Though the terms are often used together, there’s actually a sharp line between automation and true autonomy. Automation can help execute a task, but autonomy has to understand intent and act without constant human direction. That’s why Level 5 autonomy remains such a high bar — and why even Level 4 is still a stretch beyond narrow use cases, Ericsson exec Anders Vestergren tells Fierce.
The biggest roadblock, he argues, isn’t necessarily the AI, data management, security or activation tooling. It’s trust: operators need confidence that algorithms will do what they are supposed to do before humans can step out of the loop.
Ericsson’s Krishna Prasad Kalluri also dives into the edge compute question. While physical AI applications such as robots and smart city systems could create new demand for distributed inferencing, the operator sweet spot is still being tested. Some workloads may need device-level processing, others may be fine in regional data centers, and only certain use cases will justify compute at the cell site.
Get all the details from Fierce’s conversation with Ericsson in the video above. And check out additional content from our extended interview with Hofmeyr in these stories:
Telco automation and autonomy are not the same thing
Telcos find AI’s next big use case: energy management
Read and watch all of our coverage from DTW Ignite 2026 right here.