How to use GenAI to create value for your business
Generative AI tools like ChatGPT are exciting, but as a leader, how do you use it to give your business an advantage? Here are ten ways you can do that.
Oct 11, 2023 • 5 Minute Read
Generative AI has captured the imagination of many over the past few months. However, aside from using ChatGPT to write our wedding speeches and do our kid’s homework, how can we use generative AI technology to add real business value? Here are ten ways you can use it to get ahead of your competitors.
1. Build your own chatbots
Conversational chatbots and virtual assistants increase customer engagement in an interactive and personalized way. You can tailor them to reflect your brand voice, and deliver them in a consistent way across your site so your customers always have access to timely support.
How to get started
Amazon Lex makes it easy to build high-quality conversational interfaces powered by generative AI.
2. Help customers find what they’re after
Since generative AI has the ability to understand text, it’s an excellent choice for summarizing large amounts of complex, unstructured information. Generative AI technologies are likely to become embedded into everyday applications, enabling the personalization of content and presenting relevant content to users when they need it.
For example, consider a search engine that recognizes when you need more than a textual explanation. It serves you a relevant video clip, playing at exactly the right timestamp, and gets right to the heart of what you’re looking for.
How to get started
SageMaker Jumpstart is a fully managed machine learning service that makes it easy to deploy models without worrying about the heavy lifting of creating and training them. It provides a selection of models that are pre-trained using terabytes of text and image data and ready to deploy. It includes models from Hugging Face, AI21 Labs, Stability AI, and Amazon.
3. Automate your repetitive business processes
Generative AI is ideal for automating repetitive tasks that don’t require high levels of creativity, such as reviewing and summarizing contracts, generating project collateral, and code documentation. FAQ engines that handle common customer support and HR inquiries are expected to become commonplace. Marketing teams that need to develop campaigns in a similar style to previously successful campaigns, or automate customer outreach, will also find that they can easily automate these repetitive tasks with generative AI.
How to get started
Content marketers can use services like Bedrock to build a social media campaign for a new product or service. Marketers provide relevant data and prompts, and Bedrock generates copy and images for targeted social media posts.
Read our article, What is Amazon Bedrock? The custom GenAI building service, to learn more about Amazon Bedrock.
4. Use GenAI for predictive analytics and decision making
The predictive analysis capabilities of AI can improve decision-making processes, ensure business decisions are well informed, and analyze each option in a consistent way. AI technology excels at extracting meaning from unstructured data. And with generative AI, we can quickly generate summaries of analyzed data to help drive quality decision making.
This has huge implications for financial institutions making trading strategy decisions as well as pharmaceutical companies and manufacturers who use predictive data to help with developing and designing new products.
How to get started
Use SageMaker Canvas to provide a point-and-click interface that enables analysts to generate ML predictions without requiring any machine learning experience.
5. Incorporate generative AI into your cybersecurity
Generative AI can be used in risk modeling and assessing and interpreting the risk of cybersecurity incidents and findings.
How to get started
Use generative adversarial networks (GANs) to create synthetic data, enabling security experts to anticipate what might happen during a cyber attack.
Read our article, Pure magic: How to use GenAI in threat detection & response, to learn more about GANs.
6. Replace customer-sensitive data with synthetic data
You need to train a machine learning model before it can perform a task. For many organizations, it doesn’t make sense to train using real-world customer data. This is especially true for highly sensitive industries, such as financial services, healthcare, and defense, or systems that handle personally identifiable information (PII).
For these applications, generative AI can be used to generate vast amounts of training data for sensitive use cases, removing the risk associated with training the system using real-world data.
How to get started
SageMaker Ground Truth supports synthetic data generation to create high-quality labeled datasets you can use to customize generative AI models.
7. Generate image, video, and text
Most of us are familiar with image, video, and text generation—the primary capabilities of generative AI. Use cases include creating original content, images, and summarizing text.
How to get started
Leading pre-trained AI models are available through SageMaker and Bedrock to help you get started quickly. Use Bedrock Chat Playground to experiment with various models using a chat interface.
8. Improve product and app development
Developers can also benefit from using generative AI powered tools to assist them in writing effective and secure code.
How to get started
CodeWhisperer is an AI coding companion from AWS that can provide suggestions in the form of code snippets or even complete functions based on comments and prompts provided by a developer. You can also use it to run a security scan on the completed code to identify any security vulnerabilities, such as the use of out-of-date libraries.
9. Detect fraud and manage risk
Another great use case for AI is in fraud detection. You can use it to detect fraudulent online payment, identify compromised accounts, and catch trial and loyalty program abuse.
How to get started
Amazon Fraud Detector is a service that utilizes AI to identify potentially fraudulent activities. It’s trained using your own historical data and has the added benefit of AWS’ decades of experience detecting online fraud.
10. Research
Generative AI is set to revolutionize research activities that rely on the interpretation of text-based data.
For example, the pharmaceutical industry is expected to benefit substantially from the ability to quickly summarize and make sense of complex data during product design stages and when conducting clinical trials. The capacity to synthesize data can significantly accelerate the development and design of new drugs and protocols.
AWS HealthScribe, announced recently, is an exciting new service designed to help generate clinical notes based on patient-clinician conversations.
Getting your organization started with AI and ML
To start using these technologies, you need your staff to be skilled in using them. Pluralsight offers a wide range of beginner, intermediate, and advanced AI and ML courses to empower you and your teams to make the most of this emerging technology. You can sign up for a 10-day free trial with no commitments. We also offer professional and enterprise plans, as well as analytics tools for helping ensure your company's upskilling efforts are successful, driving value well beyond just learning about ChatGPT. Contact us today to learn more.
For your practitioners, I would highly recommend they check out the following Pluralsight and A Cloud Guru courses to get started:
