Meta, Outshift, Intuit and Asana are betting that the future of AI is agentic

The dawn of agentic AI: The concept of agentic artificial intelligence, which involves autonomous systems capable of making near-human decisions, is gaining traction in the tech industry and was a central focus at a recent VentureBeat AI Impact Tour event.

• Industry leaders from companies such as Outshift, Meta, Asana, and Intuit gathered to discuss the future of AI and its potential to revolutionize various sectors through autonomous decision-making capabilities.
• The concept of agentic AI represents a significant shift from traditional AI systems, promising more advanced and independent problem-solving abilities.

Key components of agentic systems: Vijoy Pandey from Outshift emphasized the need for a comprehensive infrastructure to support the development and deployment of agentic AI.

• Distributed agentic systems computing is seen as a crucial element in the advancement of this technology.
• An open and interoperable “internet of agents” is proposed as a framework for these systems to operate effectively.
• The infrastructure for agentic AI will require multiple abstraction layers, including open models, open tooling, orchestration and discovery layers, and secure communication protocols.

Industry momentum and early adoption: Despite the technology still being in its early stages, companies are already exploring ways to integrate agentic AI into their operations.

• Mano Paluri of Meta stressed the urgency for businesses to start working on AI agents, even though the technology is not fully mature.
• Meta is developing a family of customizable AI agents designed to cater to various business and consumer applications.
• Real-world implementations are already underway, with companies like Asana using agentic AI for workflow management and chat interfaces, and Intuit leveraging it for customer onboarding and navigating complex tax code changes.

Challenges and considerations: The development of agentic AI systems presents several technical and practical challenges that need to be addressed.

• One key issue is how agents will discover each other and understand their respective capabilities in a multi-agent environment.
• Collaboration between agents to solve complex problems and handle uncertainty is another area requiring significant research and development.
• Enabling agents to communicate using natural language instead of fixed structures is seen as a crucial step towards more flexible and adaptable AI systems.

The call for collaboration: Industry experts are emphasizing the importance of a collective approach to developing standards and guidelines for agentic AI.

• There is a growing consensus on the need for the tech community to work together on establishing open-source guidelines and standards for agentic AI systems.
• This collaborative effort is seen as essential for ensuring interoperability, security, and ethical considerations in the development of autonomous AI agents.

Future implications and preparations: Despite the technology still being in its early stages, business leaders would be wise to prepare for an agentic future.

• Companies are encouraged to start exploring and implementing agentic AI solutions to stay ahead of the curve and gain a competitive advantage.
• The potential impact of agentic AI spans across various industries, from improving customer service to enhancing complex decision-making processes in businesses.

Analyzing deeper: While the promise of agentic AI is significant, it’s important to consider the potential challenges and ethical implications that may arise as these systems become more prevalent.

• Questions about accountability, privacy, and the impact on human employment will likely become more pressing as agentic AI systems take on increasingly complex tasks.
• The development of robust regulatory frameworks and ethical guidelines will be crucial to ensure that the benefits of agentic AI are realized while mitigating potential risks.