Understanding artificial intelligence (AI) in business is not about deciphering the hype created by vendors, but about practical implementation. Businesses need to focus on three significant aspects: data, algorithms, and use cases. Data is the lifeblood of AI, and organisations must ensure they have sufficient quality data to train AI models effectively. Algorithms are the engines that drive AI, but they are not the most critical aspect. Instead, businesses should focus on the use cases that AI can solve.
AI can deliver valuable insights and automation, but businesses should be wary of vendors over-promising and under-delivering. It’s essential to have a clear understanding of what AI can and cannot do, and to set realistic expectations. Companies should also maintain a healthy scepticism towards vendors who claim that their AI solutions are entirely self-sufficient.
AI is not a magic bullet. It requires a significant investment of time, effort, and resources. Therefore, businesses should approach AI with a pragmatic mindset, focusing on achievable goals and measurable results. The key to successful AI implementation lies in understanding its practical applications and limitations.
Go to source article: http://www.zdnet.com/article/practical-ai-for-the-enterprise-getting-past-vendors-blowing-smoke/