Responsible AI Adoption - Companies should define red lines, assess human vulnerabilities, ensure explainability of AI decisions, and have contingency plans before deploying AI solutions [7][8][9] - Companies are advised to avoid becoming the "scientists in Jurassic Park" by carefully considering the ethical implications of AI use cases [10] - Companies should prioritize transparency, trust, and sustainability as ethical competitive advantages in AI adoption [19][20][21][22] AI Implementation Challenges - Companies are experiencing a race for efficiency with AI, achieving 15% efficiency gains but facing unanticipated side effects in one-third of cases [16] - Companies are engaging in a data race, collecting four times more data than they can manage responsibly, while overlooking IP, copyright, and data privacy [17] - Companies are facing a talent race with a scarcity of AI ethics specialists, reflected in a ratio of 1 ethics specialist for every 15 AI engineers [18] AI Coordination and Framework - Companies need internal coordination between AI officers, ethics committees, security teams, and communication teams [24][25] - Companies need external coordination with regulators, civil society, and competitors to control the AI race [25] - The RACE framework for AI coordination includes responsibility mapping, accountability systems, coordination efforts, and ethical innovation [26]