Nail it, then scale it To answer that question, Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries. The study focused on determining the extent to which AI enables the business strategy, the top characteristics required to scale AI, and the financial results when done successfully. The aim: Help companies progress on their AI journey, from one-off AI experimentation to gaining a robust organization-wide capability that acts as a source of competitive agility and growth. Three distinct groups of companies with increasing levels of capability required to successfully scale AI emerged from the research. Proof of Concept Industrialized 01 02 03 Factory Strategically Scaling for Growth In our experience, most companies (80-85%) are Only 15-20% of companies have made this leap. These Very few (<5%) companies have progressed to this point stuck on this path.They conduct AI experiments and companies have journeyed beyond proof of concept to on their AI journey. These companies have a digital pilots but achieve a low scaling success rate and a achieve a much higher success rate scaling AI—nearly platform mindset and create a culture of AI with data low return on their AI investments. Their efforts tend double. And a much higher return—nearly three times and analytics democratized across the organization. to be siloed within a department or team and are their counterparts. As a C-suite priority, these They have scaled thousands of models with a responsible often IT-led. They lack a connection to a business companies have a clear AI strategy and operating AI framework. They promote product and service outcome or strategic imperative. The time and model linked to the company’s business objectives, innovation and realize benefits from increased visibility investment it takes to scale is underestimated, supported by a larger, multi-dimensional team into customer and employee expectations. Our leaving the full potential of AI untapped. championed by the Chief AI, Data or Analytics Officer. research indicates that industrializing AI will enable However, the scaled AI is generally across point competitive differentiation which is correlated with solutions, e.g., personalization. significantly higher financial results. What do Artificial Intelligence (AI) encompasses Pilot: Rolling out a capability with real data, Scale: Extension of the piloted capability we mean? multiple technologies that enable users and processes in a production across the full applicable scope with all computers to sense, comprehend, act, and environment (using a subset of the relevant relevant data, end users, customers, and learn. AI includes techniques such as scope). The purpose is to test how the processes. Purpose is to maximize the machine learning, natural language capability performs with a limited scope and application’s value to the organization. processing, knowledge representation, to make any needed modifications before computational intelligence, among others. expanding to the full applicable scope. AI: BUILT TO SCALE 4