AI + Legacy Systems: Where Does Automation Deliver the Most Value?

Hi everyone! I'm Lungile, founder of RePlatform Insights, a South African technology company focused on legacy-system modernisation, custom business applications, systems integration, automation and data solutions.

One challenge I'm exploring is how organisations can introduce practical AI capabilities into established business systems without replacing infrastructure that already works.

Many businesses still rely on legacy applications, SQL databases, internal reporting tools and tightly connected operational workflows. These systems often contain years of valuable business logic and data.

Rather than pursuing a complete replacement, I'm interested in a more incremental approach:

• Understanding existing processes and identifying operational bottlenecks.
• Connecting AI-assisted tools to existing systems through controlled integrations.
• Automating repetitive administrative and reporting activities.
• Improving access to business information without compromising security, reliability or data governance.
• Measuring whether these improvements deliver meaningful operational value.

My question to the community:

For those who've integrated AI into complex legacy environments, where have you seen the strongest early results?

1. Workflow and process automation
2. AI-assisted reporting and information retrieval
3. Decision support and operational insights
4. Modernising interfaces and user experiences

I'd be especially interested in hearing about the integration challenges, lessons learned and approaches that worked in practice.

Looking forward to learning from other founders and builders tackling similar problems.