7 Benefits of AI & Low-Code for Legacy System Integration
AI and low-code platforms are revolutionizing legacy system updates. Here's how:
- Faster Development: Cut dev time by 40-60%
- Better System Understanding: AI maps complex code quickly
- Accurate Integration: AI ensures smoother data handling
- Improved Operations: Automate tasks, boost efficiency
- Lower Costs: Reduce expenses for updates and maintenance
- Easy Scalability: Adapt systems without starting over
- Enhanced Security: AI spots vulnerabilities early
Quick Comparison:
| Benefit | Without AI/Low-Code | With AI/Low-Code |
|---|---|---|
| Dev Time | Months | Weeks |
| Code Analysis | Manual, slow | Automated, fast |
| Integration | Error-prone | Highly accurate |
| Operational Efficiency | Limited | Significantly improved |
| Update Costs | High | Reduced by 40%+ |
| Scalability | Difficult | Easy, on-demand |
| Security | Reactive | Proactive |
AI and low-code aren't perfect - data quality and tech mismatches can be issues. But for most companies updating old systems, they're game-changers. Get on board now to future-proof your tech.
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How AI and Low-Code Work Together for Legacy Systems
AI and low-code platforms join forces to update legacy systems. Here's the breakdown:
1. AI digs into old code
AI examines legacy systems, finding weak spots and mapping connections. This gives developers a clear view of what they're up against.
LegacyLift, for instance, uses AI to analyze source code, test cases, and regulations. It uncovers original design goals, business logic, and system dependencies.
2. Low-code speeds things up
Low-code platforms like Mendix help developers build new apps quickly. They use pre-made components and visual tools instead of writing every line of code.
"Low-code development helps us create a roadmap to transform legacy products into powerful, next-gen solutions." - Rishabh, Legacy Application Modernization Services
3. AI suggests tweaks
As work progresses, AI can spot ways to improve the new system. It might recommend faster code or flag security issues.
4. Low-code bridges old and new
Low-code platforms often include tools to connect with older systems. This lets companies keep using parts of their old setup while adding new features.
5. AI boosts testing
AI can create and run tests to ensure the new system works correctly. This catches bugs faster and smooths out the process.
6. Low-code simplifies updates
Once the new system is live, low-code platforms make it easy to add features or make changes as the business grows.
1. Faster Development and Rollout
AI and low-code platforms are game-changers for updating legacy systems. Here's the scoop:
Low-code solutions cut development time by 40-60%. What used to take months now takes weeks.
AI handles the boring stuff like data entry and basic coding. This lets developers tackle the tricky parts.
AI tools quickly analyze old systems, giving developers a jumpstart. They map connections and find weak spots.
Low-code platforms enable rapid prototyping. Build and test new features fast, get feedback, and improve.
Real talk:
Microsoft Power Platform users save up to 85% of development time in the first three years. Employees using it with existing systems save 25% of their time.
Want to get started?
- Automate something simple with Power Automate.
- Build a basic app for a common task using Power Apps.
- Try AI accelerators like OutSystems' AI suite to generate new solutions based on your legacy systems.
2. Better Understanding of Old Systems
AI tools are changing how we make sense of complex legacy systems.
Decoding the Mystery: Old systems often lack clear docs. AI fills this gap.
Automated Analysis: AI scans and maps legacy code connections in days, not weeks or months.
Uncovering Hidden Logic: AI digs deep to find business rules and logic in old code.
IBM's Mono2Micro tool is a prime example. It uses AI to analyze source and object code, showing how different parts interact. Nick Fuller from IBM Research says:
"Mono2Micro uses AI clustering to group similar code, clearly showing how code groups interact."
This insight is key for safe system updates.
Real-World Impact:
- American Express: AI in legacy transaction processing improves fraud detection.
- Walmart: AI algorithms with old supply chain systems boost inventory and logistics.
Bridging the Knowledge Gap: AI preserves system knowledge as older devs retire. This is crucial for COBOL systems running critical ops.
Steve Brothers from Phase Change Software notes:
"The real problem is understanding what apps do. To change code well, you need to know what it does."
Their COBOL Colleague tool uses AI to turn COBOL into a cause-effect model, helping new devs grasp and maintain it.
3. More Accurate Integration
AI supercharges the connection between old and new systems. It's like having a super-smart assistant that never sleeps, making sure everything fits together perfectly.
Smarter Data Handling
AI gobbles up data like Pac-Man. It's FAST and ACCURATE. This is huge when you're trying to mix old systems with new ones.
American Express put AI to work in their old transaction system. Now, AI watches every swipe, tap, and click in real-time. It looks at where you shop, what you buy, and more. The result? Way better at catching fraud and spotting fishy business.
Finding Hidden Treasures in Data
AI is like a data detective. It spots things humans might miss, leading to smarter choices during integration.
Walmart's using this superpower:
- AI digs through their old supply chain data
- It predicts what products will sell
- It figures out how much inventory each store needs
- Result? Better stocked shelves and less wasted money
Manufacturing Magic
Factories are loving AI-powered legacy systems. Check out BMW:
- They added AI brains to their old factory setup
- Now, smart robots and algorithms predict assembly line hiccups
- This means smoother work and better quality checks
- The payoff? They make more cars, and they're still top-notch quality
Making Old and New Play Nice
AI is the ultimate translator. It helps crusty old systems chat with shiny new apps.
Siemens Healthineers shows how it's done:
"Our AI tools have turbocharged everyday workflow. We're getting way better at analyzing images and our diagnostic tests are WAY more accurate."
Their AI makes medical imaging systems work better, leading to smoother operations and better diagnoses.
Moving and Cleaning Data
Switching from old to new systems? Your data probably needs a good scrub. AI handles this like a pro:
- It's faster than humans
- It makes fewer mistakes
- Your new system gets cleaner, better data
AI doesn't just connect systems – it makes the whole process smoother, faster, and more accurate.
4. Improved Day-to-Day Operations
AI and low-code platforms are transforming business operations. Here's how they're making daily work more efficient:
Work Gets Done Faster
AI handles repetitive tasks, freeing up humans for strategic thinking:
- JP Morgan's COIN tool reads legal documents in seconds
- American Express uses AI to identify at-risk customers
IT Support Gets Smarter
Low-code tools let IT teams create intelligent solutions:
- Chatbots handle basic queries
- AI diagnoses common tech issues
This lets IT pros tackle the tough stuff.
Problems Get Solved Quicker
AI spots issues fast and offers solutions. This means:
- Less downtime
- Fewer mistakes
- Happier customers
Teams Work Better Together
Low-code platforms boost collaboration:
- Business leaders make small tweaks themselves
- Developers focus on complex tasks
- Projects wrap up faster – some in just 1.5 weeks
Costs Go Down
Updating systems with AI and low-code makes financial sense:
- Cuts development costs by 40%+
- Requires smaller teams
- Frees up budget for other priorities
Real Companies, Real Results
"AI tools have supercharged our workflow. We're analyzing images better and our diagnostic tests are much more accurate." - Siemens Healthineers
A major bank added AI chatbots for customer service. The outcome? Satisfied clients and reduced expenses.
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5. Lower Costs for System Updates
AI and low-code platforms are slashing the cost of updating legacy systems. Here's how:
Faster Development
Low-code tools speed things up:
- A Vermont power company built an app in a week using Volt MX
- OutSystems' AI creates new solutions from old systems
This means less time and money spent on long projects.
Smarter Resource Use
- Existing staff can learn low-code in about two weeks
- No need for expensive legacy system specialists
A major health insurer used Volt MX to reallocate IT resources and save big.
Gradual Updates
Companies can update bit by bit:
- Keep using parts of old systems that work
- Add new features without starting from scratch
This protects past investments and cuts upfront costs.
Less Maintenance, More Innovation
Modernizing frees up cash:
- Cut licensing fees for old software
- Spend less time fixing old code, more on new ideas
| Cost Area | Before | After |
|---|---|---|
| Maintenance | High | Low |
| Development | Slow, expensive | Fast, cost-effective |
| Staff Needs | Specialists | Existing team |
| Innovation Budget | Limited | Increased |
Real-World Results
"We've used low-code platforms to leverage prior IT investments and fill gaps without complete system replacements." - Aaron Jackson, Accenture Federal
One client found an outdated process costing $2-3 million yearly. Switching to electronic signing and modern document management could save them millions.
With AI and low-code, updating legacy systems is cheaper and easier. Companies can modernize step-by-step, use resources wisely, and focus on growth.
6. Easier to Grow and Change
AI and low-code platforms are game-changers for updating legacy systems. They let businesses adapt fast without starting over.
Flexible Updates
Low-code solutions mean companies can change things piece by piece:
- Add features without messing up the whole system
- Test and launch updates quicker
- React to market shifts faster
Take Walmart. They boosted their online platform with a flexible system. Result? Faster responses and more online sales.
Scalability
Systems built with AI and low-code handle growth better:
- Manage more data and users
- Add functions as needed
- Play nice with new tech like cloud services
| Old Way | New Way |
|---|---|
| Fixed capacity | Grows on demand |
| Slow changes | Quick updates |
| Limited tech options | Works with new tools |
Real-World Impact
Klarna, a payment company, revamped their decade-old system using Erlang Solutions. This let them:
- Use new programming languages (Scala, Haskell)
- Boost system uptime
- Handle more data (crucial for finance)
Always Improving
This new approach keeps systems fresh:
- Fix issues faster
- Add features regularly
- Stay ahead of security threats
OutSystems offers AI tools to modernize old systems quickly. This frees up developers to improve things, not just keep them running.
7. Better Security and Rule-Following
AI and low-code platforms are game-changers for security and compliance in legacy system updates. Here's the scoop:
Smarter, Safer Code
AI's got developers' backs, even if they're not security pros. It spots issues and suggests fixes on the fly.
Get this: 33% of developers think AI will beef up code security. That's huge, considering devs typically spend just 10% of their time patching old apps.
Nipping Problems in the Bud
AI tools catch security flaws early. Check out the difference:
| Without AI | With AI |
|---|---|
| Late problem detection | Early issue catching |
| Alert overload | Fewer alerts |
| Slow fixes | Quick problem-solving |
Compliance Made Easy
AI's got your back on complex rules:
- Crunches data
- Keeps an eye on systems
- Whips up reports
Perfect for stuff like AML checks in banking.
Real Impact
AI security is a money-saver:
- $3.60 million: Average data breach cost with AI
- $5.36 million: Without AI
- 108 days: How much faster AI spots and contains breaches
Threat Detection on Steroids
AI's like a super-smart security guard. It watches:
- System logs
- Network activity
- User behaviors
James Segil from Motorola Solutions puts it this way:
"AI enables proactive surveillance by analyzing video and flagging unusual activities, allowing operators to review the footage and take immediate action when a possible breach is detected."
Security, Simplified
AI handles the boring stuff, freeing up human experts for the big-picture stuff. Plus, it's a whiz at access control, learning who should be where and when.
Problems and Things to Think About
AI and low-code platforms can boost legacy system integration, but they're not without challenges. Here's what you need to know:
Tech Mismatch
Old systems often don't play nice with new AI tech. This can cause compatibility issues, data silos, and scaling problems. The fix? Careful planning and maybe updating or replacing parts of your old systems.
Data Hurdles
AI needs good data to work its magic. But legacy systems often have outdated info, scattered data, and quality issues. In fact, Gartner found that data problems messed up 85% of AI projects in 2022.
To tackle this:
- Clean up your data
- Connect different data sources
- Keep your data fresh and accurate
Money Matters
Updating old systems with AI isn't cheap. You'll need to budget for new tech, training, and possible downtime. To keep costs in check, start small, use cloud services, and look for AI tools that work with your current setup.
People Problems
Your team might worry about AI taking their jobs or struggle to learn new ways of working. Help them adapt by:
- Explaining how AI will make their jobs easier
- Offering training and support
- Starting small and building up slowly
Security Concerns
Adding AI to old systems can create new security risks. You'll need to update your security measures, control AI access to sensitive data, and watch out for new cyber threats.
Keeping It Legal
AI must follow laws and rules, which can be tricky with old systems. Make sure your AI use follows data protection laws, track how AI makes decisions, and be ready to explain those choices if asked.
Wrap-up
AI and low-code platforms are shaking up legacy system modernization. Here's the lowdown:
1. Speed and savings
AI-powered low-code tools slash modernization timelines. OutSystems' AI accelerators, for example, auto-generate system components. This means faster updates and fatter wallets.
2. Legacy code demystified
AI helps devs crack complex code quicker. It maps system structures and flags trouble spots. Less head-scratching, more problem-solving.
3. Smooth connections
Low-code platforms often pack pre-built connectors. Old meets new without the fuss. Think AI and automation playing nice with legacy systems.
4. Everyone's invited
Low-code opens the door for non-devs. IT teams get a breather, and fresh ideas flow in from across the company.
5. Dev happiness boost
Check out these stats on AI coding assistants:
| Metric | Boost |
|---|---|
| Speed | 80% up |
| Job satisfaction | 65% up |
| Success rate | 60% up |
6. Future-ready
Easy updates mean nimble businesses. That's gold when 85% of leaders see more curveballs coming.
7. Real-world impact
This isn't just tech for tech's sake. Healthcare providers craft better care plans. Retailers nail personalized marketing.
What's next?
The AI and low-code combo is just warming up. Expect:
- More AI baked into low-code platforms
- Non-techies wielding AI like pros
- AI tackling bigger, hairier legacy system overhauls
Sure, there are hurdles (data quality, security). But for companies modernizing old systems, AI and low-code are looking pretty sweet. Jump on board now, and you'll be ready for whatever tech throws your way next.
FAQs
How can GenAI help modernize legacy systems?
GenAI is a game-changer for updating old systems. Here's how:
It scans and understands complex legacy code FAST. This saves developers tons of time and cuts down on mistakes.
GenAI can whip up clear docs for systems that lack them. This helps teams get a grip on what they're dealing with.
Need to improve old code? GenAI's got ideas. It can suggest tweaks to make the code more efficient and easier to handle.
It's also a security buff. GenAI can spot potential weak spots in old systems before they turn into real headaches.
And when it's time to move to new tech? GenAI can help translate old functions into modern frameworks, making the switch smoother.
Take American Express, for example. They've put AI to work on their old transaction processing system. Now, AI models check purchases in real-time, looking at things like spending habits and location to catch fraud quicker.
"GenAI enhances the accuracy of the modernization process by automating tasks such as code analysis and documentation, which reduces human errors and ensures a more precise translation of legacy functionalities to the new system." - Jun 21, 2024
In short: GenAI is like a Swiss Army knife for modernizing legacy systems. It's making the process faster, smoother, and more accurate.
