David Irecki, chief technology officer for Asia Pacific and Japan at Boomi, said the lack of data readiness is holding back artificial intelligence (AI) success in the Philippines.
“Confidence is just the beginning. Many organizations still struggle to define and execute their AI strategy, often hindered by a lack of data readiness,” Irecki said in an email to Manila Standard.
Boomi is a global software as a service (SaaS) company with more than 23,000 global customers and a worldwide network of 800 partners. As CTO, David leads the region’s efforts in advocating the future of AI in business with intelligent integration and automation.
According to PwC’s 2025 Global CEO Survey, 75 percent of Philippine chief executives trust AI in their core processes, and 88 percent expect AI to be embedded in their business processes and workflows over the next three years.
Key challenges include data that are siloed, inconsistent or lack the integrity to fuel AI initiatives. Boomi’s “Data Readiness for AI” report supports this, with 45 percent of global leaders admitting they still struggle with data quality despite its critical importance for AI outcomes, said Irecki.
He said that in building a smarter and more connected strategy, organizations should focus on two important things. These include ensuring that high quality, trusted data is fed into AI models to drive relevant and accurate outcomes and enabling seamless data flow or “data liquidity” by connecting systems so the right data reaches the right place at the right time.
“Without these core foundations, AI initiatives risk falling short,” he said.
“Ultimately, success in AI depends heavily on the quality of the data. That’s where having the right partners, like Boomi, becomes invaluable. We help organizations build an AI-ready foundation so they can create, scale, and govern their AI initiatives on trusted data,” he said.
Irecki said one of the most critical missteps companies make when deploying AI is failing to address foundational issues like disconnected systems, poor data quality and weak governance. Often, these challenges are tackled reactively rather than proactively, he said.
Organizational data is often scattered across disparate platforms — legacy infrastructure, cloud services and siloed business units. This fragmented environment prevents teams from accessing the real-time, unified data needed to effectively power AI, often resulting in AI models being trained on unreliable and incomplete information, he said.
“As the saying goes, AI is only as smart as the data it learns from. No matter how advanced an AI model may be, its output will be flawed if the underlying data is inaccurate, outdated or inconsistent,” Irecki said.
He said another common pitfall is when companies overlook governance until AI deployments have grown significantly. However, it is crucial not to wait until you have thousands of AI agents before putting governance tools in place, he said.
Without first getting governance right, prioritizing data quality and enabling data liquidity before deploying AI, your initiatives risk becoming a liability instead of a competitive edge, said Irecki.
He said application programming interfaces (APIs) are essential for successful AI-driven transformation. They serve as the connective tissue between AI agents and enterprise systems, enabling seamless data flow and process automation.
According to IDC, about 70 percent of APAC organizations expect agentic AI to disrupt business models within the next 18 months. These autonomous AI tools can reason, decide and adapt without human intervention.
As companies adopt agentic AI to boost operational efficiency, enhance customer engagement and support better decision-making, they would need to connect their AI agents to a broad array of systems and data sources. This is where APIs become indispensable, said Irecki.
He said, however, not all APIs are designed for AI use cases. As teams create new APIs to support diverse AI needs, they often contribute to “API sprawl,” a growing number of APIs that are hard to manage and govern. The complexity increases the risk of cybersecurity vulnerabilities and compliance issues, he said.
“Beyond ensuring that the data powering AI agents is accurate and high quality, Boomi also helps organizations conquer API chaos that comes with AI-driven transformations. With a solid data foundation and the right API management strategy, businesses are well-equipped to unlock the full potential of their AI investments,” he said.