What is generative AI?
Generative AI (GenAI) is the name for AI systems that can produce new content - images, text, audio, even video. They learn patterns and structure from large datasets and then generate fresh content based on what they have learned.
The technology turns up all over the place now: on the web, in art and music, in text generation, and in fields as far afield as drug discovery. What it does, in short, is let a computer create content on its own, which blurs the line between what a person made and what a machine made.
For web-based businesses, that means a mix of creativity and automation - everything from turning raw data into readable content to helping out with customer service.
Generative AI for SMEs
Generative AI can be genuinely useful for small and medium-sized enterprises (SMEs) building web applications and operations software. A few of the places we see it earn its keep:
- Workflow automation: automating the repetitive bits of a business process. Drafting replies to common email enquiries, scheduling appointments, or suggesting which tasks to prioritise based on past data.
- Web content generation: a first draft of website content such as product descriptions, blog posts and landing-page copy. It will not write the finished article for you, but it takes the pain out of the blank page and keeps a steady flow of fresh content going.
- Chatbots and customer support: chatbots that answer frequently asked questions, help with product queries and handle the simpler customer service tasks, so a person only gets involved when one is actually needed.
- Data analysis and insights: working through large datasets - website analytics, customer feedback, sales figures - to find patterns and trends a human might miss, and giving SMEs a clearer picture of their customers and their operations to make decisions from.
- Custom software development: a hand with building bespoke software, from generating code snippets to sketching out user interfaces. It speeds the work up, but a developer still has to check what it produces.
Used well, in web applications, operations software and the rest, this can free people from the dull, repetitive work and let them get on with the things that actually need a human.
How we use GenAI
We are already using generative AI in a few ways ourselves - automating repetitive development tasks, helping keep code quality up, and generating content. There is a good range of tools available to developers and businesses now, and we make use of ChatGPT, Copilot and Amazon Q.
One of the AWS services worth knowing about here is Amazon Bedrock. It is a managed service that gives you access to a range of foundation models from different providers through a single API, so you can build generative AI features into an application without running the models yourself. You can also customise those models with your own data and connect them to your own data sources when you need answers grounded in your business.
Because it sits within AWS, Bedrock plays nicely with the rest of the platform - storage in Amazon S3 and RDS, and compute from the likes of AWS Lambda - so the AI side fits into the same architecture as everything else we build, and scales with it.
Guardrails and security
Guardrails are the practices and guidelines that keep a GenAI product within industry standards and a company's own security policies. Getting them right is how you keep the risks down and avoid leaving holes for someone to walk through.
Keeping business data private matters to us. With the right measures in place - encryption, access controls and sensible network configuration - sensitive data stays protected and is not handed over to a cloud vendor to do as it pleases with.
Amazon Bedrock helps here too: your data is not used to train the underlying models, and it comes with built-in security features and compliance certifications to lean on.
If you are weighing up where generative AI might help your business, or you just want a straight answer on what is realistic and what is hype, get in touch.
