Jon Purizhansky | Buffalo News, New York

 Artificial intelligence is rapidly changing the way businesses operate, communicate with customers, and make decisions. From automated customer support to data analysis and personalized marketing, AI tools can create significant advantages for organizations of all sizes. However, building an AI solution without proper planning can result in wasted resources, poor user experiences, security concerns, and disappointing business outcomes. For entrepreneurs and business leaders such as Jon Purizhansky , understanding the common mistakes behind unsuccessful AI projects is essential. Here are three critical mistakes businesses should avoid when developing AI tools. 1. Building AI Without a Clear Business Problem One of the biggest mistakes companies make is creating an AI tool simply because AI is popular. Technology should support a specific business objective rather than become the objective itself. Before developing an AI application, businesses should identify the problem they want ...

For decades, finding a job abroad has often meant navigating a costly, opaque chain of recruiters, sub-agents, staffing firms, paperwork brokers, and placement fees. Artificial intelligence is beginning to break that chain — matching workers directly with legitimate employers at scale, while making recruitment faster, more transparent, and potentially far fairer. The change will not eliminate the human role in recruitment overnight. But as algorithmic matching improves and agentic AI becomes capable of completing multi-step workflows autonomously, the traditional gatekeepers of cross-border hiring will face a profound reset. The labor market’s great mismatch The world does not have a simple “jobs problem” or a simple “workers problem.” It has a matching problem. Many developed economies are experiencing shrinking working-age populations, aging populations, and persistent shortages in essential sectors. The OECD projects that its working-age population will decline by 8% by 2060. In 202...