Decision Intelligence & AI Strategy - Decision intelligence is defined as turning information into better action across any scale or setting, breaking down silos between decision-making disciplines like psychology, social sciences, managerial sciences, and data/mathematical sciences [4] - Many decision-makers believe they are data-driven when they are merely data-inspired or data-decorated, leading to confirmation bias; pre-committing to how information will drive decisions is crucial [6][7][8][9] - In the age of generative AI, the abundance of "right answers" can be overwhelming; limiting options and defining "good" outcomes becomes essential [12][13][15][16] - Organizations should focus on what they value most to optimize decisions when faced with numerous similar options generated by AI [20] - AI can assist in generating options, but humans must drive the process, set criteria, and maintain control to ensure technology serves people [22][23] Generative AI Value & Implementation - A "generative AI value gap" exists between individual users finding value and organizations struggling to measure that value; scaling AI requires defining ROI and success metrics [24][25] - Leaders must define why AI is being implemented and what constitutes a "good" or "better" answer for the system to succeed [26] - AI can be used as a "thought partner" to brainstorm and identify overlooked aspects or assumptions in decision-making [29][30] - Generative AI democratizes access to technology by allowing users to interact with machines in their own language, but precision is sacrificed [34][35] - Organizations must establish guardrails and safety nets for AI systems due to their potential for surprise, uncertainty, complexity, and chaos [36][38] The Future of Work & AI - AI and machine automation will automate more "thunking" (routine tasks), requiring a shift in how organizations manage "thinking" (creative and engaged moments) [48] - Companies should avoid simply compressing work hours after automating tasks; instead, they should focus on optimizing for creative ideas, healthy cultures, and productive work environments [49][54] - Organizations need to address how to handle the "empty space" created by automation to foster creativity and engagement [53]

AI and Leadership - AI is lowering the cost of expertise, requiring leaders to rethink organizational aspects [1] - Leaders should avoid "falling asleep at the wheel" with AI [1] - Learning from the AI-native generation of MBAs is crucial [1] Microsoft's Initiatives - Microsoft has a WorkLab podcast exploring innovations and disruptions in the way we work [1] - The WorkLab podcast features conversations with economists, technologists, and researchers on AI and thriving in a digital age [1] - Microsoft offers a WorkLab newsletter with AI research, insights, and trends [1] - Microsoft provides resources on the future of work via its WorkLab website [1] Engagement Channels - The WorkLab podcast is available on Apple Podcasts and Spotify [1] - Microsoft encourages users to subscribe to its YouTube channel [1] - Microsoft maintains a presence on LinkedIn, Twitter, Facebook, and Instagram [1]