Red flag #3: Lack of integration with existing tech stacks
A common reason pilots stall is that AI tools don’t mesh with current infrastructure. It’s one thing to demo a chatbot or AI solution in isolation. It’s entirely different to integrate it with existing ERP systems, CRMs or cloud data platforms. A lack of integration creates data and organizational silos, operational inefficiencies and technical hurdles that undermine performance and, thus, business impact.
Leaders should insist on seeing integration plans up front. Successful vendors understand that adoption isn’t just about the AI; it’s about embedding AI into business-critical workflows. Prioritize centralizing data from across the business, creating a single source of truth, before scaling AI applications. You can also consider leveraging AI-ready platforms with built-in connectors and capabilities that simplify connecting legacy and modern systems.
Red flag #4: Ignoring prerequisites for success
AI thrives on strong foundations: the aforementioned centralized data, consistent governance and cross-functional alignment. Many failed pilots happen because organizations try to leapfrog into sophisticated AI before checking the prerequisites off this list. Downplaying this preparatory work is simply setting businesses up for frustration and, ultimately, failure.