2. Insurance leads the way in adoption
The insurance industry is at the forefront, with 91% of surveyed insurance businesses actively involved in planning intelligent automation projects. Financial services, healthcare and government sectors aren't far behind, displaying widespread adoption across industries.
3. Data quality is a make-or-break factor
Deep Analysis found 83% of organizations have been forced to exclude at least one data source from intelligent automation projects due to poor quality, highlighting the necessity of clean and usable data for successful outcomes. Among these, CRM and ERP systems emerged as the most critical data sources.
4. AI projects are proving effective
Early adopters are seeing results, with 88% of AI projects meeting or exceeding targets. These businesses report significant progress in automating tasks and improving decision-making processes, demonstrating AI’s growing role in operational success.
5. Automation is about data, not just labor shortages
Contrary to popular beliefs, only 10% of organizations cited labor shortages as a primary reason for adopting automation. Instead, efforts are focused on improving data quality (63%) and access to knowledge/data (58%) — a clear signal that organizations are prioritizing smarter data strategies.
6. IT dominates automation efforts
Projects tend to be IT-led and IT-centered, with 75% of initiatives directed toward improving IT capabilities. However, the benefits often extend beyond IT, enhancing customer support, finance and back-office operations.