Common Challenges in Implementing IPA
Intelligent process automation can deliver capture and handle strong results — but getting there takes more than just technical capability.
Most obstacles come from how organizations special lead structure their processes, assign responsibility, and align automation with outcomes.
Poor process and data readiness
Automation works best when processes are consistent. But in many organizations, workflows are undocumented or handled differently across teams. Data often lives in disconnected systems or varies in format, making it hard to build stable automation.
Before introducing intelligent process automation, take time to map how the process currently works. Document the inputs, known exceptions, tool the future of work and artificial intelligence dependencies, and points where human intervention is still required.
Overcomplicating initial implementations
Teams often try to automate too much, too soon. When the initial rollout spans several systems or includes edge cases from the beginning, it increases the chance of delays or failure to launch.
Instead, start with a single process that has one clear decision point and a measurable output. Prove value early by keeping the scope focused.
Lack of clear ownership or long-term vision
Intelligent process automation systems are capture and handle adaptive and evolving projects. Without a team or person responsible for performance, logic, and maintenance, the system often becomes outdated or misaligned.
Assign ongoing ownership from the start. Someone needs to track how the automation performs, what breaks, and where adjustments are needed.
Misalignment between business goals and automation logic
Not every process is worth automating — and not whatsapp filter every automation drives value. Sometimes the logic reflects what’s technically possible, but not what the business actually requires.
To avoid that, design workflows in collaboration with the people who use them. That includes support teams, ops leads, and product owners.
When automation aligns with real needs, it’s capture and handle far more likely to deliver lasting results.
Before introducing intelligent process automation, take time to map how the process currently works. Document the inputs, known exceptions, tool dependencies, and points where human intervention is still required.