03 Treat AI The “A” and “I” as a team sport in team A leading global convenience store chain with The effort of scaling calls for embedding $60B in revenue and 16,000 locations sought to gain a more competitive position to stave multi-disciplinary teams throughout the organization off more agile rivals. in addition to having sponsorship from the top. They leveraged data science to price their products more competitively to better match customer demand across global markets. Leveraged machine learning and automation The effort of scaling calls for embedding multi-disciplinary teams to increase pricing frequency. And throughout the organization—teams with clear sponsorship from the top established virtual agents to interact with ensuring alignment with the C-suite vision. For Strategic Scalers, these their global category management teams to teams are most often headed by the Chief AI, Data or Analytics Officer. 92% drive adoption of the new pricing approach. They’re comprised of data scientists; data modelers; machine learning, All of these changes were made possible data and AI engineers; visualization experts; data quality, training and of Strategic thanks to multi-disciplinary teams with skills communications specialists. Scalers leverage in areas like data engineering, visualization, multi-disciplinary data quality, and human-centered design. It’s a lesson Strategic Scalers have learned well. In fact, a full 92% of them teams The initiative is expected to deliver an leverage multi-disciplinary teams. Embedding them across the organization is expected US$300 million in gross profit not only a powerful signal about the strategic intent of the scaling effort, it uplift annually once fully scaled. also enables faster culture and behavior changes. In contrast, those still in Proof of Concept are more likely to rely on a lone champion within the technology organization to drive AI efforts. AI: BUILT TO SCALE 15