What does AI mean for bespoke database development?

Ever since Chat GPT burst on the scene last year, people have been thinking about how AI will change every facet of our lives. And, now that Open AI is letting everyone access their platform, innovation in this space will explode. As a bespoke database development company, we can answer one question at least, “What does AI mean for bespoke database development?”  Well, AI is really good at a few things – looking for patterns, learning and executing tasks. So, if we just look at these abilities, we can draw some conclusions on how AI will change bespoke database development.

Data management and analysis

AI will make data management faster by automating tasks like data cleansing, deduplication and normalisation. By leaning into its desire to find patterns, it can also use predictive analytics and trend identification to root out key insights from the data stored. This means that more of the business can have access to quality information from the whole of the database (not just segmented departments or anecdotal feedback) to base their decisions on.

Query optimisation

AI can optimise database queries dynamically based on usage patterns and workload. This helps in improving database performance and query responsiveness. As a result, you’ll see better user experiences from even the most basic databases. And that brings us to…

Natural interactions

AI-powered NLP lets users talk to bespoke databases with natural language queries and commands – just like you’d ask someone in person. This simplifies data retrieval and manipulation, making databases more accessible to even non-technical users from customer service agents to board members.

Data security

Remember how we said AI is good at finding patterns? Well, anomalous patterns in your traffic or network queries could indicate potential security breaches. AI is great at sniffing those out – even blocking them if you like. This pairs well with user authentication, access control and encryption to ensure data privacy and compliance with regulatory requirements.

Automated schema design

AI algorithms could help us make database schemas that are optimised for performance, scalability and data integrity. Machine learning may analyse usage patterns and data relationships to suggest improvements to the database schema automatically and then we could deploy those recommendations in half the time it would normally take.

Predictive maintenance

It also enables predictive maintenance for bespoke databases by analysing historical data and providing probabilistic estimates and alerts. The goal is to identify potential performance bottlenecks or hardware failures before they occur. We can then jump in and make the required updates. This minimises downtime and ensures continuous availability of your database.

Recommendation engines

For databases in e-commerce or content management systems, AI-powered recommendation engines can analyse user behaviour and preferences to provide personalised recommendations. This could be for products or content. Data suggests that personalisation can increase customer satisfaction, loyalty and conversion rates.

Challenges with AI in bespoke database development

But with all these benefits do come some challenges. There are ethical implications of AI-driven database development. Since AI can’t have experiences on its own, everything it can create is based on someone else’s work. There are also potential biases in AI algorithms and data processing around the data these models were trained on that reflect the bias in our world or overcompensate against it. Lastly, there are some regulatory compliance and legal considerations to weigh as this emerging technology hasn’t been legislated fully yet.


However, that’s no reason not to jump in and begin reaping the benefits of automation and efficiency that AI can offer. We’re ready to help you with your bespoke database development today. Talk to us on LinkedIn, Twitter or via the website here.