While the effects of automation and AI in the workplace can often defy our intuition, and much of the discussion remains rooted in theoretical territory, recent studies on AI adoption allow us to sketch some broad conclusions and considerations for companies:
- Predicting the fate of individual jobs, especially those involving the "last mile"—where automation handles 99% of the work, but that crucial 1% still calls for a human touch—can be astoundingly complex. Identify the “last mile” for key decisions and actions and ask if the inherent variability (hallucinations for example) are tolerable. Is GenAI a net positive or negative or neutral in these situations?
- Humans, with their innate ingenuity, often repurpose AI in ways its creators never envisaged. This unexpected human agency produces surprising outcomes, as it influences the effectiveness of AI deployment in the real world. Consider the role of human agency and the changes which might happen when humans and GenAI interact. Ask, how can we use the combination of human agency and machine variability to envisage new creative processes?
- Companies that incorporate AI usually evolve into leaner, more decentralized entities with autonomous operations and a higher concentration of technical roles compared to their non-AI investing counterparts. Consider how your company would look with more need for technology. How would that change the demand for certain skills?
- However, AI often disappoints when it comes to delivering financial benefits, particularly when jobs and technology aren't harmoniously designed to foster mutual learning between humans and machines. Consider what happens when companies are overinvested in experimental technology and under invested in the complex system of humans who use the machines. Ask how best to prepare for more diverse skills sets and organizational complexity.
The influence of AI on productivity presents a convoluted puzzle, which Generative AI only complicates further. As it diffuses across areas of knowledge work, human creativity, and inventiveness, the dialogue around AI's impact on productivity becomes more complex and intricate.
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