Do the basics brilliantly When it comes to scaling AI, Strategic Scalers do the basics brilliantly. Compared to companies in Proof of Concept, they have a clearly defined strategy and operating model for AI, defined process and owners for measuring value from AI, clearly defined accountability, appropriate levels of funding, Sizing up and flexible business processes with embedded AI. They also scale through reusable assets on platforms, so successive AI programs are 3-5X faster to market at lower spend. the situation The “smaller” companies in our study generated revenues between US$1 and 5 billion a year. The largest had revenues of more than US$30 billion. When it comes to scaling AI, are there any major differences +60% +50% +50% between these two groups of companies? Do the largest companies face lower scaling Clearly defined Clearly defined Appropriate success rates due to their organizational accountability strategy and operating level of funding complexity? Or, quite the opposite, do they for scaling model for scaling achieve higher returns as they untap greater value potential? When we grouped the surveyed companies by size, we found no significant differences in +26% scaling success rate or return on AI +30% +27% investments. So, size is not a factor. It’s all Flexible business about instilling the right AI capabilities and Defined process and Packaged or custom processes with mindset in the organization. owners for measuring built AI applications value from AI for scaling embedded AI AI: BUILT TO SCALE 11