5 tips for business leaders to harness the true potential of generative AI

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It feels like generative AI is everywhere. The explosive launch of advanced chatbots and other generative AI technologies, like ChatGPT and others, has captured the attention of everyone from consumers to business leaders to the media.

But these chat tools are just the tip of the iceberg when it comes to the potential impact of AI generation. The even greater value of generative AI will come when companies start applying it on behalf of their customers and employees. There are a huge number of business use cases, from product design to customer service to supply chain management and more. New models, chips, and cloud development services, like those from AWS, open the door to wide-scale adoption across industries.

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Understanding the realm of opportunity – and risk – of generative AI is critically important for CIOs looking to start using this technology to gain an advantage for their business. Here are my five tips for getting started.


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1. Get your data house in order

Generative AI is here, and it’s about to have a transformational impact on our world. The potential upsides of leveraging it in your business are too great – and the downsides of being a latecomer too many – not to start now. But the very beginning of this journey is making sure you have the right databases for AI/ML. In order to train quality models, you need to start with quality, unified data from your business.

For example, Autodesk, a global software company, created a generative design process on AWS to help product designers create thousands of iterations and choose the optimal design. These machine learning models are backed by a strong data strategy for user-defined performance characteristics, manufacturing process data, and production volume information.

2. Consider use cases around your own data

Generative AI could be used to develop predictive models for businesses or to automate content creation. For example, companies could generate financial forecasts and scenario planning to make more informed recommendations for capital expenditures and reserves.

Or generative AI could serve as an assistant to clinicians to create recommendations for diagnosis, treatment, and follow-up care. Phillips does exactly that. The health technology company will use Amazon Bedrock to develop image processing capabilities and simplify clinical workflows through speech recognition, all using generative AI.

We also see AWS customers leveraging generative AI to optimize product lifecycles, such as retail companies looking to more accurately manage inventory placement, out-of-stock issues, deliveries, etc., or use generative AI to create, optimize and test store layouts. By identifying these scenarios early and exploring the art of the possible with the data you already have, you can ensure that your investment in build AI is both focused and strategic.

3. Discover the benefits of developer productivity

Generative AI can provide significant benefits for developer productivity. It can be a powerful assistant for repetitive coding tasks such as testing and debugging, allowing developers to focus on more complex tasks that require human problem-solving skills. CIOs should work with their development teams to identify areas where generative AI can increase productivity and reduce development time.

4. Take outings with a grain of salt

Generative AI is only as good as the data it is trained on, and there is always a risk of bias or inaccuracies. Sometimes the result is a hallucination, a response that sounds plausible but is actually made up. So guide your developers, engineers, and business users to view build AI outputs as directional and not prescriptive.

Manage business expectations for accuracy and consider some of the unique challenges of responsible generative AI. These models and systems are still in their infancy and there is no substitute for human wisdom, judgment and curation.

5. Think carefully about security, legislation and compliance

As with any technology, security and privacy are paramount, and Generation AI introduces new considerations, especially around IP. CIOs should work closely with their security, compliance, and legal teams to identify and mitigate these risks, ensuring that generative AI is deployed in a secure and responsible manner. Additionally, frame your plans around compliance and regulations and think carefully about who owns the data you use.

Generative AI has the potential to be a transformational technology, tackling interesting problems, increasing human performance and maximizing productivity. Dive in now, experiment with use cases, exploit its benefits, and understand the risk, and you’ll be well positioned to leverage generative AI for your business.

Shawown Nandi is the Director of Technology and Strategic Industries at AWS.


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