Being realistic means understanding the pros and cons and sharing this information with customers, employees, and peers in the C-suite. They’ll also appreciate your candor. Make an authoritative warts-and-all list so they can be clearly explained and understood. As AI advisors have pointed out, some downsides include the black box problem, AI’s vulnerability to misguided human arguments, hallucinations, and the list goes on.
Establish a corporate use policy
As I mentioned in an earlier article, a corporate use policy and associated training can help educate employees on some risks and pitfalls of the technology, and provide rules and recommendations to get the most out of the tech, and, therefore, the most business value without putting the organization at risk. In developing your policy, be sure to include all relevant stakeholders, consider how gen AI is used today within your organization and how it may be used in the future, and share broadly across the organization. You’ll want to make the policy a living document and update it on a suitable cadence as needed. Having this policy in place can help to protect against a number of risks concerning contracts, cybersecurity, data privacy, deceptive trade practice, discrimination, disinformation, ethics, IP, and validation.
Assess the business value for each use case
In the case of purely textual output, we tend to believe answers from gen AI because they’re written well with excellent grammar. Psychologically, we tend to believe there’s a powerful intelligence behind the scenes when actually gen AI has no understanding of what is true or false.
While there are some excellent use cases for gen AI, we need to review each one on a case-by-case basis. For example, gen AI is typically bad at writing technical predictions. The output often tells us something we already know, and it may also be plagiarized. Even using a rewriting or rephrasing tool can make matters worse, and teams can end up spending more time using these tools than if they wrote predictions themselves. It’s best to pick your battles and only use gen AI where there’s a clear benefit to doing so.
Maintain rigorous testing standards
With gen AI most likely being utilized by a large number of the workforce in your organization, it’s important to train and educate employees on the pros and cons and use your corporate use policy as a starting point. With so much adoption of gen AI, we’re all effectively testers and learning as we go.
Inside your organization, whether within the IT department or business units, be sure to emphasize and allow considerable time for testing and experimentation before going live. Setting up internal communities of practice where employees can share experiences and lessons learned can also help raise overall awareness and promote best practices across the organization.
