On transformation, C&T firms highlight the potential for AI to reshape careers, foster talent development and positively affect work cultures. They describe AI as a coach and tutor. Its adaptive feedback mechanisms can accelerate learning and reduce the preparation time for employees to become client- ready or manager-ready. Business leaders also point to cultural dividends beyond productivity: workers experience less burn-out, enjoy faster decision cycles and have more opportunities for experimentation or prototyping. While these potential benefits vary across companies and industries, they hint at an expanded conception of AI’s promise – one that includes improved employee experience and organizational culture alongside measurable efficiency.AI at the client interface BOX 2 Companies described how AI is raising the quality of client-facing work, such as sales or customer support. When solving a customer’s issue, empathy and personal connection can be just as important as the technical expertise needed to resolve the problem. For example, customer support AI agents can be trained to do sentiment analysis and escalate to a human agent when they detect a change in the customer’s tone. In addition to improving the customer’s experience, these use cases can directly drive core business metrics, such as revenue growth or renewal rates. At Pegasystems, Pega Blueprint™ streamlines the ideation, design and building of enterprise workflow apps, reducing weeks of discovery and demo-building to hours. GenAI drives creative process design, while AI agents are deployed to follow the prescribed workflows, thereby making AI predictable and governable. Even new hires can lead collaborative design sessions, providing live, real-time examples in meetings. For example, Vodafone used Blueprint to both radically improve its radio optimization process in just seven weeks and complete its budget process, from ideation through to delivered production app, in under 40 hours. Snowflake successfully launched a go-to- market assistant based on its Snowflake Intelligence solution, for higher-quality customer conversations with less preparation. The large language model (LLM)-powered assistant unifies marketing, learning and development, CRM and performance data within Snowflake’s platform, and makes it all accessible to business users through a natural language interface. The assistant is being used by 1,500 weekly average users, with a >90% Net Promoter Score (NPS). More importantly, customer teams are reporting more time spent on better, higher-quality interactions focused on customer needs. As these cases show, AI is not just cutting busy work. It is making client conversations sharper, helping juniors contribute earlier and giving professionals more room to focus on strategy and relationship-building. In practice: Telefónica deployed AI-powered recommendation engines to support a skills- based organizational strategy, enabling predictive and personalized career pathing for each employee. With 76% of employees having their skills mapped in a common taxonomy, the system extracts skills, matches roles and suggests job positions and learning courses with 80–90% accuracy. Annually, it recommends around 3,000 job vacancies and 12,500 learning courses. This initiative has enhanced internal mobility, engagement and alignment between individual development and business needs. In practice: HP uses an AI-driven coaching platform to improve employees’ video presence and communication skills. The app offers real-time feedback during video calls and personalized practice sessions tailored to roles and business needs. HP uses these tools for sales training, leadership development and onboarding programmes, ensuring employees represent the brand with confidence and authenticity in meetings. AI at Work: From Productivity Hacks to Organizational Transformation 9

AI at Work from Productivity Hacks to Organizational Transformation 2026