.png)
At first glance, the AI agent looks solid. It promises autonomy, it integrates into your CRM, and the demo is polished. You move forward.
But months later, the cracks show.
These are the hidden costs of choosing the wrong AI agent platform — and they go far beyond the line items in a pricing sheet.
“With the success of foundational models and growing interest in autonomous systems, vendors are racing to label their products as ‘AI agents’ — often without delivering anything remotely autonomous or agentic.” — Gartner®
What looks intelligent in a demo can fall apart under production pressure. Many vendors are repackaging legacy automation tools, chatbots, or decision trees as AI agents, when in reality, they lack the architectural backbone for true autonomy.
These “agents” aren’t built to make decisions or take action. Many are built to search and retrieve information or execute simple, predefined workflows.
Most AI agents built on RAG (Retrieval-Augmented Generation) simply search through your data. When asked a question like “How do we win this deal?”, they return past snippets of similar phrases, relying on vector similarity to find matching words across emails, transcripts, and documents. It’s sophisticated search—but it’s still search.
The most impactful AI sales agent will not just search—it will think and act like a B2B veteran.
For example, Ava is powered by Agent Intelligence and a structured memory system that mirrors how a top-performing seller would operate. She captures:
Then, Ava walks her interconnected knowledge graphs to deliver strategic, context-aware recommendations—not summaries of the past, but actionable steps to win. She’s not just looking back. She’s helping you move forward.
A Gartner® key finding says “Enterprises lack a clear understanding of AI agent fail-safe mechanisms when evaluating vendor solutions, leading to significant blind spots in risk assessment.”. Here are our takeaways from their report:
“Many AI agents, especially those built on pure LLM architectures, may not be reliable enough for critical use cases.”
Hallucinations, brittle prompts, and unclear escalation paths can undermine trust, fast.
“Integration with enterprise systems and reliance on third-party LLMs can create new vulnerabilities.”
Without clear guardrails and control, AI agents can expose sensitive data or make unreviewed decisions. Thoroughly vet vendors on how they use and protect your and your customers’ data, how they manage third- and fourth-party sharing, and their broader program for governance and compliance.
“Relying on a single vendor’s platform can limit flexibility and make it hard to switch solutions.”
This becomes especially problematic if the vendor doesn’t support your domain-specific needs or innovation pace.
“AI agent platforms may lack standard protocols, limiting cross-platform collaboration.”
A siloed agent that can’t interact with other systems is just another tool — not a teammate.
“Usage-based pricing and lack of usage control may lead to higher than expected costs.”
Token-based billing, vague limits, and high customization costs can quickly exhaust budgets.
Choosing the right AI agent isn’t just about features; it’s about fitness for purpose. Gartner® advises leaders to look beyond surface-level capabilities and instead:
“Probe deeply into architecture, decision-making models, alignment safeguards, governance mechanisms and pricing models.”
This is where real costs (and potential regrets) hide. If the platform can’t explain how its agent makes decisions, manages safety, or adapts to your use cases, you’re buying a black box and assuming the risk that comes with it.
Short-term readiness doesn’t equal long-term impact. To ensure value over time:
As Gartner® notes, “Minimize uncertainty in proving business value by initially focusing on low-risk pilot use cases that deliver tangible business outcomes before committing to significant investments .”
AI agents hold enormous promise — but only when built and deployed responsibly. The cost of choosing wrong isn’t just money — it’s momentum, trust, and opportunity.
Use the Gartner® framework as your lens to assess not just what an agent claims to do, but how it operates — and whether it will scale with your team’s ambition.
Source: Gartner, Selecting an AI Agent Solution: Questions to Challenge Vendor Claims, Jim Hare, Gene Alvarez, Tom Coshow, & Deepak Seth, 12 June 2025.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved
