To AI or to Automate? So be the question!...or, as the co-pioneer of BPR, Michael Hammer quoted: "Don’t Automate, Obliterate!"
I am fascinated by AI and spending time getting my head around it – GREAT podcast recently hosted by Staffing Industry Titan, Suky Sodhi Sodhi and Cartwheel’s Laura Boivin . How to use A.I. and Automation in the Staffing Industry
Food for thought:
While automation focuses on executing repetitive, rule-based tasks to save time, AI adds intelligence to processes, enabling predictive analysis, adaptive learning, and decision-making. Together, they can complement each other in the staffing industry by handling both mundane tasks and strategic functions, transforming recruitment workflows. However, could we be using technology to either “AI and/or Automate,” as an excuse, as we're not truly in touch to know if we have poorly trained and/or led or incompetent team members and/or leaders or simply have great people in the wrong roles?
More on a granular level:
But here’s the kicker for me - it can/should/does play an integral part (fast – effective – efficient – positive experience for all parties) in moving the Applicant to Candidate in the way I’ve outlined above - BUT does it?
I’d be interested to hear from folks who have applied as Applicants to a role and have interfaced with AI during the process – how have you found it? Pro’s and Con’s?
Below find my musings post digesting and allowing the great podcast to marinade:
1. Definition and Scope
AI:
AI involves the use of machine learning, natural language processing, and algorithms to simulate human intelligence. It learns and improves over time to perform complex tasks, make decisions, and predict outcomes.
Example in staffing: AI tools can analyse resumes, predict candidate success, and recommend the best talent for specific roles.
Automation:
Automation refers to the use of software or robotic processes to perform repetitive, rule-based tasks without human intervention. It follows predefined workflows but does not learn or adapt.
Example in staffing: Automation tools can send follow-up emails, schedule interviews, or update records in applicant tracking systems (ATS).
2. Functionality
AI:
Can interpret and analyse unstructured data (e.g., resumes, job descriptions, or interview videos).
Provides insights and recommendations, like suggesting the best candidates based on historical hiring data.
Learns from user behaviour, adapts, and improves outcomes over time (e.g., learning which skills are most critical for a job).
Automation:
Executes straightforward, repetitive tasks based on set rules.
Focuses on increasing efficiency and reducing human error in routine tasks.
Does not adapt or learn from data; it requires manual updates to workflows.
3. Examples in the Staffing Industry
AI in Staffing:
Resume Parsing and Analysis: AI can read and analyse resumes, identifying key skills and qualifications that match job descriptions.
Candidate Matching: AI matches candidates to job openings by analysing compatibility based on skills, experience, and cultural fit.
Chatbots: AI-powered bots can engage candidates in real-time, answering questions and guiding them through the application process.
Predictive Analytics: AI can predict hiring trends or the likelihood of a candidate’s success in a role.
Automation in Staffing:
Application Tracking: Automating the tracking of candidate progress in the recruitment pipeline.
Interview Scheduling: Automatically coordinating times between candidates and interviewers.
Email Campaigns: Sending mass emails to candidates or clients with predefined templates.
Document Management: Automatically organising and storing resumes, offer letters, or contracts.
4. Levels of Complexity
AI:
High complexity; requires significant initial setup, training data, and fine-tuning.
Can handle nuanced tasks, such as detecting soft skills through video interview analysis but can it really?
Automation:
Low to medium complexity; often straightforward to implement with predefined rules.
Handles simple, repetitive tasks like processing applications or generating standard reports.
5. Strategic Role
AI:
AI supports strategic decision-making by providing actionable insights and enhancing candidate or client experiences. It focuses on improving the quality of hires and streamlining complex workflows.
Automation:
Automation reduces administrative burdens, allowing recruiters to focus more on strategic tasks like relationship building and interviewing. Its primary role is to improve efficiency.
Key Takeaway:
While automation focuses on executing repetitive, rule-based tasks to save time, AI adds intelligence to processes, enabling predictive analysis, adaptive learning, and decision-making. Together, they can complement each other in the staffing industry by handling both mundane tasks and strategic functions, transforming recruitment workflows. However, are we truly in touch of what's going on with our people in the business....
MC
