What: Status quo bias and inertia are major obstacles to generative AI adoption in organisations, but targeted leadership and peer-driven strategies can overcome them.

Why it is important: This insight aligns with recent findings that only a small fraction of retailers successfully scale AI, highlighting the need for leadership-driven change and workforce engagement.

Status quo bias and inertia remain significant barriers to the adoption of generative AI, even when employees acknowledge the advantages these tools could bring to their daily work. People tend to default to established routines, often exaggerating the risks of change while overlooking the dangers of remaining static. Overcoming this requires organisations to reframe AI adoption as the new standard, making inaction appear riskier than embracing innovation. Leadership plays a pivotal role, with senior executives modeling the desired behaviors and visibly integrating AI into their workflows. Peer influence is equally powerful; celebrating early adopters and positioning them as internal champions accelerates cultural acceptance. Tailored training and exposure to successful AI integration in other organisations further help shift mindsets. These combined efforts create an environment where change feels natural and safe, encouraging employees to adopt new technologies and supporting the organisation’s broader transformation. This approach is essential for retailers aiming to remain competitive in a rapidly evolving market

IADS Notes: In September 2025, BCG reported that only 36% of retail workers felt prepared for AI-driven change, despite widespread tool adoption, highlighting the need for foundational upskilling. Forbes in October 2025 found that only 10% of retailers had scaled AI solutions, emphasising the importance of governance and cultural adaptation. BCG’s July 2025 research demonstrated that leader-driven change programmes were key to successful transformation at Saks, El Corte Inglés, and Galeries Lafayette. In April 2025, BCG showed that CEO leadership and employee engagement drove up to 30% operational efficiency gains. By September 2025, BCG confirmed that scalable GenAI innovation depended on infrastructure, oversight, and celebrating internal champions.

The cognitive brakes on the gen AI accelerator