By Ann Hilzim, Partner within EisnerAmper’s Advisory Services Group By now, almost every organization has implemented artificial intelligence (AI) into their daily processes. Usage doesn’t automatically equate readiness or acceptance; therefore, it alone cannot be used to measure value. When eva luating AI investments, organizations cannot just compare vendors or calculate project costs—they need to confirm whether employees are prepared to change their current processes. The human factor is a crucial variable that determines the payoff, and it’s commonly overlooked when planning technology integration. The Human Factor Gap Most would assume that technology is the sole bottleneck to innovation. Roughly 70% of transformations fail to meet their objectives when implementing new technology, and AI is no exception. The common thread isn’t the tool itself; it’s organizational misalignment. AI investment decisions are often viewed only as technology purchases, rather than as operational change efforts. Prior to implementing new technologies, organizations should develop a structured change management plan to streamline adoption and strengthen understanding. Consider an organization that has invested in a new AI platform, and so far, it’s performing as it did during the demonstration. What happens when employees use that tool daily without adequate training built around their actual workflows? Adoption stalls. What Changes When the Organization Is Ready? Organizations that prioritize change management efforts in parallel with a technology rollout see that 88% of initiatives meet their intended outcomes. That gap between 70% failing and 88% succeeding doesn’t reflect software quality. It’s the difference between organizations that treated operational adoption as an afterthought and those that treated it as a priority. Readiness like this has to be built deliberately, tied to the organization’s specific operational goals. Common steps to include in a change management framework include: Alignment: Before any investment, decision-makers should align on the problem the AI investment would solve and articulate it in plain terms. Intentional Communication: When informing employees, craft clear messages on what this means for their specific role. Refrain from sending only general, organization-wide memorandums. Real-world Training: Conduct training built around actual responsibilities and tasks, not just generic tool tutorials. Feedback Loops: After the rollout, seek employee feedback to identify and close gaps before bigger risks occur. Readiness Looks Familiar to Anyone Who Has Prepared for a Storm AI adoption is a different kind of disruption; the organizations that come out ahead are the ones that still treat readiness as seriously as the technology itself. New Orleans has weathered storms that tested every plan an organization had on paper, and the outcomes rarely came down to who had the newest equipment. They came down to those who had evaluated responsibilities and prepared people beforehand. The parallel is not about the technology causing harm. It’s about preparation mattering more than people expect until the moment it’s tested. An organization that has practiced clear communication, defined ownership, and a plan for how people adapt is the same organization that will get real value from an AI investment. Getting Your Organization Ready with EisnerAmper The right question is not “which AI tool should we buy?” It’s “Is our organization ready to change how it works?” That question can be answered before a single dollar is spent on technology, and answering it honestly is what separates the 70% from the 88%. Organizational readiness can be assessed, built, and strengthened ahead of an AI investment. Is your organization transforming with AI? Watch our webinar. ...read more read less