Why 'Get Your Hands Dirty' Governance Is The Future Of iPaaS

Enterprise AI adoption isn't happening as fast as leaders expected. For most, the greatest hurdle has been integrating new models with legacy systems, disparate platforms, and convoluted workflows. Now, the limitless possibilities of AI are starting to paralyze the very people it was designed to empower.

CIO News spoke to Dave Kreitter, CEO and Automation Consultant at Grail Automation, to learn more. With a career as a solutions and technical architect for tech giants like HubSpot, Broadcom, and Workato, he's had a front-row seat to significant technological shifts, including as an individual contributor to Marketo's IPO and its eventual $4.75B acquisition by Adobe. For Kreitter, the clear solution is a new mindset, one with unwavering commitment from the top.

• Swinging and missing: While acknowledging that the early, 'hit-and-miss' phase of AI exploration can be frustrating for leaders, Kreitter also framed it as a prerequisite for success. A period of trial and error is the only way to build institutional knowledge, he said. "When you start using AI, you'll find a lot of it yields mediocre results. But as you start to land more successful solutions, your home run rate increases. You have to go through the gray area to get to the black."

Effective adoption also requires absolute conviction from the C-suite, Kreitter said. "If leadership expresses hesitancy, the whole team feels it. You have to be all in." Fortunately, the technical fix is just as direct: move beyond classic APIs to Modern Connectivity Platforms (MCPs), an orchestration layer that sits on top of existing APIs.

• One tool to wield them all: The goal is custom, multi-system workflows, Kreitter explained. Rather than giving it access to hundreds of small tools, he recommends building one powerful tool for AI to wield instead. "The real value is going to be in exposing tools to these LLMs that actually execute complex workflows across multiple systems."