British Gas took 15 months to issue a final bill and refund more than £1,500 to a customer, Beth Kojder, despite a ruling from the energy ombudsman nearly a year prior. Kojder moved out of her one-bedroom flat in south-east London in October 2024 and subsequently filed a complaint with the ombudsman when British Gas failed to provide a final bill or refund her credit balance.

The energy ombudsman ruled in Kojder's favor in February 2025, instructing British Gas to fulfill her request. However, the ombudsman lacks the legal authority to enforce its decisions. Kojder received an offer for her refund this week, shortly before her case was scheduled to be heard in a small claims court.

British Gas stated that it was "implementing the ombudsman's remedy" for Kojder and apologized for the delay. The company acknowledged the extended timeframe and expressed regret for the inconvenience caused.

Kojder described the process as "relentless," "tiring," and "completely draining" in a statement to the BBC. She initially requested a final bill from British Gas, providing meter readings when she moved out of her flat.

The delay highlights ongoing concerns about customer service and billing accuracy within the energy sector. While automated systems are increasingly used for billing and customer interactions, cases like Kojder's demonstrate the limitations of these systems when dealing with complex situations or errors. The reliance on algorithms and machine learning in customer service raises questions about accountability and the potential for bias in automated decision-making processes.

The use of AI in customer service is a growing trend, with companies implementing chatbots and automated systems to handle routine inquiries and streamline operations. However, these systems can struggle with nuanced issues that require human intervention. The challenge lies in developing AI systems that can effectively address customer needs while maintaining transparency and fairness.

The latest developments in AI include advancements in natural language processing (NLP), which enable AI systems to better understand and respond to human language. However, even with these advancements, AI systems are not always capable of resolving complex issues without human assistance.

The implications for society include the potential for increased efficiency and cost savings through the use of AI in customer service. However, there are also concerns about job displacement and the need for retraining and upskilling workers to adapt to the changing job market. Furthermore, there are ethical considerations related to data privacy, algorithmic bias, and the potential for AI systems to perpetuate existing inequalities.

Dan Whitworth, a Money Box reporter, also covered the story. The case underscores the importance of regulatory oversight and consumer protection in the energy sector.