×
Automation vs. agents — what’s the difference and which is best for your company?
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

The rise of AI agents and automation in disguise: As AI technology advances, a trend of automation systems masquerading as AI agents has emerged, raising questions about the true nature and capabilities of these technologies.

  • Gartner has named “Agentic AI” as the top tech trend for 2025, highlighting the growing importance of distinguishing between genuine AI agents and sophisticated automation systems.
  • Major tech companies like Salesforce, Microsoft, and Amazon have recently announced various AI agents designed to revolutionize customer service, business operations, and third-party seller support.

Defining the distinction: The key difference between AI agents and automation lies in their core capabilities and level of autonomy.

  • True AI agents can be given a goal, which they can research, reason about, make decisions on, and take action to achieve, possessing what is referred to as “full process autonomy.”
  • Automation systems, in contrast, are designed to respond to specific situations with predetermined actions based on prescribed recipes.
  • AI agents can manage entire workflows independently and improve over time through learning, while automation systems maintain consistent behavior patterns.

Identifying the masquerade: Several telltale signs can help distinguish between genuine AI agents and automation systems in disguise.

  • Systems that can only follow predefined steps and struggle with exceptions are likely to be automation rather than true AI agents.
  • Scope limitations and heavy reliance on human intervention for decision-making or course correction are indicators of limited agency.
  • True agents can research, reason, make decisions, and take action when faced with exceptions, demonstrating greater flexibility and adaptability.

The benefits of both approaches: The distinction between AI agents and automation is not necessarily problematic, as different business processes may benefit from different solutions.

  • Traditional automation, even when disguised as an agent, can be ideal for processes requiring precision, compliance, and clear audit trails.
  • Generative AI solutions excel at creative and variable tasks, while intelligent workflow systems provide a balance of automation and intelligence for complex but bounded problems.
  • Emerging agentic solutions are pushing boundaries for open-ended challenges where best practices don’t yet exist.

Choosing the right solution: Organizations must carefully consider their needs and goals when selecting between automation and AI agent solutions.

  •  Organizations must ask key questions, including aligning with the desired future of work, evaluating provider capabilities, and identifying opportunities for revenue growth through freed-up resources.
  • Transparency from vendors about their solutions’ true capabilities is crucial for making informed decisions.
  • Organizations should develop clear frameworks for evaluating and implementing these technologies, especially given Gartner’s prediction about the growing importance of agentic AI.

Looking ahead: The future of AI agents and automation in business processes is evolving rapidly, with implications for various industries and job functions.

  • Major tech players are investing heavily in the development of true AI agents, suggesting significant advancements on the horizon.
  • Organizations must stay informed about the latest developments and be prepared to adapt their strategies as the technology landscape continues to change.
  • The ability to understand and effectively implement the right mix of automation and AI agents will likely become a crucial competitive advantage in the coming years.

Broader implications: As the line between automation and AI agents becomes increasingly blurred, businesses and individuals must navigate a complex technological landscape.

  • The rise of these technologies may lead to significant changes in workforce dynamics, potentially requiring new skills and adaptations from employees across various sectors.
  • Ethical considerations surrounding the use of AI agents and automated systems, particularly in customer-facing roles, may become more prominent as these technologies become more widespread.
  • The development of truly autonomous AI agents could have far-reaching consequences for business processes, decision-making, and innovation, potentially reshaping entire industries in the coming decades.
The great AI masquerade: When automation wears an agent costume

Recent News

Grok stands alone as X restricts AI training on posts in new policy update

X explicitly bans third-party AI companies from using tweets for model training while still preserving access for its own Grok AI.

Coming out of the dark: Shadow AI usage surges in enterprise IT

IT leaders report 90% concern over unauthorized AI tools, with most organizations already suffering negative consequences including data leaks and financial losses.

Anthropic CEO opposes 10-year AI regulation ban in NYT op-ed

As AI capabilities rapidly accelerate, Anthropic's chief executive argues for targeted federal transparency standards rather than blocking state-level regulation for a decade.