND’, I proposed implementing dual frameworks: OPEN and CARE.  These frameworks work together to help organizations maximize AI's potential while managing risks. OPEN guides organizations through outlining opportunities, building partnerships, experimenting systematically, and navigating change. CARE ensures comprehensive risk identification, assessment, regulation, and exit planning. These frameworks operate in parallel for balanced AI implementation. #fortune500 #business #innovation #AI #management

Unlocking the Power of AI Network Effects in Business: AI is frequently praised for its capacity to automate tasks, but its real potential lies in a more dynamic aspect: interaction. The more users engage with an AI system, the smarter it becomes. This phenomenon, known as AI network effects, can significantly benefit businesses that are willing to embrace it. Each user interaction enhances the AI's ability to learn, make predictions, and respond with increasing accuracy. Think about it: 🔹Google Maps doesn’t just guide us, it gets sharper with every driver, refining traffic predictions in real-time. 🔹Spotify creates playlists that feel remarkably personal, enhancing with each song you listen to (or skip). 🔹Amazon finetunes its recommendations every time you browse, click, or purchase, creating a shopping experience that feels tailor-made for you. 🔹Netflix evolves its suggestions with every show you watch (or abandon), keeping you hooked with uncanny accuracy. Now, picture this power unleashed across industries: > Customer service that anticipates needs before a call even begins. > Healthcare diagnostics that evolve with every patient outcome. > Personalized learning platforms that adapt to each student’s unique pace. The magic lies in the feedback loop. Each interaction is a data point, and every data point makes the system stronger. Businesses that tap into AI network effects don’t just gain efficiency, they build a self-improving competitive edge that’s tough to replicate. Whether it’s enhancing decision-making, streamlining operations, or delighting customers, the opportunities are endless and the advantage belongs to those who act. #AI #NetworkEffect #MachineLearning #DataDriven #TechInnovation #BusinessStrategy #SageIT