A profitable path powered by AI: Benefits of becoming a ‘data master’

More companies are closer to capturing an abundance of benefits from a well-structured strategy that harnesses the power of data and artificial intelligence.

A new report reveals the potential value of achieving mastery over data as well as some of the keys to getting there.

In Data-powered enterprises: The path to data mastery, the Capgemini Research Institute categorized 17% of 500 surveyed companies as “data masters” – organizations around the globe that, based on responses provided by representative data and business executives, displayed acuity in a series of data-driven parameters.

Those companies reported a 39% higher net income margin the previous year than the whole of the 500 companies on average, and 42% higher net income growth over the past three years.

In the previous Capgemini report in 2020, a similar percentage of companies (16%) were labeled “data masters” for having achieved mastery across two dimensions – a series of data foundation/enablers parameters and a series of data behavior parameters.

With four more years of AI advancements, the percentage of companies closing in on masters status has more than doubled: 33% now are leaders in one dimension but not the other, compared to just 14% being halfway there in 2020.

What data-related actions, according to the report’s findings, could put companies over the top?

Data activation

• 87% of data executives in the masters group said their company has a vision for a data-powered enterprise with AI at its center, compared with 62% of others.

• 84% of data executives in the masters category said their organizational vision is readily accessible to employees (compared with 64% of others). Around 71% of business executives in the data masters category say they are actively upskilling the workforce for the required skills in generative AI (compared with 56% of others).

Data advantage

• 83% of data executives in the data masters category have evaluated the current state of data infrastructure, systems, and processes, and they have a comprehensive plan for scaling the deployment of generative AI (compared with 56% of others).

• 87% of data executives in the data masters category have set standards and prequalify sources to ensure that data fed into AI models follows specific protocols (compared with 69% of others).

Data enablers

• 90% of data executives in the data masters category said that key business and technical stakeholders understand commercial models and the cost implications of generative AI technologies (compared with 73% of others).

• 87% of data executives in the data masters category use technical guardrails and human-in-the-loop supported controls (compared with 59% of others).

Even for top achievers, given generative AI’s seemingly daily advancements, success can be a moving target. Across the entire population of the survey, 75% of respondents said that scaling generative AI proofs-of-concept to large-scale deployments is a major challenge.

In response to the challenge, 95% of data executives in the data masters category said they have built cross-functional data and insights to work with business sponsors, business analysts, data engineers, data scientists, solution architects, and software developers. By comparison, 69% of others have done the same.

— To comment on this article or to suggest an idea for another article, contact Bryan Strickland at Bryan.Strickland@aicpa-cima.com.