Andrea Lungulescu is back at it again with this incredible post. (original post)

In his recent podcast "How AI Will Revolutionise the HR Department, in Detail" Josh Bersin presented an ambitious vision of an AI-driven end to end talent (process) approach. I am a huge fan of Josh Bersin’s work, it's only that this podcast episode prompted me to pigeonhole it.

All while knowing that he solely presents a “what could be” scenario. 

As a Principal Talent Partner, I analysed this vision considering Pedro Porto Alegre's insight that "problem-finders are just as valuable as problem-solvers".

And I found 85 problems.

This is a very deep journey into:

1. Why AI cannot replace us (yet),

2. Why it may just as well be that a real Principal Recruiter will be what it takes to win at the AI game in Recruitment,

3. How you need to train your teams.

My perspective will also be particularly relevant when examining the implications of AI in Recruitment.

The Context of Problem Finding

Before diving into Bersin's vision, I want to acknowledge Pedros's fundamental point: identifying potential issues early is crucial for any (technological) transformation. In Talent Acquisition, this means scrutinising proposed solutions before implementation, not after they've become costly mistakes.

Deep Dive

Until “what could be” turns to life (something tells me we still have a bit to go, by all accounts) I will present my review in a table format. Below each Table will be some additional ideas of mine on what can be done (on top of, obviously, solving the problems).

Each Table is Expandable and can be Downloaded.

How to read this: 

Column A - Bersin’s AI Vision - I extracted the information from the Podcast.

Column B - Problems a Principal Found - where I see the gaps in that approach. These are also things you should DO in your role (anyway).

Text Below - A Principal's Practical Approach - Here are additional things I would do as a seasoned Talent Acquisition professional.

NOTE: AI is not to be excluded, quite the opposite.

I solely make the case that some teams are so far behind, that no AI will truly be their saving grace. So let’s get the “basics” right, shall we?

Pre-Recruitment Process

Job Creation and Job Analysis

Overview: Job creation and analysis encompasses stakeholder requirements gathering, market analysis, and compensation planning. Bersin proposes AI systems to conduct interviews, analyse market data, and generate job specifications.

Challenges: Companies often lack structured data and frameworks for requirements, career paths, and compensation. Regional differences in pay transparency and inconsistent market data create additional complexity. Many organisations struggle with unrealistic role requirements and limited market perspectives.

Solutions: A combined AI-human approach strengthens the foundation of job creation. AI processes market data while recruiters validate requirements, expand market analysis, and integrate strategic priorities. This requires clear frameworks for job analysis, market benchmarking, and succession planning.

A Principal's Practical Approach

1. Review all of the above (AI + Human approach) and include them in your Job Analysis and Creation

2. Add the below

   
   

3. Requirement Development

   1. Implement structured Hiring Strategies (aka "kick-off meeting templates - gosh I hate these antiquated terms) that challenge assumptions

   2. Create frameworks for realistic requirement setting

   3. Develop a team composition analysis tool

4. Market Understanding

   1. Expand analysis across industries and locations

   2. Design bias-checking mechanisms

   3. Create or review cross-industry benchmark studies

5. Strategic Integration

   1. Establish succession planning protocols

   2. Build diversity strategy integration

   3. Develop change management frameworks

Candidate Sourcing / Finding

Overview: Candidate sourcing involves evaluating internal and external talent against location, compensation, and career progression criteria. Bersin suggests AI systems can create scored shortlists and structure interview approaches.

Challenges: Current AI systems cannot effectively assess non-traditional backgrounds or candidate potential. They miss crucial elements like motivation and cultural contribution, while often reinforcing existing hiring patterns.

Solutions: Combining AI data processing with human insight allows for comprehensive candidate evaluation. This requires clear frameworks for assessing potential, implementing inclusive sourcing strategies, and developing market intelligence systems

A Principal's Practical Approach

1. Review all of the above (AI + Human approach) and include them in your Candidate Search (Sourcing / Finding) approach

2. Add the below

3. Assessment Enhancement