#Businessstrategy

Southwest Airlines recently ended its long-standing “bags fly free” promise, introducing $35 and $45 fees for checked bags. The move, effective immediately, aims to boost revenue by about $1–1.5 billion but could cost the airline as much as $1.8 billion in market share losses. In short, the policy change may deliver a short-term gain at a potentially steep long-term cost, according to an analysis by Forbes.

This issue resonates beyond airlines. It highlights how businesses must balance immediate financial pressures with the trust and fairness that underpin customer loyalty. Southwest built its identity on hassle-free travel and clear pricing, and the abrupt shift challenges that image.

A new framework released in early May by a leading fintech group product manager is making waves throughout the global business and technology communities, urging organizations to reconsider the automatic use of large language models (LLMs) for every artificial intelligence (AI) application. The article, recently published by VentureBeat, cautions that LLMs—despite their popularity—are not always the best fit for all customer needs and often prove costly and imprecise compared to other machine learning (ML) or rules-based solutions (VentureBeat).

A new framework released in early May by a leading fintech product manager is sparking debate in global business and tech circles. It urges organizations to pause before automatically adopting large language models (LLMs) for every AI need. The piece, summarized by VentureBeat, notes that while LLMs are popular, they are not always the best fit, and can be costly and less precise than alternative machine learning (ML) or rules-based solutions.