Governing the Agentic Workforce: What CIOs Need Before Scaling AI Agents
Agentic AI is integrating itself across industries as a force of productivity and efficiency in many different departments and roles.
Organizations are implementing AI agents at scale, and their potential to transform everyday work is undeniable. 40% of respondents from large organizations in McKinsey & Company’s State of AI survey report scaling AI agents, which is up from 27% last year. However, it is important for CIOs to understand the practices that are necessary to undergo before making this shift.
It may be tempting for organizations to act quickly on integrating AI agents at scale, but doing so can result in increased failure risk and low-quality results. A strong foundation will make all the difference for effective and responsible AI agents.
Delve into more information on governing the agentic workforce and what CIOs need before scaling AI agents for their organizations.
Scaling AI Agents
An AI agent is like a partner or a member of the team. They are excellent at collecting and processing data to create actionable insights with minimal human input. In addition, the speed at which they conduct immense workloads is swift, outpacing their human counterparts with ease.
Scaling these agents enables organizations to adopt technology that elevates the roles of human workers. Employees have the ability to save large amounts of time to focus on more high-impact, creative work, thanks to the autonomous capabilities of AI agents.
Modernizing Legacy Systems
There are a number of organizations, especially in the public sector, that still utilize outdated legacy platforms. These systems were not made to handle more advanced technologies such as AI, and can even present vulnerabilities that introduce cybersecurity challenges.
AI agents require clear structured data and systems, and outdated technology combined with AI agents has increased risk of failure due to misinterpreted logic and incompatibility. It is essential to modernize before introducing AI into organizations in order to reap the most benefits and receive measurable results that drive business growth.
Ensuring Data Readiness
AI systems rely on good data. It is imperative that organizations review, update, and clean their data to prepare it for integrating AI and ensuring its fullest potential.
AI agents depend on reliable inputs of data to ensure the most unbiased and accurate outputs, which is not only necessary for high-quality work but for mitigating operational and reputational risk. Organizations must have structured data available to each worker, whether a human employee or an AI agent, to enable a trusted and consistent workflow that benefits both the organization and those it serves.
Implementing Governance Frameworks
Before any AI implementation, it is critical that organizations develop strong governance frameworks. These will align the people of an organization with the strategy and technology that drive productivity and efficiency. The mission of governance is to set clear guidelines and rules that ensure that AI agents are not only effective but accountable and secure.
AI agents, while they have the capability to act autonomously, require strict human oversight. CIOs should be prepared to enact human-in-the-loop strategies before scaling AI agents to ensure that any automated actions or decisions are aligned with business priorities and are explainable and auditable.
AI agents are powerful sources of productivity and efficiency for enterprises, however ones that require a strategic and technological foundation in order to support their implementation.
Organizations in the public and private sectors can explore an AI-driven future with confidence through our practical and scalable solutions built for innovation. Sedna has deep expertise in the necessary foundations for any AI adoption projects, and our team is prepared to deliver technology that enables real value.
Reach out and get started on your AI journey with us.
“Data is a precious thing and will last longer than the systems themselves.”
– Tim Berners-Lee, Computer Scientist & Inventor of the World Wide Web
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