A large percentage of people use Generative AI at work. These users often report that AI has reduced their working time for almost half of the professional tasks they do. However, individual performance gains do hardly automatically lead to an increase in organizational performance.
At the same time, most users of Generative AI in industry and academia, as educators and students, are often unwilling to talk openly about their effective use of generative AI.
Why is that?
They fear shaky legal foundations and unclear AI ethics. Many try to avoid the risk of financial disadvantages. Or they are afraid of earning mistrust if they expose an AI-based co-worker.
How can we overcome this blockade?
I would advise organizational leadership to take a systemic, even holistic approach to implementing Generative AI across their entire organization.
This is an accelerated change that comes on top of everything else. However, it cannot be outsourced as every organization's prerequisites and needs are different.
For media organizations and corporate newsrooms, it may be best to hire independent interim editorial managers to guide them through this intense change with focus and fresh insights.
Bottom line
To start with, I recommend three lines of action:
1. create spaces in your organization to engage largely in research and development yourself.
2. model clear and precise Generative AI guidelines from the bottom up. Develop positive use cases, build prompts and tools that work. Integrate AI experiences into the strategic thinking and mission of your organization.
3. create psychological safety, reward first movers and self-learning cyber experts, define active roles and responsibilities.
Sources:
1. Alexander Bick, Adam Blandin, and David J. Deming, The Rapid Adoption of Generative AI, September 2024.
Find selected graphs from this paper in the article.
2. MIT Technology Review, Insights, in cooperation with Databricks, The great acceleration: CIO perspectives on generative AI, August 2023.
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