For the past few months, ChatGPT has been wowing us with its ability to, say, write Shakespearian sonnets about our mother-in-law’s collection of garden gnomes (Amidst the blooms and blossoms they do dwell / A whimsical and merry company / Their presence lending magic to the spell / That makes this garden such a sight to see …). But ChatGPT and other generative AI platforms aren’t simply a parlor trick. They take on a more transformative role for organizations when applied to the products and platforms we use every day.
Over the years, AI has helped make incremental improvements in integration productivity. Say, identifying (but not resolving) data quality issues or auto-matching fields between applications that are being integrated. It has lent a helping hand to a capable integration specialist to make their jobs more efficient and more accurate.
But this new wave of AI – generative AI with an uncanny ability to process natural language inputs and responses – will have an exponential impact on integration platforms and how we even think about integration. In fact, we likely don’t understand how monumental those shifts will be.
But, as of today, here’s what we expect to happen.
1. Want an integration? Just ask for it.
Decades ago, if you wanted to get two applications or systems to work together, there was only one way to do it: start coding. IT teams would write long, complicated, brittle lines of code. It was a job that could only be done by developers, and with each change came even more code. The result was an inefficient, complicated mess of spaghetti code connecting applications.
Integration solutions came along – first the enterprise service bus (ESB) and now the iPaaS – which introduced ways to make integrations easier to configure and more resilient. The modern iPaaS offers a visual drag-and-drop visual interface that can be used by developers, but also by citizen integrators. This has been a big improvement and freed up developers to focus on more advanced integration scenarios.
But with generative AI, the interface between you and an iPaaS may be as easy as a simple request. If you need information from platform A to sync to platform B, you won’t need to know the intricacies of how it happens, you just need to know what you want. For example, you could say “Update customer lead score in Marketo into Salesforce”. And then the AI will figure it out on your behalf. And then test it to see if it is working properly. And if not, it will figure out how to fix the problem.
2. Integration connectors that practically build themselves
Integration connectors are the building blocks of the iPaaS. Right now, there are two ways that connectors are built. They can be built and managed by the iPaaS vendor. The advantage is that they are built the “right” way and managed on an ongoing basis. They will work reliably, as expected, every time. And if they don’t, you can reach out to get it fixed.
Or they are built by the community of users. This quickly expands the library of connectors so that users aren’t all out there independently trying to build the same connector – they can benefit from the work of others. The downside of community-built connectors is that there isn’t exacting quality control, and they are not always actively maintained.
But what if connectors could be built by generative AI instead? It means a limitless number of connectors could be built – and maintained – by simply asking your iPaaS. The “library” could be as infinitely vast as the number of applications that exist to connect.
3. Better, smarter, self-healing data mapping
Everything is changing, all the time. Data formats and standards are no exception. What that means is your data may be properly mapped in your integrations today, but it may not be tomorrow. When information is no longer properly mapped, it could poison the quality of your insights or even break customer experiences that you have built.
AI will constantly monitor for data mapping errors, understand the problem and proactively plug the leaks. It means no data downtime, and insights you can trust – all without human intervention.
So what now?
I am excited for the future of AI for Integration. You will soon be able to get not 2X, but 10X or 100X productivity improvements and automation. The next generation of iPaaS, powered by generative AI, holds tremendous potential to leapfrog today’s capabilities. At Software AG, we are rethinking the limits of what’s possible – and building it.
And while ChatGPT’s sonnets about garden gnomes will continue to both amuse and amaze, generative AI will soon be busy changing integration as we know it.