AI Shift: 2025 B2B Focus to Revolutionize Sales, Battery Tech, and Medical Advancements

December 24, 2024
AI Shift: 2025 B2B Focus to Revolutionize Sales, Battery Tech, and Medical Advancements
  • According to a McKinsey report, generative AI (GenAI) is revolutionizing B2B sales by enhancing efficiency and reshaping sales operations while maintaining the core roles of sellers.

  • This shift indicates a future where AI plays a crucial role in innovation across various industries, transcending traditional text-based applications.

  • The future of sales models is expected to focus on customer outcomes and foster collaboration between human and AI-driven agents, requiring businesses to adopt agile strategies.

  • Jack Hidary, CEO of Sandbox AQ, discussed the future of artificial intelligence on CNBC's 'Money Movers,' emphasizing a significant shift towards business-to-business (B2B) applications.

  • Hidary forecasts that starting in 2025, AI will increasingly focus on addressing critical challenges in B2B sectors, particularly in enhancing battery technology and accelerating medical advancements.

  • Companies integrating generative AI are reporting improved customer experiences, streamlined sales processes, and new growth opportunities.

  • While the fundamental roles of sellers remain unchanged, generative AI offers productivity improvements through automation and personalized insights.

  • The article culminates with a selection of AI stocks ranked by hedge fund sentiment, sourced from Insider Monkey's database of 900 hedge funds.

  • The article highlights Hyperscale Data, Inc. (NYSE:GPUS) in relation to other AI stocks that investors are currently monitoring.

  • The article reviews the current landscape of AI news and ratings, focusing on major companies such as Amazon.com, Microsoft Corporation, and Advanced Micro Devices.

  • Hidary emphasized the untapped potential of quantitative AI (QAI), which utilizes fundamental equations to generate new data, impacting industries such as pharmaceuticals, automotive, and energy.

  • Unlike large language models that primarily reduce operational costs, large quantitative models are expected to create substantial economic value through innovations in product development.

Summary based on 4 sources


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