Despite proven cost efficiencies from deploying fine-tuned AI models, companies report the primary barrier to adoption is human, not technical. The core challenge is overcoming employee inertia and successfully integrating new tools into existing workflows—a classic change management problem.

While technical challenges exist, an audience poll reveals that for 65% of organizations, "people problems"—such as fear, resistance to change, and lack of buy-in—are the primary obstacles hindering successful AI implementation.

While AI's technical capabilities advance exponentially, widespread organizational adoption is slowed by human factors like resistance to change, lack of urgency, and abstract understanding. This creates a significant gap between potential and reality.

Implementing AI is becoming less of a technical challenge and more of a human one. The key difficulties are in managing change, helping people adapt to new workflows, and overcoming resistance, making skills like design thinking and lean startup crucial for success.

Organizations often prematurely focus on solutions like technology procurement (the 'what' and 'how'). This skips the crucial initial step of understanding the core business drivers ('why') and the needs of the people involved ('who'). This oversight is a primary and costly cause of project failure.

MongoDB's CEO argues that successful pivots during tech transitions like cloud or AI are fundamentally change management challenges, not technical ones. The biggest risk for established companies is complacency. Leadership must force the organization to lean into new platform shifts, even when their maturity is uncertain, to avoid being disrupted like Nokia or BlackBerry.

Companies fail to generate AI ROI not because the technology is inadequate, but because they neglect the human element. Resistance, fear, and lack of buy-in must be addressed through empathetic change management and education.

Despite mature AI technology and strong executive desire for adoption, the primary bottleneck for enterprises is internal change management. The difficulty lies in getting organizations to fundamentally alter their established business processes and workflows, creating a disconnect between stated goals and actual implementation.

Despite AI's potential, large enterprises struggle to see bottom-line impact. The primary hurdle isn't the tech, but the human challenge of "change management"—overcoming bureaucracy and altering complex, undocumented workflows within large organizations.