Businesses Tackle AI Uncertainty: De-risking Agentic AI Investments

De-risking Investment in AI Agents: Navigating the Uncertainty of Agentic AIs As the adoption of artificial intelligence (AI) continues to accelerate, businesses are increasingly turning to agentic AI systems that can plan, act, and adapt towards a defined goal. These systems have the potential to revolutionize customer experience, automate complex service interactions, and support employees in real-time. However, the shift from deterministic flows to non-deterministic, generative systems also brings new challenges. Financial Impact: According to a recent report by Gartner, the global AI market is expected to reach $190 billion by 2025, with agentic AIs accounting for a significant portion of this growth. Companies like NICE, which has become a leader in customer experience solutions, are already seeing the benefits of investing in these technologies. Company Background and Context: NICE's vice president of product management, Neeraj Verma, notes that "every single person" who interacts with their company's services has engaged with some form of generative AI. This expectation is driving businesses to adopt agentic AIs, which can handle complex service interactions, support employees in real-time, and scale seamlessly as customer demands shift. Market Implications and Reactions: The move towards agentic AIs requires businesses to rethink their approach to testing and validation. Traditional methods of testing scripted flows are no longer applicable, as generative systems can respond differently each time they interact with a user. This uncertainty has led some companies to adopt more agile development methodologies, such as continuous integration and delivery (CI/CD). Stakeholder Perspectives: Verma emphasizes the importance of balancing safety and flexibility when giving an AI system agency. "We need to ensure that these systems are not only flexible but also safe," he notes. This requires businesses to invest in robust testing and validation processes, as well as ongoing monitoring and maintenance. Future Outlook and Next Steps: As agentic AIs continue to evolve, businesses will need to adapt their approach to development, deployment, and maintenance. This may involve adopting more advanced AI-powered testing tools, such as model-based testing or generative testing. Additionally, companies will need to prioritize ongoing training and education for employees working with these systems. Key Takeaways: Agentic AIs have the potential to revolutionize customer experience and automate complex service interactions. The shift from deterministic flows to non-deterministic, generative systems requires new approaches to testing and validation. Businesses must balance safety and flexibility when giving AI systems agency. Ongoing training and education will be essential for employees working with these systems. By understanding the implications of agentic AIs and taking a proactive approach to development and deployment, businesses can unlock the full potential of these technologies and drive growth in an increasingly competitive market. *Financial data compiled from Technologyreview reporting.*