PEX Network’s key takeaways:
- Learn the top signs your organization is truly ready to implement and scale intelligent automation (IA) effectively.
- Readiness beats hype: true IA success comes from strong processes, clean data, governance, and culture - not just technology.
- Measure to scale: track performance, justify investments with ROI, and use insights to expand automation impact.
- People first, processes next: cross functional collaboration and employee buying ensure high value use cases are automated effectively.
- Think long term: Treat IA as a continuous journey, embedding governance and process intelligence into daily operations.
Intelligent automation (IA) represents the next phase of operational excellence (OPEX). By combining robotic process automation (RPA) with artificial intelligence (AI), machine learning, process mining, and advanced analytics, IA enables organizations to automate not just repetitive tasks, but judgement-based, data driven workflows that span end-to-end processes.
When deployed effectively, intelligent automation delivers measurable benefits: reduced operational costs, faster cycle times, improved accuracy and compliance, and enhanced customer and employee experiences.
Yet despite growing investment, many organizations struggle to scale beyond pilots. Research consistently shows that readiness – not technology – is the determining factor.
Below are 10 evidence-backed signs your organization is genuinely ready to implement and scale intelligent automation!
10 signs you're ready for IA!
1. You have well defined standardized core processes
IA amplifies process performance only if the underlying processes are stable and understood.
Deloitte’s Global Intelligent Automation study found that process fragmentation is one of the tip three barriers to scaling IA, with fewer than 40 percent of organizations reporting mature, standardized process documentation.
Organizations that are ready have invested in:
- Process mapping and ownership.
- Standard operating procedures.
- Clear handoffs and exception paths.
When teams can explain why a process works the way it does, and where it breaks, IA becomes a lever rather than a risk.
2. Automation spend is increasing and justified by ROI
Readiness is reflected in sustained investment. According to Automation Anywhere’s Now & Next Report, 85 percent of executives plan to increase automation investment, and over 60 percent report achieving ROI within 12 months when automation is implemented at scale.
Orgnizations ready for IA are able to:
- Quantify time saved, cost avoided, or risk reduced.
- Compare automation initiatives using a consistent value framework.
- Reinvest savings into further automation or improvement.
3. Leadership understands the difference between RPA and IA
Organizations ready for IA understand that it is not simply “RPA plus AI.” It is an ecosystem that includes orchestration, analytics, decision intelligence, and continuous learning.
Intelligent automation is the coordination of multiple technologies to automate end-to-end processes, not individual tasks, as defined by PEX Network.
This clarity at the leadership level prevents unrealistic expectations and misaligned investments.
4. You measure performance before and after automation
Automation maturity is inseparable form measurement maturity.
Research from IBM shows that organizations using process intelligence and performance analytics alongside automation are three-times more likely to scale AI successfully.
Ready organizations track metrics such as:
- Cycle time reduction.
- Error and rework rates.
- Cost per transaction.
- SLA compliance.
Without baseline metrics, automation value cannot be objectively proven or optimized.
5. Data quality is actively managed
AI-driven automation is only as good as the data that feeds it – a phrase a majority have most likely heard a few times in recent years.
According to Gartner, poor data quality costs organizations an average of US$12.0 million per year, and remains one of the primary blockers to AI success.
Organizations ready for IA have invested in:
- Data governance frameworks.
- System integration.
- Clear data ownership.
6. Business and IT jointly design automation initiatives
IA fails when ownership is unclear. In organizations that are ready, IA is neither “owned by IT” nor “driven by the business” – it is co-created.
Deloitte research shows organizations with strong cross-functional automation governance are up to 70 percent more likely to scale IA beyond initial deployments.
These organizations establish shared decision making around:
- Process prioritization.
- Technology selection.
- Risk and compliance.
- Change management.
When automation discussions include process owners, IT architects, risk teams, and frontline workers, not just one group, scale becomes realistic.
7. Employees understand how automation will change their work
IA reshapes roles. Organizations that are ready acknowledge this openly and plan for it.
Deloitte's research shows that fear of job loss and lack of role clarity are among the top causes of automation resistance, even when technology performs well. Ready organizations invest early in:
- Clear communication about automation intent.
- Role design and skill transition planning.
- Upskilling aligned to future work.
When employees can articulate how automation will support rather than threaten their roles, adoption accelerates.
8. Process intelligence is already guiding decision making
Organizations ready for intelligent automation do not rely on assumptions about how processes run - they use process intelligence.
Gartner identifies process mining as a key enabler of “hyperautomation,” enabling organizations to identify automation opportunities, quantify impact, and validate outcomes.
Process mining is the bridge between process excellence and intelligent automation allowing teams to see where automation will genuinely improve outcomes rather than automate inefficiency. When automation candidates are selected based on execution data, not intuition, intelligent automation delivers far greater value.
9. Automation value is visible across multiple functions
Organizations that are ready for IA no longer see automation as a back office tool.
McKinsey research shows that companies achieving the highest automation value deploy it across operations, finance, HR, IT, and customer facing processes, rather than in functional siloes.
When automation success stories emerge from multiple functions, IA becomes an enterprise capability rather than a niche solution.
10. Intelligent automation is treated as a long term capability, not a project
The final (and perhaps most telling) sign of readiness is mindset. Organizations ready for IA do not ask “when will automation be finished?” They ask “how do we continuously improve and scale it?
PEX Network’s Global State of Business Transformation report shows high-performing organizations embed automation, analytics, and continuous improvement into their operating model, treating transformation as an ongoing discipline.
AIMultiple analysis further shows that organizations capturing the most value from IA realize multiple benefits simultaneously – including cost reduction, time savings, improved accuracy, and compliance – because automation is sustained over time.
When IA is planned as a multi-year journey with evolving goals, it delivers durable competitive advantage.
Watch this case study session to learn how you can leverage automation to streamline processes, reduce manual errors, and empower employees to focus on high-value tasks.