In the rush to implement AI, it's easy to assume technical capabilities will determine success. Our research confirms what change management experts understand: human and organisational factors overwhelmingly determine whether AI delivers value at scale or remains isolated experiments.
Ankur Saxena from Evalueserve cuts to the heart: "The most challenging aspect of AI implementation has been the cultural shift required." This statement, echoed across interviews, reveals a truth many learn the hard way: AI transformation is about people, not technology.
The challenge manifests at multiple levels. Paolo Roberti from BIP elaborates: "The impact varies across different service areas, and this variation affects rates and competitiveness. For example, in tax legal services and M&A, the implementation of AI requires careful consideration of both the technological capabilities and the human expertise required. The key is finding the right balance between automation and maintaining the high-touch, personalised service our clients expect."
Stephanie Hamon provides insight into timeline challenges: "The evolution will happen, but likely over a longer timeframe, with a gradual shift towards more strategic work and less administrative tasks." This trajectory from enthusiasm through frustration to mastery is a human journey technology cannot accelerate.
Human factor challenges emerge at every level:
Leadership alignment. Executives must actively champion AI. This requires leaders who understand both potential and limitations, who articulate vision while acknowledging challenges.
Middle management resistance. Greatest resistance often comes from middle managers fearing AI will eliminate their roles. These fears create powerful barriers.
Frontline adoption. Employees working alongside AI daily need more than training. They need to understand how AI enhances rather than threatens their roles.
Cultural transformation. Most challenging is transforming culture from valuing human effort to valuing outcomes regardless of delivery method.
Human factor challenges emerge at every level:
Leadership alignment. Executives must actively champion AI. This requires leaders who understand both potential and limitations, who articulate vision while acknowledging challenges.
Middle management resistance. Greatest resistance often comes from middle managers fearing AI will eliminate their roles. These fears create powerful barriers.
Frontline adoption. Employees working alongside AI daily need more than training. They need to understand how AI enhances rather than threatens their roles.
Cultural transformation. Most challenging is transforming culture from valuing human effort to valuing outcomes regardless of delivery method.
Jessica Samadi from a global financial services company provides insight: "The primary challenges we face revolve around technology integration and staff training. Ensuring seamless integration and consistent service delivery requires strong IT systems and support, which can be resource-intensive. More importantly, the effectiveness of any technology implementation depends heavily on proper staff training."
She emphasises scale: "With a global presence and varying levels of expertise across offices, providing adequate training to ensure proper utilisation of new systems can be particularly challenging. To address this, implementing regular monthly meetings with teams to identify pain points and training needs are useful."
Successful organisations share several approaches:
Transparent communication.
Leaders who succeed are honest about opportunities and challenges. They help employees see their place in the AI-first future.
Inclusive transformation.
Rather than imposing AI from above, successful organisations involve employees in identifying opportunities and designing solutions.
Continuous learning culture.
AI demands ongoing skill development. Organisations treating learning as a journey see better outcomes.
Celebrating collaboration.
Instead of positioning AI as replacing humans, successful organisations celebrate where human expertise combined with AI delivers superior results.
Managing fear with facts.
Addressing concerns directly with data about AI augmenting rather than replacing roles reduces anxiety.
Financial services provides instructive examples. Bram Pauwels notes: "I think the level of regulation is important. I work in banking and there are certain things that we simply cannot do yet from an AI point of view, or there are a lot of reviews to happen." This regulatory overlay adds another dimension: bringing regulators and compliance teams along.
Timeline pressure intensifies the challenge. With 12-month windows, leaders have limited time for gradual change. This forces more intentional approaches.
Research reveals the importance of proactive planning. Successful organisations describe their approach: "We have in the coming three months what's lined up. We know what are the resources that we need, what are the implementations that need to happen, what are the conversations that need to happen?" This structured approach, planning technical implementations and human conversations, characterises successful transformations.
Evidence is overwhelming: organisations prioritising change management see dramatically better outcomes than those focusing solely on technology. As one leader put it: "The AI is the easy part. Getting people to embrace new ways of working , that's where the real challenge lies."
This human-centric view might seem paradoxical in an AI era. Yet it reflects deeper truth: AI doesn't eliminate the human element but amplifies it. Success comes from creating environments where human creativity, judgment, and expertise combine with AI's speed and consistency to deliver unprecedented value.
The message: invest as much in change management as technology. Build programmes acknowledging human concerns, celebrating contributions, and creating clear workforce evolution paths. Because successful AI transformation isn't about artificial intelligence but the human intelligence that guides and amplifies it.
While human factors dominate challenges, organisations also face a critical operational paradox: the gap between pilot success and enterprise-wide implementation.
About Enate
Enate is the leading SaaS solution for business services. Enate orchestrates work from start to finish, giving clients the visibility and control needed to deliver better services. From email management and data analysis to intelligent document processing, Enate also offers a host of touch-button AI features designed to slash the time spent on manual work. Trusted by global service teams, Enate ensures smooth, consistent operations that help clients perform at their best.