Automation + AI : Organizational Buy-in and Talent Management
Description:
Intelligent Automation tools can impact back-office processes that are often within scope of Shared Services, and every other process of the enterprise, including centralized or decentralized front-office work processes. With tools often differing based on the use, how (or should) companies coordinate Intelligent Automation initiatives in different parts of the company?
In addition, the topic of talent when it comes to the larger Artificial Intelligence spectrum – RPA as well as IPA, Machine Learning, Virtual Agents, etc., will be addressed.
Peercast Poll Results
Poll Title: Identifying, Sourcing, and Retaining Intelligent Automation (RPA, AI, etc.) Talent
Background: We have all heard the stories of the chaos that exists in the Bay Area and Silicon Valley as high growth technology companies compete for a limited number of talented software engineers. This poll looks at sourcing for Intelligent Automation talent and ways to retain these important individuals.
Poll Question: What has been your main source of talent for Intelligent Automation (RPA, AI, etc.) staff at your company?
| Internal resources, giving them additional training as needed | 55% | |
| University hires with prior experience | 0% | |
| University hires with little prior experience | 0% | |
| Recruiting from consulting firms | 0% | |
| Recruiting from other companies | 0% | |
| All or most of the above; where ever we can find them | 24% | |
| We have not done too much hiring for Intelligent Automation yet | 21% |
Poll Question: What have you found to be the best retention tool for Intelligent Automation staff at your company?
| Challenging, important assignments where they can make a difference | 41% | |
| Salary / benefits / incentives offered | 7% | |
| Overall company culture | 7% | |
| Access to ongoing training and skill development in their field | 0% | |
| Access to high level management / high level support | 0% | |
| Other (please comment) | 3% | |
| We do not have enough experience to know yet | 41% |