Careful Planning and Execution Can Help Avoid Pitfalls
Today, artificial intelligence (AI) is synonymous with modern-day innovations, and at the forefront is agentic AI. This emerging technology has the potential to transform how we interact with machines, referring to autonomous systems that can sense and act on their environment to achieve specific objectives.
Imagine having a team of highly intelligent AI agents working together to complete your tasks. For instance, if you’re organizing a birthday party, one agent can identify the venues while another sends invitations. This technology, designed to enhance efficiency, mimics human intelligence, raising concerns about the autonomy risks that businesses must assess before deploying these AI agents.
Despite being in its infancy, agentic AI can significantly impact enterprises, with risks that include unintended decisions, insufficient explainability, data vulnerabilities, ethical dilemmas, and potential over-reliance on automation. Data vulnerabilities are particularly concerning since agentic AI depends on datasets for training. Poor data governance can lead to skewed outcomes, and data breaches may result in severe financial and legal consequences.
Moreover, excessive reliance on automation presents operational risks, especially during unforeseen events such as natural disasters or geopolitical tensions. Additionally, the deployment of agentic AI can lead to decreased morale among employees who may view these systems as competition.
Successfully navigating these risks requires a comprehensive strategy. Establishing governance frameworks is essential to maintain accountability while ensuring compliance with ethical standards. It’s also crucial to assess and monitor the quality and diversity of data used in AI training to prevent bias.
Finally, investing in human oversight will provide a necessary balance between humans and AI. By permitting human intervention in critical processes, organizations can enhance accountability and build trust in AI systems.
The writer is the founder & CEO of Findability Sciences.
