Generative artificial intelligence, or generative AI, is a topic that’s popping up in conversations everywhere, from classrooms to boardrooms. Some people are excited about it. Others fear it. However, most have questions about it.
As business leaders gain a better understanding of the power of generative AI and its benefits — like improving human efficiencies and creating personalized experiences — they may want to consider how it will affect their industry and worker productivity today and in the future. They’ll also want to ask about deployment strategies and how to find trusted partners.
While generative AI technology is continuing to evolve rapidly, here are four things to consider before adding it to your businesses’ arsenal of tools.
1. Establish a trusted data source for reliable and scalable generative AI
Input will always determine output — and before the business can trust insights provided by a new technology like generative AI, they must trust the data that’s informing it. To determine if generative AI can be successfully scaled and relied on, organizations need a data foundation that includes a strong and agile data strategy, emphasizes data privacy and data quality, and looks at the addition of new technology through their IT estate, rather than just one silo.
“Data is the fuel for generative AI. If you’re feeding the machine quality data, you’re more likely to receive reliable insights,” said Nicolas Sekakki, Global Practice Leader for Applications, Data and AI at Kyndryl. “Before an organization can turn their dream of scaling generative AI into a reality within their business, they must first establish a strong data foundation.”
2. Examine use cases before applying generative AI technology
“While generative AI tools can increase worker productivity and the employee and customer experience, not all opportunities warrant the investment,” said Ivan Dopplé, Global Practice Leader for Digital Workplace Services at Kyndryl. “It’s critical to have experts guiding you in the identification of use cases for generative AI and application of the technology to ensure you receive a return on your investment.”
Enterprises should consider utilizing resources, like the AI-readiness program within Kyndryl Consult, which provides customers with one-on-one services to explore opportunities to responsibly apply generative AI within their business to drive efficiencies, deliver greater value and help achieve goals.
3. Leverage Large-Language Model Operations (LLMOps) frameworks
For a business to derive value from its data and generative AI technology in a responsible and cost-effective manner, it must use Large-Language Model Operations (LLMOps) frameworks — and those frameworks must be incorporated into a larger data and AI architecture.
“Great opportunity comes with great responsibility — and as businesses consider incorporating generative AI into their organization, they must also consider the impact on their entire data and AI architecture,” said Sekkaki. “By utilizing LLMOps frameworks and collaborating with our Data and AI experts, businesses can ensure the data being used is safe and reliable, and that the correct architecture is in place to route the insights once generated.”
4. Tap a trusted partner with strong expertise to help manage your growing IT estate
As your business adds more and new technologies — whether that’s generative AI or something else — IT estates become more complex and difficult to manage. By using the AIOps and FinOps services available on Kyndryl Bridge, and the automation expertise provided by Kyndryl, customers can achieve their business goals in a cost-effective, insightful and responsible manner.
“The IT world is constantly changing — whether that’s through the evolution of existing capabilities, or new innovations to improve the employee and customer experience,” said Dopplé. “It’s critical to have trusted voices in your corner to provide recommendations on the optimal use of your resources, technologies and architectural options.”
