PA010

Higher Intelligent Automation Capability vs. Lower Implementation Cost

Business Context. Intelligent automation that combines RPA with AI and machine learning can handle far more complex tasks than rule-based RPA alone, but building and training these capabilities requires greater investment than simple bots.

Process TRIZ Resolution. Rather than building intelligent automation capability for every process, organizations should reserve AI-enhanced automation for the subset of processes where unstructured data or judgment genuinely require it, using simpler RPA for the remainder.

Applicable TRIZ Principles

Principle 3 (Local Quality) reserves intelligent automation capability for the processes that genuinely require it.

Principle 2 (Taking Out) removes AI complexity from processes that simple rule-based automation can already handle.

Principle 35 (Parameter Changes) matches automation sophistication to the actual complexity of each process.

Expected Outcome

High capability where needed

Controlled implementation cost

Efficient use of AI investment

Right-sized automation approach

Decision Indicators

AI-enhanced automation is applied to simple, rule-based tasks unnecessarily.

Implementation costs consistently exceed the value delivered.

Simple RPA candidates are over-engineered with AI capability.

No assessment determines whether AI is genuinely required before building.

Budget for intelligent automation has outpaced measurable business value.

If several of these indicators are present, the contradiction is likely active and the Process TRIZ resolution above should be evaluated.