Beyond GenAI: What’s Next for the Enterprise? • Andrew Turner • GOTO 2023

Explore the future of AI in the enterprise beyond generative AI, examining the need for automation, human factors, and responsible adoption to drive transformation and create new value.

Key takeaways
  • The concept of “Beyond GenAI” refers to exploring what’s next in AI, beyond generative AI.
  • The need for automation and AI in enterprises is driven by the increasing complexity of data and the need for more efficient decision-making.
  • The temperature setting in AI models affects the output, but finding the right temperature is crucial.
  • The importance of considering the strengths and weaknesses of AI models and systems.
  • The need for businesses to think about how they can adopt and integrate AI into their operations, rather than simply building it.
  • The importance of considering the human factors in AI adoption, such as training and upskilling employees.
  • The need for a shift in thinking from “how to use AI” to “how to coexist with AI”.
  • The importance of considering the downstream insights and analytics that AI can provide.
  • The use of ChatGPT as a tool for generating responses and creating prompts, but highlighting the need for human oversight and review.
  • The concept of “garbage in, garbage out” applies to AI, where the quality of the data and models used will affect the output.
  • The need for businesses to consider the skills gap in AI adoption and to upskill their employees.
  • The importance of considering the environmental, social, and governance (ESG) implications of AI adoption.
  • The need for a more nuanced understanding of AI, beyond just “AI is good” or “AI is bad”.
  • The concept of “liquid workforce” and the need for businesses to adapt to changing workforce dynamics.
  • The importance of considering the role of AI in decision-making and the need for transparency and explainability.
  • The need for businesses to think about how AI can be used to transform their operations and create new value.
  • The concept of “embodied cognition” and the importance of considering how AI interacts with humans.
  • The need for businesses to consider the impact of AI on employment and the need for retraining and upskilling.
  • The importance of considering the role of AI in customer service and the need for human touch.
  • The need for businesses to think about how AI can be used to create new products and services, rather than just automating existing ones.
  • The concept of “AI-enabled entrepreneurship” and the need for businesses to adapt to changing market dynamics.