In this segment of “Office Optional with Larry English,” Larry explains how iPaaS can transform disconnected data systems into a clean, integrated foundation for AI success, enabling organizations to harness the full potential of their digital transformation efforts.
“If we don’t address the chaos of disconnected systems now, the AI revolution could slip through our fingers before we even begin to harness its power,” writes Steve Lucas in his new book, Digital Impact: The Human Element of AI-Driven Transformation.
“Chaos” isn’t an overstatement. The average large organization runs hundreds of cloud applications, resulting in thousands of data sources spread across on-premise and cloud locations. Most of these apps and data sources are disconnected. Layering AI on top of this fragmented and siloed digital infrastructure won’t produce good results; it only adds more chaos. Simply put, poor data quality makes AI useless.
Organizations that don’t solve their data problems to prepare for AI are risking irrelevance, Lucas warns. “Businesses with disconnected systems will not survive the coming change,” he writes in Digital Impact. “You can have the shiniest, fanciest AI model at the heart of your business, but AI won’t understand your business if your systems aren’t integrated and processes aren’t automated.”
iPaaS Can Solve Messy Data Infrastructure
To properly harness AI’s power, companies need connected, quality, real-time, context-rich data. Yet digital transformation projects that completely overhaul a company’s apps and data systems are extremely time-consuming, expensive and disruptive.
Lucas shares that integration platform as a service (iPaaS) provides an elegant solution to data woes. In addition to being a national best-selling author, Lucas is also chairman and CEO of Boomi, which launched the cloud-based iPaaS category nearly two decades ago.
iPaaS is a cloud-based solution that connects and automates the flow of data across an organization’s software systems. “iPaaS is like a centralized hub of data activity that allows companies to connect systems and manage data with minimal custom development; it serves as a foundational platform for integrating AI with structured enterprise data,” says Andy Park, co-founder of Team Central, a no-code iPaaS tool. Team Central was developed at my company, Centric Consulting, and later spun out into its own organization.
Until recently, iPaaS has flown somewhat under the radar as a tool for helping companies get AI-ready, and the market demand is poised for growth, says both Lucas and Park.
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How iPaaS Cuts Through Data Chaos To Fuel AI Success
Even though many companies have complex, thorny data issues to tackle before they can fully leverage AI, iPaaS is well-suited for the challenge. It can solve the main roadblocks companies face in getting their data ready for AI. Lucas refers to iPaaS as a “Swiss Army knife” for data access and orchestration.
For one, iPaaS eliminates data silos. It connects all the data sources across an enterprise. This data connection is the foundation of AI success.
“Every app, every API, every piece of enterprise knowledge has to be accessible to AI,” Lucas says in an interview. He compares an organization’s data to the human nervous system, and iPaaS as the tool that connects all the neural pathways. Just like a human brain can’t function with faulty neural pathways, AI can’t work without clear and easy access to all the information across an organization.
Furthermore, iPaaS helps companies maintain clean, consistent data. It syncs across all the systems in an organization, so whenever an employee or customer updates data in one place, iPaaS automatically updates it everywhere else. For example, if a customer updates their email in an online store, iPaaS makes sure the information is also changed in your marketing email and shipping platforms. This way, employees across the entire organization always have the most up-to-date information.
iPaaS also understands the context for an organization’s data, which Lucas says is especially crucial for AI agents to function. “For example, if I asked an agent for my sales forecast, the agent must know where the information lives and understand how you think about forecasting. That’s contextual metadata. iPaaS has the location and the context, not just the data itself,” he says.
Finally, because iPaaS automatically maintains clean, connected, context-rich data, analytics are not only accurate but easy to access, helping companies achieve informed, agile decision making — an essential capability as the pace of new technology accelerates.
iPaaS Is Critical To Digital Transformation
Perhaps the biggest advantage of iPaaS is that it allows companies to begin unlocking AI benefits without embarking on a full-scale digital transformation project. Or, iPaaS can serve as a first step toward digital transformation, allowing a company to begin modernizing and achieve some quick wins without going through a giant overhaul or a rip-and-replace transformation.
Many organizations have put off cleaning up their data and modernizing their tech stack for a long time, because leaders know it’s a complicated, expensive, time-consuming and risky process, especially for organizations carrying a heavy tech debt.
“Companies know they have all this technology that’s been cobbled together with duct tape and chicken wire over the last few decades,” Park says. “Cleaning up data and implementing automation technology to programmatically govern data quality has been long overdue, but it’s an intimidating prospect. By leveraging iPaaS, businesses can start preparing their data for AI without the need for a complete modernization from the ground up.”
iPaaS offers a practical alternative to full-scale digital transformation because the technology is low- or no-code and relatively easy to implement. iPaaS is a cost-effective and low-risk solution because it requires little to no custom development. Its lightweight nature, especially when compared to other platforms, makes it a practical choice for businesses looking to streamline integration without heavy IT investment.
“A more traditional way of integrating might take 10,000 lines of code; there are zero lines of code in our solution,” Park says. “So the amount of time savings and the amount of complexity in the solution is dramatically reduced. You don’t have to create a new framework or structure to manage security, accessibility and logic — iPaaS provides a pre-built, scalable infrastructure that reduces this complexity so you can focus more on proper data mapping, business rules and data transformation.”
Businesses need connected, clean and contextual data to unlock AI’s true power. iPaas makes that possible. It cuts through complexity to lay the foundation for AI success.
This blog was originally published on Forbes.com.
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