OKR's in the age of Generative AI

Objectives and Key Results (OKRs) have long been a cornerstone of effective organizational goal-setting. Some have complained about it as well.

As generative AI reshapes industries, companies must evolve their OKR strategies to harness AI's potential while addressing new challenges.

OKRs can be relative in the era of generative AI by addressing the following challenges

• AI-Enhanced Goal Setting: With its ability to analyze enormous volumes of data and see patterns and opportunities, generative AI can assist leaders in creating more well-informed and ambitious goals. To understand AI-generated recommendations and match them with the company's principles and long-term goals, human expertise is still necessary. ( I am moving away from Human in the loop to Human enabled).
• Dynamic Key Result: AI is accelerating the rate of change, defying Moore's law and some say Right's law, important outcomes can require more regular updates. Understanding #VUCA ( Volatility, Uncertainty, Complexity, Ambiguity) coupled with PESTLE analysis is even more important. Companies should think about putting in place tools for measuring and adjusting OKRs in real time, which will enable teams to react quickly to changes in the market caused by AI.
• AI Productivity Metrics: With the increasing use of AI systems, new measures are required to assess success and productivity. Key outcomes related to AI should be included in OKRs, such as increased accuracy in AI models or efficiency gains from AI integration.
• Ethical Considerations: Objectives including guaranteeing algorithmic fairness, protecting data privacy, and minimizing potential negative effects of AI deployment are now required to be included in OKRs when discussing responsible AI use. This is an area, I struggle with as "Ethics at the cost of Innovation". Are we hyping or overly concerned about "AI Ethics when in reality we need to consider Human Ethics"? Rogue nations and people have no barriers and will have an edge as they do not have breaks. This is a highly debatable topic. As they say "What is right in one culture is wrong in another culture ". I am no pundit or guru but just asking.
• Upskilling Objectives: Companies should define OKRs centered on staff AI literacy and upskilling to stay competitive. This guarantees that workers can work together productively with AI tools and adjust to changing job demands.
• Innovation Balance: In addition to utilizing AI to increase productivity, OKRs ought to foster critical thinking and human innovation. Long-term success requires striking a balance between human-led innovation and AI-driven optimization. ( concepts like Skunkworks, and McKinsey's 3 horizons of growth can play a leg-up in innovation).

Organizations can manage the generative AI revolution more skillfully, driving development while controlling risks and cultivating a culture of constant adaptability, by carefully incorporating AI issues into their OKR framework.