Enterprises Must Modernize Before Starting Generative AI Projects

Strategies should include upgrading data management, ensuring data integrity and securing cloud environments

Paras Chandaria, Executive chairman, UST

July 1, 2024

3 Min Read
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Generative AI has moved from the theoretical to the mainstream more rapidly than perhaps any other technology in recent memory. The ease of access and intuitive nature of generative AI have encouraged widespread adoption for both personal and business use and millions of daily users are understanding that the more they experiment with generative AI the better it gets. We’ve seen many once-vaunted technologies fail to find their “killer apps” while interest slowly fizzles out, but generative AI seems living up to the hype.

There is already an understanding that generative AI, though still in its infancy, has the potential to revolutionize various domains and industries by enhancing creativity, personalization and innovation. The sheer range of its uses has created a rush to adopt generative AI as well as to invest in bespoke solutions and training as enterprises fear losing a step to more tech-savvy competitors.

Openness to new technology is good, but firms must remember that there is no one-size-fits-all approach to how generative AI is integrated into their organizations. Identifying the right tactics will require taking a step back to evaluate if the infrastructure is fully prepared to support and executive any generative AI plan.

Effective integration of generative AI effectively requires that enterprises do more than simply update their technology. Instead, they must adopt a comprehensive modernization strategy. While this will look different for each company, a nuanced strategy will typically involve upgrading data management and cloud infrastructure while simultaneously preparing for the inevitable challenges these advancements bring. Ensuring data integrity and secure cloud environments is not only crucial for long-term AI success, but for a range of other efforts as well.

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Addressing integration challenges — cultural resistance, data quality, or system compatibility — requires a comprehensive approach. These obstacles can be overcome through cultural adaptation, stringent data governance and selecting interoperable AI solutions. All of these tactics can help ensure a seamless transition to AI-enabled operations. In addition, businesses must remain mindful of existing regulations. The rapid pace of AI development as well as evolving legal and privacy considerations necessitate a well-thought-out integration plan that adheres to strict data privacy standards and incorporates privacy-by-design principles. 

The rise of generative AI is reshaping our approach to workforce management. As AI takes on more tasks, we're shifting resources, focusing human talent on areas that demand creativity, strategic insight and innovation. This realignment ensures our workforce remains a vital asset in the AI-enhanced landscape, complementing technological capabilities with irreplaceable human skills. 

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However, once a business has decided and implemented its ideal AI approach, it is critical to build in adaptability so that it remains flexible enough to meet future needs. This will consider potential regulatory changes but also the ability to adapt to changing environments and scale up as demand grows. Beyond easing the development and deployment of generative AI, modernized infrastructure, which includes robust and reliable hardware, software, data and security platforms, supports the ongoing maintenance and scalability of flexible AI applications across an organization.

Embracing generative AI is a huge step and can define an organization’s trajectory for years to come. This underscores the importance of identifying the right approach so that businesses will not be forced to backtrack if initial projections prove inaccurate.  After all, in a field that is evolving this rapidly, there are bound to be significant disruptions over the coming years.

While generative AI has seemingly limitless potential, businesses should avoid leaping before they look and must instead take time to develop their approach. In doing so, they will be better positioned to forge a strategy that adequately addresses the cultural, technical regulatory and ethical aspects of this emerging technology. Only by doing so can businesses position themselves for success while also ensuring that AI initiatives are consistent with their objectives, values and vision.

About the Author(s)

Paras Chandaria

Executive chairman, UST, UST

Paras Chandaria is the executive chairman of UST, a global provider of digital transformation solutions headquartered in Aliso Viejo, California.

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