Yes - but not everything, and not unsupervised. AI agents can genuinely automate whole workflows today, provided the work is repetitive, spans a few systems, and has outcomes you can check. The mistake is expecting them to run the business; the win is letting them run the errands.
Workflows agents handle well now
- Invoice and payment chasing - reading records, drafting reminders, escalating overdue accounts
- Support triage - reading tickets, answering common ones, routing the rest to the right person
- Data reconciliation - keeping the same information consistent across systems
- Research and monitoring - gathering information from many sources into one summary
- Onboarding admin - creating accounts, sending documents, chasing missing details
These share a pattern: clear steps, frequent repetition, and a result a human can verify at a glance.
Where they still struggle
Agents wobble when a task needs deep context they were never given, when the "right" answer is a matter of judgement, or when an error is expensive to reverse. Negotiating a contract, making a hiring call, approving a large payment - these stay human. The realistic model is an agent doing 80% of a workflow and handing the tricky 20% to a person.
Start with one workflow, not ten
The businesses that succeed pick a single, well-understood process, automate it end to end, measure the result, then expand. Our guide to running a small agentic AI pilot walks through exactly that. Trying to automate everything at once is the fastest route to a stalled project.
The bottom line
If you want to build and govern an AI agent yourself, the Generative & Agentic AI for Business Leaders executive certificate takes you from use case to a working no-code agent.
AI agents can automate real workflows today - the constraint is choosing the right ones and keeping a human on the results. Learning to spot automatable work and scope it safely is central to the applied AI for business course at London School of Business UK. Enquire today.