2025 will see AI Product Support and AI Knowledge Management prioritize expertise and depth over breadth to drive customer loyalty, improve accuracy and performance, and reduce the high costs of AI.
2025 will redefine how companies deliver exceptional product support, with expertise, efficiency, and sustainability driving the agenda. Here’s what you need to know:
AI-powered support solutions will shift the focus from more generic customer satisfaction metrics - like NPS or NES - to more outcome-focused metrics and results. With well-architected AI systems, you can deliver expert advice directly through customer self-service or empower human support reps with deep product knowledge. In 2025, customers will measure your success by your ability to solve their problems with AI on the first attempt. Expertise is the new currency of customer loyalty.
Over the past two years, Large Language Models (LLMs) have wowed us with their ability to handle unstructured data—whether as generalists or within Retrieval-Augmented Generation (RAG) pipelines. But this success comes with trade-offs: escalating costs, slower performance, and the persistent hallucinations.
2025 will see a renewed emphasis on structured data, enabling LLMs to evolve from generalists into true specialists in your product and problem domain. Structured data doesn’t just reduce errors; it transforms AI into a precise, domain-specific tool that delivers consistent results.
The AI land grab led by OpenAI, Anthropic, and others feels reminiscent of the Dot-com boom: rapid growth at all costs, fueled by immense spending. While we don’t foresee an immediate bubble burst, rising hardware and energy costs will drive LLM providers to escalate prices.
This will make compute efficiency not just a technology concern but a strategic imperative. Organizations relying on AI-powered support will need to optimize their usage or risk unsustainable cost structures.
Energy consumption will become a critical bottleneck for AI development in 2025. Reports of nuclear facilities like Three Mile Island being considered for recommissioning to support AI data centers underscore the urgency.
The solution? Smarter, targeted AI models. By focusing LLMs on solving specific, structured problems within a well-defined product knowledge framework, companies can reduce both energy costs and environmental impact while maintaining cutting-edge support.
In 2024, AI-driven process automation dominated the conversation in product support. The question leaders addressed was: How can your human experts work more efficiently? By 2025, the focus will shift: expertise will surpass efficiency as the ultimate outcome.
AI will not only empower your support reps to resolve customer issues on the first try but will also turn your customers into experts in your product. Expert customers are happier customers. Expert support are happier employees. This virtuous cycle will deliver faster, better solutions.
In short, AI in product support is shifting from automation to acceleration—from second gear to fifth gear and beyond —as organizations unlock the full value of expertise-driven support.
The advancements in product support by 2025 aren't just abstract trends—they address real challenges in scaling, efficiency, and precision. Here's why these shifts are critical:
The impact of these changes isn’t limited to technical execution; they offer significant strategic advantages for businesses looking to lead in a competitive market. Here’s why this evolution matters:
The changes ahead are clear: structured data, compute efficiency, and expertise-driven AI are the pillars of the next evolution in AI product support. Companies that adopt these principles will not only save costs but also delight customers, delivering results that drive loyalty and long-term growth.