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VOOZH | about |
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VOOZH | about |
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This is an excerpt from Chapter 2 of “AI for the Enterprise: The Playbook for Developing and Scaling Your AI Strategy,” a new ebook by acclaimed tech journalist Jennifer Riggins and sponsored by Red Hat and Intel.
From the advantages of using the “two-speed” AI investment model, to measuring the real impact of AI, this free book, now available for download, helps enterprise leaders create an AI strategy to unlock productivity gains, solve previously impossible problems and gain a true competitive edge.
Most organizations needed an AI usage policy yesterday. Yet only about half have them.
“How many products have had AI shoved in there while completely ignoring the primary pain points of their products and their platforms?” asked Hannah Foxwell, founder of AI for the Rest of Us. “Your AI strategy needs to be grounded in the business today, not in some fictitious version of the business tomorrow.”
To develop your AI policy, establish a cross-functional, cross-organizational AI enablement team — perhaps seated in the new CAIO office.
The International Organization for Standardization’s AI standards are a good place to start considering your AI policy:
The European Union’s AI Act offers another good way to classify risk around AI tooling:
This categorization may vary for different parts of your business, depending on their levels of risk acceptance or avoidance.
It’s also wise to give everyone in your organization a refresher in local and international data privacy regulations, like the EU’s GDPR and the California Privacy Rights Act (CPRA). Generative AI (GenAI) tools’ ease of use and adoption have already led to inadvertent data leakage — you don’t want to be next.
Once your AI enablement team agrees on an AI usage policy, make sure you communicate it with all stakeholders inside and outside the organization.
Grammarly has been using AI in its product for the last 15 years, and its User Trust Center has become an industry standard for clear AI communication. It breaks the risks down into four areas:
“Managers and leaders are going through this learning journey alongside their teams, so you can’t look to your manager for concrete advice,” Foxwell said. “A centralized enablement team or external training partner is a good way to go if you want to get consistent messaging.”
Don’t forget that your AI strategy must also factor the SaaS products you are already using. If they’ve injected some sort of AI into the product, has your company vetted it for compliance?
Since these risks and use cases vary by domain, you can’t have one policy to rule them all. Consider some overarching data and security rules, but then allow subject matter and domain experts to weigh in on department-specific aspects. And ground any policies in examples based by domain or department.
As you create this AI usage policy, just remember to “translate” it from legalese to lay terms so that all employees understand. This is a good use case for GenAI — so long as you have a human reviewer in the loop.
To read more, download “AI for the Enterprise: The Playbook for Developing and Scaling Your AI Strategy” today!
👁 "AI for the Enterprise" ebook cover
