AI: Season 2

Scaling for impact

Artificial intelligence is no longer the prerogative of a few digital innovators – far from it. Here, we discuss how many organizations are ready to take the next big step in scaling AI across core business operations.

In recent years, AI has become a core concern for businesses as well as a foundation for improved consumer experience across sectors. What it can do, and what it might do in the future, are hotly debated.

The story of AI, however, continues to develop. In narrative terms, we are progressing from AI: Season 1, to AI: Season 2. We’ve moved beyond the promise of potential, to a concrete reality in which AI is embedded as a core business processes.

However, many organizations still use AI on a prototype basis and for isolated tasks. The next question is how to implement it in a pragmatic, scalable way across the business while embedding it into the operating model and wider culture.

Scaling AI across a business 

According to Anne-Laure Thieullent, AI and Analytics Group Offer Leader at Capgemini, organizations need to move beyond simply speculating about AI’s potential, to developing a practical understanding of the role data must play in scaling the technology.

“AI used to be overhyped, but organizations are getting wiser. Our clients are becoming more mature because they are infusing AI into their businesses by activating data at the core of their processes, organizations, and culture. This is what we mean by ‘intelligence’ – business outcomes delivered at scale.”

Broadly speaking, AI can support four important business needs:

  • Enhancing operations
  • Rehumanizing the customer experience to boost engagement
  • Helping people to assess risks, detect fraud, and ensure compliance
  • Augmenting the human workforce.

Data must reflect reality

Organizations need to activate data at scale and use powerful analytics if they are to unleash AI’s full potential to accomplish these tasks. And, as Steve Jones, CTO for Insights and Data, says, that data must be trustworthy.

“There’s only one measure of good data quality – that it acts as an accurate reflection of reality,” he says. “This is the ‘simple’ challenge on which we are working with clients. For a business to become data driven, it needs a platform for data that reflects its reality, at the pace at which decisions need to be made – accurate data that is late is pointless.”

Expertise in AI and machine-learning tools, the important regulatory, privacy, and ethical considerations in this area, and strong technology partnerships are all key to realizing the value of accurate, timely data.

Empowering marketing

Capgemini has more than 25,000 professionals around the world driving transformation by bringing together our clients’ data assets with third-party sources to transform processes fundamentally – and help them understand their customers, right down to the level of the individual. For Anne-Laure, our work with digital marketing companies exemplifies what we bring to clients in this area.

“For brands, success used to mean relying on data for interesting insights to justify decisions,” she says. “Today’s data-rich, dynamic technology landscape raises the bar. Data-native brands, born with a focus on the capture, mobilization, and activation of data, have been out front in the application of AI technology. We have a unique ability to navigate this marketing technology landscape through proprietary partnerships and approaches, empowering traditional marketers to take the lead.”