The art of strategic GenAI adoption

Date:
Tue, 29 Oct 2024 09:49:33 +0000

Description:
How to leverage GenAI for operational tasks, allowing humans to focus on creativity and innovation.

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

You know what the biggest problem with pushing all-things-AI is? Wrong direction. I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.

The post is sassy, but spot on. Its a stark reminder that humans want AI to assist with undesirable and painstaking tasks, not to assimilate creativity. Companies may ultimately want the same thing. They need creative productivity from humans, and they need GenAI to deliver the ROI that keeps the financial house in order, rather than falling into the AI money pit.

If you think this message is coming from yet another company looking to jump on the GenAI bandwagon, think again. We come at GenAI and data management which is critical to GenAI success from a position of unrivaled understanding, experience and commitment.

Heres what weve learned, and what to do in transforming your organization
with GenAI. Be extremely selective in using GenAI

Organizations sometimes fail to take the time to define what it is that they want to get out of GenAI. This has led many companies to go too big too fast or proceed with excess caution, or not move forward at all.

Everest Group says that 2023 saw more than 1,200 GenAI proofs of concept (PoCs), signaling strong enterprise engagement, but less than 18% of PoCs reach production stage. Gartner adds that growth in 90% of GenAI enterprise deployments will slow by 2025 as costs exceed value.

Position your GenAI efforts for success and growth by first defining the problem you are trying to solve. Specify what outcomes you expect. And be selective in using GenAI, because it requires tremendous compute resources
and scaled out IT infrastructure that can handle large data sets, so it can get expensive fast. Also keep in mind that consuming a lot of compute and power will have an impact on the planet and your sustainability goals. So, make sure that youre using GenAI in a sensible manner, and only use GenAI to solve problems that couldnt otherwise be solved. Implement robust policies
and infrastructure

If someone is using GenAI to write a poem, there are no right or wrong answers. But mission-critical enterprise applications are going to require near 100% accuracy. If you dont employ high-quality data in your GenAI efforts, you wont get the results that you are expecting.

Assess where you are 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
ecosystem are well-prepared for GenAI implementation.

Work with data experts to establish and implement robust data management solutions and strategies that address data security and integrity wherever that data may reside.

Also, make sure your GenAI strategy positions you to be agile in this fast-moving environment in which there are a lot of acquisitions and consolidation. Plan and build for GenAI in a way that keeps you flexible because what worked a few months ago may not work in the future. Understand and address risks and regulations

Using high-quality data sets is also important considering the growing regulatory scrutiny around AI and GenAI. For example, the European Unions Artificial Intelligence Act went into effect Aug. 1. This applies to any providers that put AI systems into service within the EU.

The new EU AI Act calls for AI systems that are classified as high risk such as systems that are used for energy and transport, medical devices, and systems determining access to education or employment to implement risk-mitigation strategies. The EU explains that includes achieving high standards of accuracy, cybersecurity and robustness; ensuring human
oversight; maintaining activity logs; providing detailed documentation; and using high-quality data sets.

But the unprecedented volume and complexity of data environments can make
that a challenge. Employ the tools and DataOps processes to understand data lineage, do data cost optimization, and ensure reliability, resilience, and visibility throughout the data lifecycle. Establish a data foundation for innovation

GenAI now makes it easy for virtually anybody to put AI to work, which is accelerating the pace of business transformation at an exponential rate. And thats an extremely powerful thing. With GenAI, you can drive more automation and save on costs. GenAI also can enable product differentiation to drive revenues. If you can become more proactive by using GenAIs infinite knowledge and capacity to act quickly, you can fix problems and deliver better
solutions faster.

But, in the process, GenAI is increasing the storage demands and extending
the infrastructure concerns at enterprises far and wide. To stay competitive, modern businesses like yours must establish a data foundation for innovation allowing your business to run, manage, and harness data and applications wherever they exist on premises, in the cloud, and/or at the edge.

Whether your organization opts to leverage GenAI to save on everyday tasks, build revenue by delivering differentiated services or all of the above, keep in mind that getting GenAI right is both an art and a science. And it
requires people and organizations to leverage both the knowledge earned with years of experience and the latest innovations in data management.

We've 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 the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro



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