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Scaling Generative AI: 13 elements for sustainable growth and value

AI scaling factors across strategy, process, talent, and data and technology

Near the top of nearly every enterprise agenda is a question of how to leverage Generative AI (GenAI). With use cases proliferating horizontally across functions and vertically within business units, we’ve identified 13 elements to help organizations take the next step to sustainably scale GenAI for strategic business  value.

Key takeaways:

  • Scaling GenAI remains a challenge. Over 70% of organizations have implemented only 1/3 of their GenAI projects, underscoring the difficulty of achieving enterprisewide AI adoption and value.
  • Strategic alignment is essential. Successful scaling requires aligning GenAI initiatives with business objectives while prioritizing high-impact, value-driving use cases—instead of adopting technology for its own sake.
  • Internal trust is critical. As the roles of employees evolve, building workforce trust in GenAI requires transparent communication, clear documentation and support.
  • Effective scaling relies on robust data and infrastructure. Establishing an “AI Factory” model that supports reusable components and scalable products can enhance data management and strengthen infrastructure.
  • Risk management must evolve as the regulatory environment does. As the landscape of regulations continues to change, organizations must proactively manage compliance, risk and governance to deploy GenAI safely and effectively at scale.

 

STRATEGY

PROCESS

TALENT

DATA AND TECHNOLOGY

Signs you’re successfully scaling GenAI

  • Increased speed to market, from ideation to deployment
  • A decline in proof-of-concept demand, as demand shifts to low-code environments available to business users
  • A decrease in unit cost for new capabilities/solutions, with technical solutions and code being reusable, thus reducing development efforts
  • An increase in the number of foundational capabilities that help the organization access GenAI advancements as they emerge
  • An increase in domain-specific models allowing for more use cases and broader application across the organization
  • Increased use of capabilities and solutions, owing to a growing number of users in the enterprise
  • An increase in stated value realization on a cumulative basis due to GenAI
  • An increase in internal certification/badging of existing employees in GenAI capabilities, both functional and technical
  • Use of GenAI to redefine a business process, rather than embedding GenAI in existing business processes

An evolving approach to Generative AI strategy

Deloitte’s State of GenAI in the Enterprise Q3 2024 report reveals that, while organizations are improving and multiplying their GenAI capabilities, many businesses are encountering challenges moving from proof of concept to scale as the leading practices, processes and ecosystem of complementary technologies are still being developed and defined. While change is inevitable, pursuing the 13 elements of scale can help position organizations to drive value as this transformative technology continues to evolve.

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