Shereen Faisal, Project Manager and AI Data Scientist at Nasser Centre for Science and Technology, tells Tahawultech.com why transparency, governance, and focused pilot projects are essential to overcoming hesitation and scaling AI successfully.
Artificial intelligence has moved firmly onto boardroom agendas across the region, yet hesitation continues to slow adoption among organisations and end users alike. Concerns around trust, transparency, data protection, and the impact on people and established workflows remain the most common barriers, often outweighing questions about the technology itself.
Shereen Faisal, Project Manager and AI Data Scientist at Nasser Centre for Science and Technology, believes confidence in AI is earned through honest communication, strong governance, and practical results delivered in a controlled and transparent way.
Speaking to Tahawultech.com, Faisal explains why focused pilot projects create internal advocates, how leaders can set realistic expectations, and why placing people at the centre of every initiative is the surest path to scaling AI successfully and sustainably.
Interview Excerpts
What are the biggest reasons organisations and end users remain hesitant to embrace AI projects today?
Hesitation is rarely about the technology itself. It stems from uncertainty about how AI makes decisions, how reliable it is, how data is used, and its impact on people and established ways of working. For organisations, the biggest concern is trust. Leaders need assurance that AI will produce reliable outcomes, operate securely, and comply with regulations. For end users, the concerns are more personal, from data protection to whether meaningful human support will remain. Confidence grows when AI delivers practical, measurable benefits in a controlled and transparent way.
“Trust is built through experience, good governance, and consistent results.”
How can organisations build trust in AI by being more transparent about its capabilities, limitations, and decision-making processes?
Trust begins with honest communication. A common mistake is presenting AI as capable of solving every problem, when every system has strengths, limitations, and conditions under which it performs well or less effectively. Organisations should clearly explain what an AI system is designed to do, how it supports decision-making, and where human judgement remains essential. Transparency should also extend to how systems are developed and governed, covering data quality, security, fairness, privacy, and ongoing monitoring. Building trust is an ongoing process, not a single communication exercise, and when transparency becomes part of the culture, confidence grows naturally.
Why are quick wins and focused pilot projects so important in overcoming resistance to AI adoption?
Focused pilots allow organisations to learn before they scale, evaluating not only whether the technology works but how it fits within existing workflows and what organisational changes may be required. They create space to experiment without the pressure of enterprise-wide deployment, refining processes and success metrics while the scope remains manageable. Successful pilots also create internal advocates. When employees and business leaders experience tangible improvements firsthand, they become champions for broader adoption. Each successful initiative strengthens internal knowledge and builds a culture that is more confident, informed, and prepared to embrace AI-driven transformation.
How can business leaders set realistic expectations that encourage long-term confidence and sustained adoption of AI?
Leaders must position AI as a journey of continuous improvement rather than a one-time solution. Unrealistic expectations arise when AI is presented as an instant transformation, when in practice value is achieved gradually. Leaders should define clear, measurable objectives tied to specific business challenges, tracking outcomes such as improved decision quality, reduced processing time, or enhanced customer experience. Incremental progress deserves celebration, since smaller improvements often create cumulative value and build organisational confidence.
“Above all, leaders should foster a culture of learning, treating insights and occasional setbacks as part of the innovation process.”
What practical advice would you give organisations looking to overcome customer and user hesitation while scaling AI initiatives successfully?Focus on people. Successful adoption is achieved by helping people understand how AI improves their experience, solves real problems, and fits naturally into the way they work. Communication is a powerful enabler, so organisations should explain why AI is being introduced, what value it will deliver, and where human involvement remains important. Involving users early ensures solutions address genuine needs and creates a sense of ownership. Adoption should be a continuous process supported by training, feedback, and refinement. Success should be measured by user acceptance and business impact, not technical performance alone.
Source: Tahawul Tech