Despite the ambition to scale agentic AI, organizations are facing significant challenges primarily stemming from outdated processes and insufficient access to reliable data. A recent study highlights that merely layering AI onto existing legacy systems does not suffice; instead, a complete redesign of these processes is essential. Currently, only 31% of companies plan to revamp their processes around AI agents by 2028, while a promising 74% anticipate changes by 2030.
Workforce Investment is Critical for AI Adoption
Half of the surveyed leaders expressed concern that their organizations are not sufficiently investing in workforce transformation, which is crucial for effective AI integration. The expectation is that new roles will emerge, enabling collaboration between humans and AI to enhance business value. However, nearly 43% of business leaders foresee significant job disruptions due to agentic AI, as many routine tasks will become automated.
The financial implications of training employees and managing AI tokens could increase budget pressures, leading to unexpected costs. To address this, leaders must enhance their awareness regarding infrastructure investments, employee preparedness, and AI literacy, as well as the expenses related to redesigning processes to align with AI capabilities. Currently, 71% of organizations are focusing on improving baseline AI literacy, while 65% are committed to upskilling employees in roles likely to be affected by AI.
The survey results underline the importance of investing in AI-friendly infrastructure, a solid data foundation, and comprehensive employee AI training as pivotal to scaling AI agent deployments successfully. Key considerations include developing a cohesive agentic roadmap, treating AI layering as a transitional phase rather than an endpoint, allocating adequate resources for workforce transformation, and clarifying the operational model involving both humans and AI.
Transitioning into an agentic enterprise will necessitate a thorough redesign of current business processes. This includes reskilling the workforce to adapt to new methodologies, reallocating employees from repetitive tasks to more strategic roles, and restructuring organizational and financial frameworks. Companies must also reclaim previously overlooked value creation opportunities and recalibrate performance metrics to reflect agentic usage, such as tokens utilized for automating discrete work units. Moreover, leadership must embrace a vision focused on autonomy, developing strategies and execution models that align with this goal.
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