Latest / Edan Haddock - Total Talent / No More With Less: The Productivity Rebellion in Talent Acquisition

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No More With Less: The Productivity Rebellion in Talent Acquisition · Edan Haddock - Total Talent

• 0:51
  SPEAKER_00: Welcome back, Rockstars.
• 0:54
  SPEAKER_00: This is Eden Haddock, Total Talent, where we rip up the old playbook and rewrite what it means to win in talent.
• 1:05
  SPEAKER_00: Today's episode is going to be a statement.
• 1:09
  SPEAKER_00: A rebellion against the worn out narrative that TA leaders in twenty twenty five must do more with less.
• 1:19
  SPEAKER_00: That phrase it's dying.
• 1:24
  SPEAKER_00: And it's about time.
• 1:27
  SPEAKER_00: The real war right now is productivity, not busyness.
• 1:34
  SPEAKER_00: Working smarter, not harder.
• 1:39
  SPEAKER_00: And the future belongs to talent leaders who treat technology, data, and automation as co-pilots, not threats.
• 1:51
  SPEAKER_00: For this episode, I'm going to take you through why do more with less is a myth you must bust now.
• 2:03
  SPEAKER_00: The modern TA technology stack, AI agents, smarter HIRS or HRMS, integrated systems, the rise of talent advisory, and how total talent is the only game in town.
• 2:23
  SPEAKER_00: A provocative take, strategy itself is being automated.
• 2:28
  SPEAKER_00: And what that means for TA leaders.
• 2:32
  SPEAKER_00: A call to arms.
• 2:47
  SPEAKER_00: And where the edge truly lies.
• 2:50
  SPEAKER_00: So strap in because this is going to get bold, edgy, and of course, unapologetic.
• 3:01
  SPEAKER_00: The myth of do more with less.
• 3:04
  SPEAKER_00: Why it's dead.
• 3:08
  SPEAKER_00: Let's start by tearing down the myth.
• 3:13
  SPEAKER_00: For years, talent acquisition leaders have been saddled with the expectation squeeze more out of the same headcount.
• 3:25
  SPEAKER_00: Hire more with fewer resources.
• 3:29
  SPEAKER_00: Stretch budgets to the breaking point.
• 3:32
  SPEAKER_00: But I say that model is broken.
• 3:37
  SPEAKER_00: Why is it broken?
• 3:39
  SPEAKER_00: Number one, diminishing returns.
• 3:44
  SPEAKER_00: Piling more tasks on a stressed-out team doesn't scale.
• 3:50
  SPEAKER_00: You have burnout, turnover, and lowered quality.
• 3:56
  SPEAKER_00: Number two.
• 3:58
  SPEAKER_00: Complexity today demands focus, not volume.
• 4:04
  SPEAKER_00: We're sourcing across global markets.
• 4:07
  SPEAKER_00: We're building candidate experiences.
• 4:10
  SPEAKER_00: We're maintaining data integrity, compliance, diversity, inclusion, and equity.
• 4:18
  SPEAKER_00: Employer branding, right?
• 4:21
  SPEAKER_00: These are no longer side projects, they are central.
• 4:26
  SPEAKER_00: Number three, you're fighting the wrong fight.
• 4:31
  SPEAKER_00: Doing more is a distraction.
• 4:36
  SPEAKER_00: What matters more, and what really matters, is doing more of what works and then automatically managing the rest.
• 4:49
  SPEAKER_00: Number four.
• 4:52
  SPEAKER_00: Your competition isn't doing less, and we all have it.
• 4:55
  SPEAKER_00: They're doing smarter.
• 4:58
  SPEAKER_00: The teams that will win will be the ones who adopt next gen productivity, not those who fumble with old spreadsheets and manual handoffs.
• 5:12
  SPEAKER_00: I'm not normally Mr.
• 5:13
  SPEAKER_00: Highbrow, and I'll never claim to be, and I'm not here, but there is supporting data and research on this.
• 5:20
  SPEAKER_00: I recently read a Deloitte article on 2025 talent acquisition tech trends, and it argues that AI and agent-powered recruiting will shift recruiting from a manual to a semi-autonomous model, freeing talent acquisition teams to focus on value, not volume.
• 5:48
  SPEAKER_00: I found some recent research in Science Direct called From Automation to Augmentation: Human Resources Journey with AI.
• 5:58
  SPEAKER_00: And it suggests that maturity in AI adoption can optimize HR decision making, improving both efficiency and employee engagement.
• 6:11
  SPEAKER_00: Then we have our HR automation strategy guides.
• 6:15
  SPEAKER_00: And for example, Hi Bob's 2025 playbook.
• 6:19
  SPEAKER_00: And that's where we see best practices.
• 6:22
  SPEAKER_00: Automate high frequency, low judgment tasks to free human time for creative work.
• 6:33
  SPEAKER_00: So the first truth I want you to own: you don't have to do more with less.
• 6:41
  SPEAKER_00: You have to leverage more with less effort.
• 6:45
  SPEAKER_00: Productivity comes from leverage, systems, agents, automation, and data.
• 6:56
  SPEAKER_00: Let me give you a metaphor.
• 6:58
  SPEAKER_00: Suppose you're in a rock band.
• 7:01
  SPEAKER_00: You could ask your drummer to play twice as fast, your bassist to cover two parts, your singer to also play guitar, or just to compensate for missing members.
• 7:14
  SPEAKER_00: Or you could bring in a synthesizer, backing tracks, intelligent sound mixing.
• 7:22
  SPEAKER_00: You leverage your tools.
• 7:27
  SPEAKER_00: That's how modern TA must work.
• 7:33
  SPEAKER_00: The modern technology stack, where real leverage lives.
• 7:39
  SPEAKER_00: Here's where the rubber meets the road.
• 7:43
  SPEAKER_00: If you're still approaching tech as a cost center, it's time to pivot.
• 7:50
  SPEAKER_00: Tech is your amplifier, your distortion pedal, your secret source.
• 7:59
  SPEAKER_00: Let me walk you through the key components of a future-proof talent acquisition or total talent stack.
• 8:07
  SPEAKER_00: Number one, AI agents and agentic systems.
• 8:15
  SPEAKER_00: I'm not talking about chatbots.
• 8:17
  SPEAKER_00: They're not chatbots.
• 8:19
  SPEAKER_00: These are mini recruiters you can deploy.
• 8:25
  SPEAKER_00: Deloitte's trend research points to agent-powered recruiting as a core shift.
• 8:31
  SPEAKER_00: AI agents that can autonomously manage parts of the recruiting process with minimal human intervention.
• 8:42
  SPEAKER_00: For example, a recent paper which is titled AI Hiring with LLMs, a context-aware and explainable multi-agent framework for resume screening.
• 8:56
  SPEAKER_00: This research proposes that dividing screening tasks into multiple agents, extractor, evaluator, summarizer, etc.
• 9:09
  SPEAKER_00: Connected by a rag, the result, a system that evaluates resumes contextually with explainability.
• 9:20
  SPEAKER_00: These agents can parse resumes, score relevance, help surface best matches, flag bias, and then generate summaries for recruiters.
• 9:33
  SPEAKER_00: Number two, smarter HRIS or human capital management, those platforms.
• 9:44
  SPEAKER_00: Your HR system is no longer a record-keeping hack.
• 9:48
  SPEAKER_00: It's your data hub, your automation engine, your insight engine.
• 9:57
  SPEAKER_00: The integration of AI into core HR platforms is becoming standard.
• 10:06
  SPEAKER_00: According to AIHR, AI tools are being embedded in applicant tracking, onboarding, learning systems, and analytics dashboards, reducing friction and creating unified experiences.
• 10:26
  SPEAKER_00: Another recent study, artificial intelligence in talent acquisition, this is quoted from Emerald, and it highlights that AI is not just reworking TA processes.
• 10:41
  SPEAKER_00: It actually shapes or reshapes how organizations are structurally designed.
• 10:49
  SPEAKER_00: The HR automation for outcome-led HR framework from Workday, it's a really useful blueprint.
• 10:57
  SPEAKER_00: Automate simpler processes first.
• 11:00
  SPEAKER_00: So things like payroll, onboarding, requests, and then you expand into attraction, deployment, analytics, and naturally transformation.
• 11:15
  SPEAKER_00: Number three, data and analytics, decision automation.
• 11:23
  SPEAKER_00: Data is your amplifier's knob.
• 11:26
  SPEAKER_00: It tunes everything.
• 11:29
  SPEAKER_00: The field is shifting from descriptive reports, what happened, to predictive and prescriptive systems.
• 11:38
  SPEAKER_00: What should we do next?
• 11:42
  SPEAKER_00: Research in using automation to build an outcome-led HR organization shows that HR functions mature when they shift into measurement, insight, and agility via automation.
• 11:57
  SPEAKER_00: That again is quoted from Workday.
• 12:02
  SPEAKER_00: A review paper on AI and automation in HR titled AI and HR from the Human Resource Journal describes how AI plus automation reduce human error, increase speed, and let HR focus on creative and strategic tasks.
• 12:23
  SPEAKER_00: A big point here.
• 12:26
  SPEAKER_00: Strategy can now be embedded in systems.
• 12:29
  SPEAKER_00: More on that later.
• 12:32
  SPEAKER_00: Number four, talent life cycle automation, so beyond acquisition.
• 12:39
  SPEAKER_00: We still tend to talk about TA in isolation.
• 12:43
  SPEAKER_00: But the real magic is automating across onboarding, internal mobility, performance, LD, retention, and engagement.
• 12:57
  SPEAKER_00: A paper titled From Recruitment to Retention, AI Tools for Human Resource, explores the full employee life cycle.
• 13:08
  SPEAKER_00: So recruitment, onboarding, retention, and shows how AI tools are driving scaling, customization, and predictive interventions.
• 13:23
  SPEAKER_00: In research on AI and HR management, the trends suggest convergence.
• 13:29
  SPEAKER_00: Talent acquisition, performance, learning, engagement all become nodes in interconnected systems.
• 13:39
  SPEAKER_00: Number five, ethics, oversight, and human in the loop.
• 13:46
  SPEAKER_00: Automation doesn't mean set and forget.
• 13:50
  SPEAKER_00: You ride the pedal, but you're still the driver.
• 13:56
  SPEAKER_00: Issues of bias, transparency, data privacy, and fairness are non-negotiable.
• 14:05
  SPEAKER_00: The employee well-being in the age of AI paper warns that if employees feel systems are unfair, then trust collapses.
• 14:16
  SPEAKER_00: There's got to be that trust there.
• 14:20
  SPEAKER_00: There's also the danger of automation bias.
• 14:24
  SPEAKER_00: The tendency to over-rely on machine and machine suggestions, even when they're flawed.
• 14:34
  SPEAKER_00: And then there's the ironies of automation.
• 14:37
  SPEAKER_00: When you automate everything, humans become passive monitors, losing skills and situational readiness.
• 14:47
  SPEAKER_00: But truly, make no mistake, the future lies with those who command the tech.
• 14:58
  SPEAKER_00: Total talent and talent advisory.
• 15:01
  SPEAKER_00: This is where things get spicy.
• 15:05
  SPEAKER_00: In twenty twenty-five, TA is no longer isolated.
• 15:11
  SPEAKER_00: It melds into total talent.
• 15:15
  SPEAKER_00: That means talent acquisition, talent management, employee experience, people development, all under one umbrella.
• 15:28
  SPEAKER_00: So why the shift?
• 15:32
  SPEAKER_00: Because talent doesn't come into an organization at higher date and leave at exit date.
• 15:38
  SPEAKER_00: Talent is a continuum.
• 15:42
  SPEAKER_00: You need to think how do I attract, deploy, retain, develop, evolve the workforce.
• 15:53
  SPEAKER_00: Internal, external, contingent.
• 15:58
  SPEAKER_00: As a unified architecture.
• 16:02
  SPEAKER_00: So here's how I break it down.
• 16:04
  SPEAKER_00: Number one, talent advisory.
• 16:09
  SPEAKER_00: The TA leader can no longer be a back office executor.
• 16:14
  SPEAKER_00: You have to be the talent advisor to the business.
• 16:19
  SPEAKER_00: That means you translate business goals into talent strategy, future skills, scenario modeling, workforce supply and demand, agility.
• 16:35
  SPEAKER_00: But here's the provocative twist.
• 16:38
  SPEAKER_00: That advisory role is increasingly partially automatable.
• 16:45
  SPEAKER_00: You'll see that in the next segment.
• 16:48
  SPEAKER_00: Number two, integration across silos.
• 16:54
  SPEAKER_00: Imagine your recruiting team being disconnected from LD, performance, mobility.
• 17:00
  SPEAKER_00: That's just so inefficient.
• 17:04
  SPEAKER_00: Total talent demands you stitch together the data and interventions across the life cycle.
• 17:12
  SPEAKER_00: For example, if your TA system passes candidate data to onboarding, LMS, performance systems, seamless flow, minimal redundancy.
• 17:29
  SPEAKER_00: Number three, employee experience and internal mobility as feeders.
• 17:37
  SPEAKER_00: Many of your future hires should come from within.
• 17:41
  SPEAKER_00: Your role is to build internal pipelines, redeploy talent, scaffold career paths.
• 17:50
  SPEAKER_00: Automation helps here.
• 17:53
  SPEAKER_00: Matching internal competencies to projects, flagging gaps, suggesting rotations, providing micro learning.
• 18:06
  SPEAKER_00: Your HRIS, LMS, TA stack should help unlock talent mobility dynamically.
• 18:16
  SPEAKER_00: Number four, people development and learning systems.
• 18:21
  SPEAKER_00: Training, coaching, upskilling.
• 18:25
  SPEAKER_00: These are not side functions.
• 18:28
  SPEAKER_00: They're integral to keeping your talent alive.
• 18:33
  SPEAKER_00: Generative AI is now making inroads here.
• 18:37
  SPEAKER_00: A recent review titled A Review on Generative AI Powered Talent Management discusses how generative models can dynamically create curricula, tailor learning paths, and support engagement.
• 18:55
  SPEAKER_00: Number five, talent analytics and insights as the backbone.
• 19:02
  SPEAKER_00: In a total talent system, data from acquisition, performance, learning, attrition, mobility all feed into unified dashboards.
• 19:17
  SPEAKER_00: You get to run scenario models, simulations, what if projections, and guide business decisions.
• 19:28
  SPEAKER_00: A review, data-driven decision making and human resources to optimize talent.
• 19:34
  SPEAKER_00: This review outlines how data analytics optimizes acquisition and retention strategies.
• 19:41
  SPEAKER_00: So a bold declaration here.
• 19:45
  SPEAKER_00: By 2027, if your TA leader still thinks my job is hiring, recruiting, and pipeline, you're about to get left behind.
• 19:59
  SPEAKER_00: The future demands advisor executor hybrids who operate systems, drive interventions, and build talent architecture.
• 20:14
  SPEAKER_00: Strategy is being automated and what that means for leaders.
• 20:21
  SPEAKER_00: This is the part that will ruffle feathers.
• 20:25
  SPEAKER_00: I'm going to argue that strategy itself is becoming automatable.
• 20:33
  SPEAKER_00: And if you cling solely to strategy as your domain, you'll get displaced.
• 20:40
  SPEAKER_00: Yes, I know that sounds extreme, but the signs are there.
• 20:47
  SPEAKER_00: And here's how.
• 20:51
  SPEAKER_00: Systems can now infer strategy based on constraints, data, and outcomes.
• 20:57
  SPEAKER_00: Let me show you with a path.
• 21:01
  SPEAKER_00: You feed the system business goals, for example, growth in region X or lowering attrition in function Y, the skill ramp in Z.
• 21:13
  SPEAKER_00: The system ingests talent supply, cost, historical metrics, hiring pipeline, learning data, attrition models.
• 21:25
  SPEAKER_00: The system then suggests interventions.
• 21:29
  SPEAKER_00: Upskill versus hire versus redeploy versus outsource, balance by cost, risk, and lead time.
• 21:40
  SPEAKER_00: It runs scenarios, projects outcomes, and optimizes a plan.
• 21:48
  SPEAKER_00: All with minimal human input.
• 21:52
  SPEAKER_00: Once this is possible, what is the role of the strategy person?
• 21:59
  SPEAKER_00: Less ideation from scratch, more steering, validating, refining.
• 22:07
  SPEAKER_00: Ultimately, you become the curator, the optimizer, the context setter.
• 22:15
  SPEAKER_00: The human's domain becomes in the tools, not beyond them.
• 22:22
  SPEAKER_00: And already parts of strategy are creeping into algorithms.
• 22:28
  SPEAKER_00: Algorithmic management theory used in HR research describes how HR functions will lean into algorithms that do the managerial level decisions.
• 22:41
  SPEAKER_00: In TA, generating forecasts, modeling attrition, designing talent plans.
• 22:51
  SPEAKER_00: These are all domains where AI data models are being embedded.
• 22:57
  SPEAKER_00: Let's be clear.
• 23:00
  SPEAKER_00: I'm not claiming humans are obsolete.
• 23:04
  SPEAKER_00: But the locus of power is shifting from those who think strategy to those who build, operate, and fine-tune strategy systems.
• 23:17
  SPEAKER_00: If you're a leader who says, I only do strategy, leave execution to others, you're in danger.
• 23:25
  SPEAKER_00: Because what if strategy is no longer purely human?
• 23:31
  SPEAKER_00: So your value will pivot to being fluent in AI, data systems, shaping the narrative, values, constraints, designing the feedback loops, leading execution, not just dictating it.
• 23:51
  SPEAKER_00: And being the human guardrail when systems fail, when ethics matter, when markets shift.
• 24:04
  SPEAKER_00: So the edgy are called.
• 24:07
  SPEAKER_00: Your new domain is tools plus delivery.
• 24:13
  SPEAKER_00: Strategy is the substrate, not the prize.
• 24:20
  SPEAKER_00: So some practical steps and playbooks.
• 24:22
  SPEAKER_00: How to shift from doing more to doing smarter.
• 24:28
  SPEAKER_00: Enough theory, right?
• 24:29
  SPEAKER_00: It's not very many, is it?
• 24:31
  SPEAKER_00: So time for some actionable moves.
• 24:35
  SPEAKER_00: Here's your playbook to dismantle, do more with less.
• 24:38
  SPEAKER_00: And to build a smarter TA total talent engine.
• 24:43
  SPEAKER_00: Step one: audit ruthlessly.
• 24:48
  SPEAKER_00: Inventory all talent acquisition human resource tasks.
• 24:53
  SPEAKER_00: Label them either high value, which is judgment, influence, relationship, versus low value.
• 25:01
  SPEAKER_00: Data entry, scheduling, passing.
• 25:07
  SPEAKER_00: Ask.
• 25:09
  SPEAKER_00: Which ones must remain human?
• 25:13
  SPEAKER_00: Which ones can be automated, delegated, augmented.
• 25:22
  SPEAKER_00: Use the HR Automation Self-Assessment Frameworks.
• 25:26
  SPEAKER_00: And Workdays model is a good reference, to be honest.
• 25:30
  SPEAKER_00: Use the workday model to rate maturity against processes like attraction, retention, and insights.
• 25:39
  SPEAKER_00: Step two.
• 25:42
  SPEAKER_00: Start small and scale smart.
• 25:47
  SPEAKER_00: Begin automating a few high-volume, repetitive subtasks in recruitment.
• 25:54
  SPEAKER_00: So whether that's resume screening, candidate triage, interview scheduling is a big one and an easy one.
• 26:03
  SPEAKER_00: Use AI agents or workflow bots as assistive tools first.
• 26:09
  SPEAKER_00: Keep humans in the loop.
• 26:12
  SPEAKER_00: Collect the feedback, measure error, and adjust the thresholds.
• 26:20
  SPEAKER_00: Step three, connect your systems, right?
• 26:24
  SPEAKER_00: Make your ATS, HRIS, LMS, performance engagement systems talk to each other.
• 26:33
  SPEAKER_00: Build shared data models.
• 26:37
  SPEAKER_00: Use integration and pipeline automation to erase manual handoffs.
• 26:45
  SPEAKER_00: Step four.
• 26:48
  SPEAKER_00: Embed analytics and prediction.
• 26:52
  SPEAKER_00: Shift from reporting what happened to predicting what could happen.
• 26:59
  SPEAKER_00: Use talent and attrition models.
• 27:03
  SPEAKER_00: So this is supply-demand planning.
• 27:06
  SPEAKER_00: What if scenario engines?
• 27:10
  SPEAKER_00: Let insights drive interventions.
• 27:12
  SPEAKER_00: For example, when attrition risk is high, trigger deployment or mobility nudges.
• 27:23
  SPEAKER_00: Step five.
• 27:25
  SPEAKER_00: Transition the team mindset.
• 27:29
  SPEAKER_00: Upskill your team.
• 27:31
  SPEAKER_00: Invest in data fluency, AI literacy, and systems thinking.
• 27:38
  SPEAKER_00: It's a culture shift.
• 27:42
  SPEAKER_00: Reward leveraging your tech, not brute force hours.
• 27:49
  SPEAKER_00: Redistribute roles.
• 27:52
  SPEAKER_00: Some become agent managers, analytics curators, platform integrators.
• 28:01
  SPEAKER_00: Step six.
• 28:03
  SPEAKER_00: Guardrails, governance, and ethics.
• 28:07
  SPEAKER_00: You could establish an AI ethics committee or oversight group.
• 28:14
  SPEAKER_00: Use transparent models and allow explanations.
• 28:20
  SPEAKER_00: Always monitor for automation bias, fairness, and human override paths.
• 28:27
  SPEAKER_00: Maintain human audit checks and exception flows.
• 28:34
  SPEAKER_00: Step seven.
• 28:36
  SPEAKER_00: Continuous feedback loops.
• 28:39
  SPEAKER_00: Use metrics such as time to fill, quality, candidate experience, retention to loop back into system tuning.
• 28:50
  SPEAKER_00: Use A B experiments, try interventions, measure lift, refine.
• 28:56
  SPEAKER_00: Let your system learn as you do.
• 29:03
  SPEAKER_00: Here's a hypothetical example.
• 29:05
  SPEAKER_00: Imagine your team automates resume screening with a multi-agent framework.
• 29:13
  SPEAKER_00: The system flags top 20% candidates for human review.
• 29:18
  SPEAKER_00: It also summarizes each candidate in three bullets for recruiters.
• 29:23
  SPEAKER_00: Over three months, your recruiter productivity jumps.
• 29:27
  SPEAKER_00: Your recruiters will now spend their time researching and reaching candidates, engaging and doing deeper assessment, not passing word files.
• 29:39
  SPEAKER_00: You redeploy those saved hours to strategic sourcing, building pipelines, increase candidate touch points.
• 29:47
  SPEAKER_00: That's leverage.
• 29:51
  SPEAKER_00: Some risks, warnings, and what to watch out for.
• 29:55
  SPEAKER_00: Let me be the devil's advocate.
• 29:58
  SPEAKER_00: This power shift brings peril.
• 30:02
  SPEAKER_00: You must steer with your with your eyes open.
• 30:07
  SPEAKER_00: Number one, over automation, cascading failures.
• 30:11
  SPEAKER_00: When you automate too much, you risk glitches, blind spots, and rigidity.
• 30:19
  SPEAKER_00: The ironies of automation warns that humans lose practice in rare edge interventions.
• 30:27
  SPEAKER_00: So build fallback modes, human override, and constant vigilance, right?
• 30:37
  SPEAKER_00: And number two, there's automation bias.
• 30:39
  SPEAKER_00: Teams may lean too heavily on system recommendations, ignoring nuance or context.
• 30:48
  SPEAKER_00: You need to teach your team to question, validate, and challenge.
• 30:55
  SPEAKER_00: There are opaque systems, number three, and lack of trust.
• 31:02
  SPEAKER_00: If your people or candidates just see a black box, that trust erodes.
• 31:09
  SPEAKER_00: The employee well-being in the age of AI paper emphasizes transparency, communication, and human involvement as central to maintaining trust.
• 31:21
  SPEAKER_00: Number four, bias and fairness.
• 31:24
  SPEAKER_00: AI models trained on historical data may perpetuate bias.
• 31:31
  SPEAKER_00: You must audit your algorithms, ensure fairness, engage diversity checks, maintain human oversight.
• 31:43
  SPEAKER_00: Number five, change resistance in politics.
• 31:48
  SPEAKER_00: Some will resist.
• 31:55
  SPEAKER_00: You need change management, communication, and champions.
• 31:59
  SPEAKER_00: You need to involve stakeholders early, show your early wins, and build credibility.
• 32:07
  SPEAKER_00: Number six, data quality and governments, garbage in, garbage out.
• 32:12
  SPEAKER_00: If your data is flawed, your automation breaks.
• 32:16
  SPEAKER_00: So clean your data, enforce data standards, and define owner roles.
• 32:31
  SPEAKER_00: And fast forward to 2027 to 2030.
• 32:35
  SPEAKER_00: Oh my gosh, 2030.
• 32:37
  SPEAKER_00: The winners will be those who master talent ops, orchestration of talent systems, pipelines, mobility, and development in real time.
• 32:51
  SPEAKER_00: They will operate agent ecosystems.
• 32:56
  SPEAKER_00: Not one AI, but many small agents collaborating under human oversight.
• 33:02
  SPEAKER_00: They will think in scenario simulations.
• 33:06
  SPEAKER_00: They will optimize with real-time feedback loops.
• 33:12
  SPEAKER_00: They will embed talent intelligence into business decision making.
• 33:18
  SPEAKER_00: Workforce as a line item in all levers.
• 33:22
  SPEAKER_00: They will maintain human edge, empathy, culture, interpretation, judgment, and ethics.
• 33:32
  SPEAKER_00: So that's who wins, so who fades?
• 33:36
  SPEAKER_00: TA leaders who cling to old models and insist on more work, more manual oversight.
• 33:45
  SPEAKER_00: Strategy-only leaders who can't build or operate the systems, they will fade.
• 33:52
  SPEAKER_00: HR functions that treat tech as a side tool and not a backbone.
• 33:58
  SPEAKER_00: And organizations that ignore ethics, bias, and trust.
• 34:05
  SPEAKER_00: In 2027, when people ask how many hires did you make, the real metric will be how effectively did your talent engine evolve the workforce?
• 34:16
  SPEAKER_00: Hiring is a sub-function, a tiny part of total talent movement.
• 34:24
  SPEAKER_00: Honestly, this is rock and roll level disruption.
• 34:30
  SPEAKER_00: So we've been on a ride, and let me land you with a challenge.
• 34:36
  SPEAKER_00: As soon as this episode ends, list out five tasks in your talent acquisition or talent process that you hate doing.
• 34:46
  SPEAKER_00: Ask yourself, which of those can you automate or remove entirely?
• 34:56
  SPEAKER_00: Pick one small experiment, whether that's resume screening, scheduling, candidate communications, and run it in the next 30 days.
• 35:07
  SPEAKER_00: Automate it.
• 35:10
  SPEAKER_00: Reframe your role from more work to intelligent leverage.
• 35:17
  SPEAKER_00: Measure time saved and redeploy that into higher value work or better yet, creative work.
• 35:27
  SPEAKER_00: Stay close to your tech, build feedback loops, and never let strategy be abstracted from execution.
• 35:38
  SPEAKER_00: If you're a TA leader in 2025, still clinging to do more with less, this episode was hopefully your wake-up call.
• 35:50
  SPEAKER_00: The myth is busted.
• 35:52
  SPEAKER_00: The future waits for no one.
• 35:55
  SPEAKER_00: But those who move, who lean into AI, data, agents, and total talent thinking, the horizon is boundless.
• 36:09
  SPEAKER_00: Thanks for riding with me today.
• 36:11
  SPEAKER_00: This is Eden Haddock, Total Talent.
• 36:14
  SPEAKER_00: Until next time, stay loud, stay brave, build smarter.