Co-Founder/CEO at PrimaFelicitas | Expert in Blockchain & AI Development | Helping Startups & SMBs build cutting-edge products with AI, Web3, dApps, and Smart Contracts
Starting an AI business? Ensure these 9 critical strategies are aligned to avoid costly mistakes. Businesses are not seeing the ROI on their AI investments, and Gartner's 'Trough of Disillusionment' is looming large. It's time to move beyond hype and return to the fundamentals while building an AI business or integrating AI into your business. Success relies on strategic decisions and Smart execution, and the following nine considerations are critical: 𝗔𝗰𝘁𝘂𝗮𝗹 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: Identify a real problem and real use case to work upon. The sector is filled with products that don't solve any major issue. 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗙𝗼𝗰𝘂𝘀: Keep users at the centre. Ensure your AI solution is practical and easy to use. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗠𝗼𝗱𝗲𝗹: Develop a clear value proposition that tackles your use case through AI. 𝗗𝗮𝘁𝗮 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆: AI thrives on data. Ensure access to high-quality datasets. Protect user privacy and security. 𝗦𝗽𝗲𝗲𝗱 𝘁𝗼 𝗠𝗮𝗿𝗸𝗲𝘁: This is the key to success. Launch the MVP quickly, iterate, and improve based on real user feedback. 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆: Based on the use case, choose to build a proprietary model or to leverage open-source. 𝗢𝗯𝘀𝗼𝗹𝗲𝘀𝗰𝗲𝗻𝗰𝗲: AI tech is evolving rapidly, so prepare for obsolescence and tech upgrades. 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Architect a system that is scalable for future demands. Invest in flexible infrastructure for future expansion. 𝗧𝗮𝗹𝗲𝗻𝘁: AI talent is scarce and critical to success. Hire AI, Data Science, and ML experts or hire specialist AI Development companies. By following these strategies, your AI startup can thrive in an evolving landscape and stay ahead of the competition. 𝗡𝗲𝗲𝗱 𝗲𝘅𝗽𝗲𝗿𝘁 𝗔𝗜 𝗮𝗱𝘃𝗶𝗰𝗲 𝗼𝗿 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻? 𝗟𝗲𝘁’𝘀 𝘁𝗮𝗹𝗸! 𝗦𝘁𝗮𝘆 𝗮𝗵𝗲𝗮𝗱 𝘄𝗶𝘁𝗵 𝗼𝘂𝗿 𝗰𝘂𝗿𝗮𝘁𝗲𝗱 𝘁𝗲𝗰𝗵 𝗻𝗲𝘄𝘀 𝗮𝗻𝗱 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀. 𝗥𝗲𝗽𝗼𝘀𝘁 𝘁𝗼 𝘀𝗽𝗿𝗲𝗮𝗱 𝘁𝗵𝗲 𝘄𝗼𝗿𝗱. 𝗙𝗼𝗹𝗹𝗼𝘄 👉 Anurag Yadav 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝗳𝘂𝗹 𝗽𝗼𝘀𝘁𝘀!