This morning I attended a Technology First Cybersecurity session at the Digital Transformation Center in Dayton Ohio. It was my first introduction to the center. it is a significant focal point for Ohio educational, governmental and commercial interests, hosted by the University of Dayton’s Research Institute (UDRI). I was surprised to learn that both my alma maters are sponsors: Ohio University and the University of Dayton.
The session was led by Randy Hinders of MileTwo and focused on Digital Tools and Cross Integration. The group talked about several challenges, including shadow IT and shadow AI. Shadow IT, or the introduction of computing resources outside of traditional IT acquisition, management and support, often bedevils an organization’s IT groups.
Shadow AI, on the other hand, is the intentional or accidental introduction, evaluation, testing and adoption of artificial intelligence tools. Shadow AI is mostly targeted at the production or work layer of the organization, as well as the IT development community. Workers are empowered to discover and employ AI as an adjacent technology to help them in the completion and improvement of their tasks and products.
Shadow AI is not a pejorative term. Rather, it represents what I see as the inversion of the adoption hierarchy, which ultimately may become the “new new” in organizational thinking. In the inversion, the real organizational value rests in the hands of the user. It represents the potential of workforce creativity,
IT as well as business management will become facilitators and guides as AI learning becomes more commonplace. Governance will remain in its traditional top-down role, providing sponsorship, funding, direction, policies and guidelines.
The real changes and power, however, will be in the hands of end users working with AI tools on their traditional work. Improvements and changes will be invented here, Business and IT management will find themselves acting in the capacity of coaches and participants in the examination and exploration of AI capabilities.
New attention will be given to knowledge and data interactions with AI through training and resource models, as well as the protection of organizational data and intellectual property. Small and localized models will become important to specific and proprietary research. Regulatory and competitive oversight will influence the mix of both technical and creative activities; business and technical thinking will begin to blend into more productive interactions. A renaissance of sorts will characterize the influence of AI and human interaction.
The most important contribution that both business and IT management can make in this uptake of AI is the areas of organizational collaboration and learning. AI is the horse that’s left the gate, now the challenge is how to harness and guide the attention and energy it will produce as change becomes the status quo.
Good insights for a Wednesday morning meeting.
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