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It feels like generative AI is everywhere. The explosive launch of advanced chatbots and other generative AI technology, such as 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 gen AI. The even greater value of generative AI will come as companies begin to apply it on behalf of their customers and employees. There are a myriad of business use cases, from product design to customer service to supply chain management and many, many more. New models, chips, and developer services in the cloud, such as those from AWS, are opening the door to widespread adoption in every industry.
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Understanding the opportunities—and the risks—of generative AI is critical for CIOs looking to leverage this technology to benefit their business. Below are my five tips to get started.
1. Organize your data house
Generative AI is here and about to have a transformative impact on our world. The potential benefits of using it in your business are too great – and the drawbacks of being a straggler too many – not to start now. But the very beginning of this journey is making sure you have the right data base for AI/ML. To train quality models, you need to start with high-quality, unified data from your company.
For example, Autodesk, a global software company, built a generative design process on AWS to help product designers create thousands of iterations and choose the optimal design. These machine learning models are based on a strong data strategy for user-defined performance characteristics, manufacturing process data, and production volume information.
2. Imagine use cases around your own data
Generative AI can be used to develop predictive models for businesses or automate content creation. For example, companies can generate financial forecasts and scenario planning to make more informed recommendations for capital expenditures and reserves.
Or generative AI can act as an assistant to clinicians to make recommendations for diagnosis, treatment and aftercare. Phillips does just that. The health technology company will use Amazon Bedrock to develop image processing capabilities and simplify clinical workflows with speech recognition, all using generative AI.
We’re also seeing AWS customers using generative AI to optimize product lifecycles, such as retail companies looking to more accurately manage inventory placement, out-of-stock issues, deliveries, and more — 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 Gen AI is both targeted and strategic.
3. Dive into developer productivity benefits
Generative AI can provide significant benefits to developer productivity. It can be a powerful assistant for repetitive coding tasks such as testing and debugging, freeing developers to focus on more complex tasks that require human problem-solving skills. CIOs need to work with their development teams to identify areas where generative AI can increase productivity and reduce development time.
4. Take results with a grain of salt
Generative AI is only as good as the data it’s trained on, and there’s always a risk of bias or inaccuracy. Sometimes the output is a hallucination, a response that seems plausible but is in fact made up. So guide your developers, engineers and business users to view gen AI outputs as guiding, not prescriptive.
Manage the business expectations about accuracy and be mindful of some of the special challenges around 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, legal, and compliance
As with all technology, security and privacy are paramount, and gen AI introduces new considerations, including around IP. CIOs must work closely with their security, compliance and legal teams to identify and mitigate these risks, and ensure that generative AI is deployed in a safe and responsible manner. Further shape your plans around compliance and regulation, and think carefully about who owns the data you use.
Generative AI has the potential to be a transformational technology, tackling interesting problems, improving human performance and maximizing productivity. Dive in now, experiment with use cases, reap the benefits, and understand the risks, and you’ll be well positioned to leverage generative AI for your business.
Shaown Nandi is the director of technology, strategic industries at AWS.
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