As organizations shift from isolated pilots to enterprise-wide deployments of generative and agentic AI, they are unlocking transformative benefits in innovation and productivity.
The landscape of artificial intelligence (AI) is rapidly evolving, as organizations are no longer treating AI initiatives as one-off projects or isolated pilots. Instead, many are transitioning to enterprise-wide deployments that promise not only enhanced innovation but significantly improved productivity. This shift marks a critical phase in the AI revolution, with organizations beginning to realize the transformative benefits that come from integrating generative and agentic AI into their core operations.
However, while this mainstream adoption is encouraging, it also introduces new hurdles that must be addressed. Cost containment, workforce adaptation, governance, and sustainability are among the challenges that organizations face as they seek to harness AI’s full potential. It’s essential that companies approach their AI strategies with careful consideration of these factors to ensure lasting success and a responsible approach to technology integration.
In its third edition of the research series entitled Harnessing the value of AI: Unlocking scalable advantage, the Capgemini Research Institute provides insightful analyses and strategies. Based on a global survey of 1,100 leaders from organizations with annual revenues exceeding $1 billion, the findings reveal compelling trends that underscore both the opportunities and obstacles facing today’s AI adopters.
- Gen AI adoption is now mainstream: The research indicates a dramatic rise in generative AI adoption, climbing from just 6% in 2023 to an expected 30% by 2025. Currently, a noteworthy 93% of organizations are exploring or enabling generative AI capabilities. However, even as benefits from AI continue to mount, cost concerns remain a persistent issue for many.
- AI agents are gaining ground: The study highlights that 14% of organizations are implementing AI agents at either partial or full scale, with an additional 23% engaged in pilot programs. Intriguingly, of the organizations scaling AI agents, nearly 45% are experimenting with multi-agent systems, indicating a trend towards more complex AI integrations.
- AI is evolving from tool to teammate: The role of AI is shifting, with almost six in ten organizations planning to integrate AI as augmenting or autonomous collaborators in the coming year. Yet, despite this ambition, most organizations are ill-prepared for such a significant transition.
- Trust and governance are lagging: A significant 71% of organizations report an inability to fully trust autonomous AI agents for enterprise applications. While 46% do have governance policies in place, compliance and adherence to these policies remain low, signaling a critical need for improvement in this area.
- AI’s environmental impact is under scrutiny: As sustainability becomes a priority, only one in five organizations currently measures the environmental footprint of their generative AI initiatives. Nonetheless, there is growing interest in implementing sustainability measures, such as utilizing smaller, task-specific models.
The research brief offers actionable insights aimed at business and technology leaders striving to navigate the complexities of AI integration. To maximize the business value of AI while ensuring responsible and ethical deployment, organizations should consider three key strategies:
- Architect for scalability: It’s crucial for organizations to redesign their processes to facilitate smooth AI integration. Embracing “platformization” is recommended for a successful enterprise-wide deployment that maximizes the efficacy of AI technologies.
- Reinforce trust through governance: Establishing clear boundaries for AI execution is important. Organizations should create cross-functional governance structures that include ethical oversight, along with fortifying data management and traceability to enhance trust in AI systems.
- Design human-AI collaboration models: Prioritizing reskilling and fostering a cultural transformation within organizations is essential for facilitating effective collaboration between human and AI teams. Additionally, workflows and performance metrics should be adapted to cater to these hybrid teams.
For organizations keen to transition from mere experimentation to substantial, ethical, and high-value AI deployment, a comprehensive understanding of these insights and strategies is critical. To explore further into how AI can be harnessed effectively, download the Harnessing the value of AI research brief today.