2025: Agents to Usher in a Profitable Era for AI

2025: Agents to Usher in a Profitable Era for AIAt this week's Reuters NEXT conference in New York, executives and researchers converged on a prediction: AI agents and their profitability will be the defining theme of 2024. Agents, or autonomous systems capable of performing tasks like shopping and scheduling meetings without direct human intervention, have long been a holy grail of AI research

2025: Agents to Usher in a Profitable Era for AI

At this week's Reuters NEXT conference in New York, executives and researchers converged on a prediction: AI agents and their profitability will be the defining theme of 2024. Agents, or autonomous systems capable of performing tasks like shopping and scheduling meetings without direct human intervention, have long been a holy grail of AI research. However, attendees believe that the emergence of incremental reasoning methods this year, such as those employed in OpenAI's o1 model, are making these capabilities a reality.

OpenAI CFO Sarah Friar offered a bold prediction at the summit: "I think next year we'll see a huge amount of dynamism around agents, and the pace of development might be breathtaking. We think this is just the prelude to what agents will do in 2025. They'll really become your assistants in handling everyday tasks." Friar, who joined the Microsoft-backed OpenAI six months ago, exudes confidence in the future of AI. She even predicts the arrival of Artificial General Intelligence (AGI) within the next few years autonomous systems that outperform humans in most economically valuable tasks. When pressed on a timeline for AGI, Friar stated firmly: "I don't believe it's a decade away."

Friar's sentiment isn't isolated. George Mathew, Managing Director at venture capital firm Insight Partners, points to the economic benefits already emerging from last year's advancements in reasoning capabilities. "We're starting to see a complete reshaping of both back-office and front-office functions," Mathew stated. He cited his investment in Relevance AI, whose digital sales teams effectively replace human labor at a quarter of the cost, as a prime example of agents' productivity potential.

Based on these significant productivity gains, another venture capitalist, Molly Alter of Northzone, predicts 2025 will be "the profitable year for AI." Alter explains: "Last year, companies were all focused on revenue growth. This year, the focus has subtly shifted from just growth to, 'If I use AI, how much will my margins improve?'" This shift clearly indicates that businesses are beginning to view AI as a tool for direct profit enhancement, not just growth acceleration.

This optimism regarding agents and AI profitability isn't confined to tech startups. Senior executives from major banks and other large enterprises report moving beyond experimentation and actively integrating AI into daily workflows. Robin Vince, CEO of a New York bank (name withheld for confidentiality), revealed that thousands of their employees now create and deploy large language model (LLM)-powered agents to assist with daily tasks. Vince stressed: "We are investing heavily in leveraging tools to create greater leverage for our employees, providing solutions for our clients, and generating insights and data that are unattainable through traditional methods." This signals a move from proof-of-concept to large-scale deployment and substantial impact on business operations.

The rise of agents is inextricably linked to the advancement of incremental reasoning methods. This approach allows agents to tackle complex tasks more effectively, resulting in significant efficiency gains and cost savings. Relevance AI's low-cost digital sales teams, for instance, owe their success largely to the increased precision and automation enabled by incremental reasoning. The maturation of this technology also means businesses can more easily integrate agents into existing workflows and maximize their value.

OpenAI's o1 model, representative of incremental reasoning, mimics human thought processes, allowing agents to break down complex problems step-by-step and take appropriate action. This contrasts sharply with previous rule-based systems, often ill-equipped to handle complex, unstructured information. This breakthrough enables agents to genuinely "understand" tasks and make intelligent decisions, representing a leap from simple automation to true autonomy.

Furthermore, advancements in LLMs provide a powerful engine for agent development. LLMs process and understand vast amounts of data, providing agents with a rich knowledge base and strong reasoning capabilities. The New York bank's successful deployment of LLM-powered agents directly reflects this technological progress. This highlights LLMs not as a standalone technology, but as a crucial component in agent construction.

Looking ahead, agents will play increasingly vital roles across various sectors. From customer service to supply chain management, financial analysis to medical diagnosis, agents will significantly boost efficiency, reduce costs, and create new value for businesses. This will not only fuel the booming AI industry but also profoundly reshape how we work and live.

However, widespread agent adoption presents challenges. Ensuring reliability, security, and adherence to ethical guidelines is paramount. While pursuing AI profitability, its crucial to address potential risks and establish regulations to ensure safe and responsible development and application.

In conclusion, the core theme of 2024 in AI will revolve around agents and their profitability. From venture capitalists to large enterprises, theres widespread confidence and active investment and deployment. 2025 is poised to be the year AI delivers tangible returns, marking a significant shift from proof-of-concept to practical application and unprecedented transformation across industries. Agents, as a key component of AI technology, will play a pivotal role, propelling AI into a new phase of development and creating greater value for humanity. However, while embracing the opportunities agents offer, we must cautiously navigate the ethical and security challenges inherent in their evolution.