The days of AI acting solely as a predictive tool or chatbot are numbered.

Armand Ruiz, IBM’s vice president of product management for its AI platform, told delegates at the SXSW festival in Australia this week that AI agents will soon enable businesses in the APAC region to automate complex, multi-step tasks, allowing employees to focus on more. human-centered activities.

Ruiz explained that AI technologies have evolved from traditional machine learning predictive models to the widespread use of chatbots. He predicts that the next step will mark the beginning of an “agentic era,” in which specialized AI agents collaborate with humans to improve organizational effectiveness.

“We have a long way to go for AI to allow us to do all of these routine tasks and do it reliably, and then do it in a way that you can scale, then explain it.” and you can watch him,” Ruiz told the crowd. “But we’re going to get there, and we’re going to get there faster than we think.”

What is an AI agent?

According to Ruiz, an AI agent is a system that can autonomously reason about complex problems, break down tasks, create action plans, and execute those plans using a suite of tools. These agents demonstrate advanced reasoning, memory retention, and the ability to perform tasks independently.

Ruiz identified four capabilities of AI agents: planning, memory, tools and action.

AI agents and their capabilities

1. Planning

AI agents are capable of performing advanced planning to respond to given tasks or prompts.

Personal reflection: Agents can reflect on themselves or check whether their decisions make sense or not.

Self-criticism: Agents can use feedback, often from the same or different extended language models, to critique and improve their plans.

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Chain of thought: Agents can break larger tasks into smaller steps to improve accuracy.

Breakdown of sub-objectives: They can also set sub-goals by breaking larger tasks into manageable pieces.

2. Memory

AI agents leverage both short- and long-term memory to support their autonomous actions.

Short-term memory: This contextual memory allows agents to track actions within an existing session.

Long-term memory: AI agents can record past interactions, helping them learn from mistakes and continually improve their performance over time.

3. Use of tools

AI agents will be connected to third-party tools to accomplish their tasks. With proper access and governance, they could leverage tools ranging from web search and code generation platforms to enterprise systems, such as HR platforms, Microsoft Teams, CRM tools, cloud services and data warehouses.

4. Autonomous action

The true potential of AI agents lies in their ability to act autonomously on behalf of humans. Whether streamlining HR workflows such as recruiting, resolving software code issues, or addressing other business challenges, these agents will transform AI from passive chatbot to proactive actor.

Companies will orchestrate armies of agents within their workforce

Companies will likely have “millions of AI agents” working for them, Ruiz said. These agents, who will essentially act as colleagues or AI assistants to human employees, will be able to work collaboratively with each other on various tasks, allowing them to “solve problems end-to-end”.

Ruiz explained that AI agents can operate as single- or multi-stage systems, with their actions coordinated and guided by super AI.

One-step AI agents

One-step agents are those who can perform specific tasks or resolve individual issues when prompted, executing them using appropriate tools. The tools are defined and the process is still quite manual, although these agents can access systems such as LLMs to produce results.

Ruiz cautioned that there may be times when these AI agents hallucinate or don’t perform as well as desired.

Multi-stage AI agents

Multi-stage AI agents leverage iterative strategies in what Ruiz called a “think, act, and observe loop,” using one or more LLMs. “You have this loop that is very iterative, and it’s amazing how much it improves the outcome and provides better results until you get the end result,” he said.

Super AI

Companies will deploy “Super AI” systems to coordinate networks of individual AI agents. According to Ruiz, these super AIs will act as orchestrators, planning tasks, breaking them down into smaller components and assigning them to the most appropriate agents within the organization to complete the work efficiently.

“An AI agent can be very good at sales, product management or coding, or very good at mainframe or a specific programming language. Everyone will have small language models that are very easy to train, very inexpensive to run, and will have specific access to certain tools,” he said.

Who will be the major users of AI agents?

Ruiz identified three main user groups that could benefit from AI agents: developers, no-code business users, and end users.

Developers: Traditionally, AI, data science and machine learning required highly specialized expertise. However, Ruiz explained that millions of developers now have access to these technologies through APIs. Additionally, frameworks like CrewAI allow developers to quickly create and deploy AI agents.

Professional users: No-code tools will soon allow business users to create their own AI agents through a user interface. IBM’s new Agent Builder, which will debut at IBM’s TechXchange conference, will enable employees at all levels of an organization to create agents capable of automating and performing organizational tasks without need programming knowledge.

End users: A wide range of end users will also interact with AI agents, Ruiz said, noting that there will be “a whole spectrum” of end users who will adopt and use these tools in various ways.

How agents will transform our businesses and our work

Ruiz said factories are a good analogy for how work can transform. In the early 1900s, factories relied on labor-intensive manual labor performed by many people, which was time-consuming and inefficient. However, at the dawn of the industrial revolution, machines were introduced to automate them and speed up production.

He explained that AI is now evolving to help automate and augment mental labor in the same way that machines automate physical labor in factories. Rather than replacing them, he says this will allow them to focus on more strategic and innovative tasks, improving overall productivity and efficiency.

“We’re already seeing this in marketing,” Ruiz added. “We’re going to see this in sales as well, and it’s going to start to extend across all different job functions. Our goal is for AI to free us from many distractions and allow us to work on meaningful work and human relationships.

“The vision is for AI agents to work alongside humans in a complementary way, augmenting human capabilities rather than replacing human workers entirely. This will enable greater productivity, a better work-life balance and a focus on higher value-added activities.