Accenture studied 1,500 C-suite executives with the aim to uncover how companies journey toward maturity in scaling AI, where new skill sets emerge as critical to success.
With the stakes higher than ever, what can we learn from companies that are successfully scaling AI, achieving nearly 3X the return on investments and an average 32% premium on key financial valuation metrics? Accenture conducted a landmark global study involving 1,500 C-suite executives from organizations across 16 industries to determine how crucial AI can be for your business.
According to the “Built to Scale: From experimental to exponential” from Accenture, which analyzes how AI-powered data, analytics and automation capabilities shift modern business workflows and accelerate time to value. 90% of the data in the world was created in just the past 10 years. 175 zettabytes of data will be created by 2025. Yet after years of collecting, storing, analyzing, and reconfiguring troves of information, most organizations struggle with the sheer volume of data and how to cleanse, manage, maintain, and consume it, reflecting the importance of understanding the fabric of AI, its tools—things like cloud-based data lakes, data engineering/data science workbenches with model management and governance, data and analytics marketplaces and search—to manage the data for their applications, from creation to custodianship to consumption.
Following are some highlights on the relationship between successfully scaling AI across the enterprise and key market valuation metrics.
- 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives, yet 76% report they struggle with how to scale.
- Three out of four C-suite executives believe that if they don’t scale artificial intelligence (AI) in the next five years, they risk going out of business entirely.
- Companies in our study that are strategically scaling AI report nearly 3X the return from AI investments compared to companies pursuing siloed proof of concepts.
- Further analysis validated a positive correlation between Strategic Scaling and a premium of 32%, on average, for three key financial valuation metrics.
A full 84% of C-suite executives believe they must leverage artificial intelligence (AI) to achieve their growth objectives. Nearly all C-suite executives view AI as an enabler of their strategic priorities. And an overwhelming majority believe achieving a positive return on AI investments requires scaling across the organization. Yet 76% acknowledge they struggle when it comes to scaling it across the business. What’s more, three out of four C-suite executives believe that if they don’t scale AI in the next five years, they risk going out of business entirely.
How crucial is scaling AI to your business?
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 Factory, Strategically Scaling, and Industrialized for Growth.
Proof of concept factory
In our experience, most companies (80-85%) are stuck on this path.They conduct AI experiments and pilots but achieve a low scaling success rate and a low return on their AI investments. Their efforts tend to be siloed within a department or team and are often IT-led. They lack a connection to a business outcome or strategic imperative. The time and investment it takes to scale is underestimated, leaving the full potential of AI untapped.
Strategically scaling
Only 15-20% of companies have made this leap. These companies have journeyed beyond proof of concept to achieve a much higher success rate scaling AI—nearly double. And a much higher return—nearly three times their counterparts. As a C-suite priority, these companies have a clear AI strategy and operating model linked to the company’s business objectives, supported by a larger, multi-dimensional team championed by the Chief AI, Data or Analytics Officer. However, the scaled AI is generally across point solutions, e.g., personalization.
Industrialized for growth
Very few (-5%) companies have progressed to this point on their AI journey. These companies have a digital platform mindset and create a culture of AI with data and analytics democratized across the organization. They have scaled thousands of models with a responsible AI framework. They promote product and service innovation and realize benefits from increased visibility into customer and employee expectations. Our research indicates that industrializing AI will enable competitive differentiation which is correlated with significantly higher financial results.
