Understanding the Challenge
The current landscape of artificial intelligence is facing a potential downturn, often referred to as a fourth AI winter. Many experts are questioning whether AI can deliver enough real-world value to justify its costs. This skepticism is fueled by a high failure rate of AI projects, with approximately 87% not making it to successful implementation. The root cause lies in the lack of a structured approach to transition AI breakthroughs from research to practical applications. Unlike other scientific fields, AI lacks a distinct discipline focused on applying research effectively, leading organizations to rely on data scientists who may not have the necessary engineering skills.
Key Insights
- The concept of engineered intelligence is introduced as a solution to bridge this gap.
- This discipline emphasizes collaboration between domain experts, scientists, and engineers to create practical AI applications.
- Organizations are encouraged to establish research-to-engineering pipelines and partnerships with academic institutions.
- A five-step process is proposed to identify and leverage existing expertise within organizations for successful AI implementation.
The Bigger Picture
Adopting engineered intelligence could revolutionize how organizations approach AI, leading to more successful projects and innovative applications. By focusing on practical expertise and collaboration, businesses can unlock the true potential of AI. This shift could not only prevent the impending AI winter but also create new job opportunities and drive economic growth. As industries embrace this new approach, society stands to benefit from the advancements and efficiencies that engineered intelligence can provide.
