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The Art of Strategic Adoption of GenAI

Pabio October 29, 2024

Have you seen this article on GenAI – now almost an adage of the times?

“You know what the biggest problem is with promoting anything related to AI? Bad direction. I want AI to do my laundry and dishes so I can do art and writing, not AI to do my art and dishes so I can do my laundry and dishes.

The message is sassy, but perfect. This is a stark reminder that humans want AI to help them accomplish undesirable and tedious tasks, not to assimilate creativity. Businesses may ultimately want the same thing. They need creativity productivity humans, and they need GenAI to provide the ROI that keeps the financial picture in order, rather than falling into the AI money pit.

If you think this post is from another company looking to jump on the GenAI bandwagon, think again. We come to GenAI and data management – which is critical to GenAI’s success – from a position of unparalleled understanding, experience and commitment.

Here’s what we learned and what to do to transform your organization with GenAI.

Sheila Rohra

Be extremely selective in using GenAI

Organizations sometimes don’t take the time to define what they want to get out of GenAI. This has led many companies to grow too big, too fast, or act with excessive caution, or even not move forward at all.

Everest Group says that in 2023, more than 1,200 GenAI proofs of concept (PoCs) have been completed, demonstrating strong corporate engagement, but less than 18% of PoCs have reached the production stage. Gartner adds that 90% growth in enterprise GenAI deployments will slow by 2025 as costs outstrip value.

Position your GenAI efforts for success and growth by first defining the problem you are trying to solve. Specify the results you expect. And be selective in using GenAI, as it requires huge computational resources and is scalable. IT infrastructure which can handle large data sets, which can quickly become expensive. Also keep in mind that consuming a lot of computing and energy will have an impact on the planet and your sustainability goals. So make sure that you use GenAI wisely and only use GenAI to solve problems that could not be solved otherwise.

Implement strong policies and infrastructure

If someone uses GenAI to write a poem, there is no right or wrong answer. But critical businesses applications will require accuracy close to 100%. If you don’t use high-quality data in your GenAI efforts, you won’t get the results you expect.

Evaluate where you stand with your GenAI and data strategies. Our recent research indicates that less than half (44%) of organizations have well-defined GenAI policies, and even fewer (37%) believe their infrastructure and data The ecosystem is well prepared for the implementation of GenAI.

Work with data experts to establish and implement robust data management solutions and strategies that ensure the security and integrity of data, wherever it resides.

Also make sure your GenAI strategy positions you to be agile in this rapidly changing environment in which there are many acquisitions and consolidations. Plan and build for GenAI in a way that allows you to remain flexible, because what worked a few months ago might not work in the future.

Understand and manage risks and regulations

The use of high-quality datasets is also important given the increasing regulatory scrutiny around AI and GenAI. For example, the European Union’s artificial intelligence law came into force on August 1. It applies to all suppliers who commission AI systems within the EU.

The new EU AI law calls for AI systems classified as high risk – such as systems used for energy and transport, medical devices and systems determining access to education or employment – to implement risk mitigation strategies. The EU explains that this involves achieving high standards of accuracy, cybersecurity and robustness; ensure human surveillance; keep activity logs; provide detailed documentation; and using high-quality datasets.

But the unprecedented volume and complexity of data environments can make this difficult. Use DataOps tools and processes to understand data lineage, optimize data costs, and ensure reliability, resiliency, and visibility throughout the data lifecycle.

Establish a database for innovation

GenAI now makes it easy for virtually anyone to put AI to work, accelerating the pace of business transformation at an exponential rate. And that’s an extremely powerful thing. With GenAI, you can drive more automation and save on costs. GenAI can also enable product differentiation to generate revenue. If you can become more proactive using GenAI’s infinite knowledge and ability to act quickly, you can solve problems and come up with better solutions faster.

But in doing so, GenAI increases storage requirements and expand infrastructure concerns in large-scale businesses. To stay competitive, modern businesses like yours must establish a database for innovation, enabling your business to run, manage and leverage data and applications wherever they exist – on-premises, in the cloud and/or at the edge.

Whether your organization chooses to leverage GenAI to save money on daily tasks, generate revenue by providing differentiated services, or all of the above, keep in mind that managing GenAI well is both an art and a science. And it requires individuals and organizations to leverage both the knowledge gained through years of experience and the latest innovations in data management.

We have listed the best AI tools.

This article was produced as part of TechRadarPro’s Expert Insights channel, where we feature the best and brightest minds in today’s technology industry. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you’re interested in contributing, find out more here:

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