AI agents and failing projects
Nearly half of all AI agent projects are set to fail (as Gartner predicts here). Why? Unclear business value, inadequate risk controls, and escalating costs.
As I see it, much of this is fueled by hype, leading to existing solutions being relabeled as “Agentic AI” without any rethinking of business processes.
Human creativity is missing in this picture. It’s this creative thinking that should move agent use beyond just automating or augmenting individual tasks with LLMs, leading instead to the redesign of business processes and a vision for how humans and AI can truly complement each other.
The risks and costs are more straightforward to resolve:
– Managers who are most excited about AI agents often do not fully understand the risks and limitations of LLMs. They should invest as much in understanding these models as they do in using them.
– The true cost of scaling proof-of-concept GenAI solutions is often underestimated. This is on selecting the right vendor. Gartner estimates only about 130 of the thousands of agentic AI vendors are real.