P2P

16 P E E R T O P E E R : I L T A ' S Q U A R T E R L Y M A G A Z I N E | S U M M E R 2 0 2 3 Not to mention the fact that most AI models in their current state can "lie." Instead of stating, "I do not know," they can spit out plausible, convincing, and sourced answers that are completely made up, leaving companies that take these answers at face value liable for error, and if you are in the legal field open to sanction. Adopting GAI before Government Regulation Because of these major regulatory gaps and the nascency of AI research, relying on GAI in its current form for accurate information is risky business. Especially when it comes to liability and protecting company data, it leaves companies vulnerable. That lack of government regulation and ensuing business risk, however, is not stopping organizations from integrating GAI into their tech ecosystems and operational workflows. For these organizations, the opportunities that come with being a first mover are just too great. Those competitive advantages include increased productivity and efficiency, and more time for critical thinking–made possible by GAI's ability to eliminate time- consuming manual tasks. Using GAI as a prompt to spark creativity or to provide a first draft can be enormously helpful when starting projects. Being a first mover also gives companies the opportunity to be a leader in the field. Because early adopters become experts before anyone else, they're set up to become key players when it comes time to establish industry standards. Early adopters also have the chance to optimize the technology while others play catchup, which can improve brand identity down the line as GAI becomes more important to customers. And for those looking to solve client problems with AI, there's an opportunity to corner emerging markets. The key to being a first mover and successfully implementing early-stage, unregulated GAI at any organization is to create custom guardrails that limit its harm while empowering these benefits. Until government regulation catches up, it will be up to businesses to self-monitor the uses of AI within their own specific contexts and build a roadmap for implementation that ensures data safety and accuracy of results. Though GAI imposes many risks, with a clear compliance strategy and the right workf lows in place, you can use it to successfully drive company goals and deliver more value to clients. GAI Guardrails: Getting Clear on Your Why and How The process for setting up guardrails around AI within an organization is the same process required when introducing any new kind of technology or automation: You define your "why," then you design your "how." First, it's critical to develop a clear vision for what you want the tool to help you do and determine specific use-cases around those goals. This is your "why." For example, your "why" might be as simple as increasing efficiency and productivity. Consider conducting an employee survey before starting this work. The data collected can help you identify beneficial use cases and identify potential threats. Look into how employees are using the tool and how it benefits them in their jobs right now, and then build workflows and guardrails around that. When you've identified your "why" and the specific use cases for GAI within your organization; then you can develop your "how." Your vision for the tool will help you carve out specific workflows for GAI that map back to the use-case. For example, if increasing efficiency and productivity is your end goal, then one workflow might be a process for automating emails to clients and another might involve summarizing a block of text during research. F E A T U R E S

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