By Srividya Kannan
The enterprise software landscape is transforming rapidly with the rise of artificial intelligence (AI). Companies, from tech giants to startups, use buzzwords like “intelligent agents” and “autonomous systems” to market their offerings. However, many of these so-called AI products are just traditional automation tools rebranded to ride the AI hype.
This misrepresentation, often referred to as “agent washing,” poses significant challenges for enterprises. By overstating basic automation as advanced AI, some companies mislead customers, erode trust, and slow innovation. For businesses, identifying real AI tools and avoiding hype is key to smarter investments.
What is agent washing?
Similar to “greenwashing,” where companies exaggerate environmental claims, agent washing is when businesses misrepresent products as intelligent, autonomous AI systems. These tools may provide rule-based outputs but lack the adaptability of true AI.
Why is this so common? The global AI boom has increased investment and demand, making “AI-powered” a buzzword. By branding basic automation as advanced AI, companies seek attention – often at the cost of customer trust and ethics.
Identifying genuine agentic AI
To spot agent washing, businesses first need to understand what distinguishes true agentic AI from traditional automation. Key characteristics of agentic AI:
Autonomy: The system functions independently, learning and improving without the need for constant external input.
Purpose-driven behaviour: Agentic AI performs tasks aligned with meaningful goals, rather than just executing isolated commands.
Contextual awareness: These systems adapt to external conditions in real time, making decisions based on complex, dynamic contexts.
Examples of agentic AI solutions include self-driving cars that make nuanced decisions based on traffic and weather, or advanced virtual assistants that manage schedules while considering urgency and location.
Red flags to watch for
When evaluating so-called AI solutions, keep an eye out for these telltale signs of agent washing:
Buzzwords without substance: Be wary of terminology like “self-aware” or “autonomous” if no documentation or proof supports those claims.
Static outputs: Systems presenting standard, unchanging outputs rather than learning and adapting to new inputs are likely just automation tools.
Lack of transparency: If companies don’t disclose how their AI works or require human intervention to function, approach with caution.
No proof of adaptability: True agentic AI evolves. Solutions that remain static or follow rigid algorithms fail to qualify.
Agent washing wastes resources, erodes trust, and distorts AI markets.
How to spot genuine AI
Meaningful AI capabilities could be differentiated from hollow marketing hype using this criteria:
Functionality: Does the tool demonstrate autonomy in decision-making?
Learning capabilities: Can the system evolve based on user behavior or environmental inputs?
Transparency: Are the AI’s functions, algorithms, and limitations clearly outlined?
Performance: Does it adapt to scenarios dynamically or simply deliver repetitive, rule-based outputs?
Third-party validation: Are there objective case studies or reviews to back the system’s claimed capabilities?
Choosing smarter AI investments
The promise of agentic AI is genuine, but enterprises must critically evaluate the tools they adopt. By recognising red flags, analysing AI capabilities, and setting clear organisational objectives, businesses can make smarter, future-proof investments. The ability to discern true innovation from marketing exaggeration is no longer optional; it is a competitive edge in the rapidly evolving AI-driven marketplace.
With informed decision-making, your organisation can avoid the pitfalls of agent washing and instead lay the groundwork for meaningful technological transformation.
The writer is founder and CEO, Avaali
