{Podcast + Article} The Workforce Revolution: Why Jobs Are Over, But Work Is Just Beginning
If you had to rebuild your workforce from scratch today, knowing everything we now understand about AI, automation, shifting workforce expectations, and changing global conditions, would you structure it the same way?
Most businesses wouldn’t.
Yet, we continue operating as if job titles define work, rather than acknowledging the truth: work is a collection of tasks—some best done by humans, some by machines, and some by AI.
The traditional job model is crumbling—but work isn’t disappearing. Instead, it’s being restructured, redesigned, and redefined.
The companies thriving in 2025 and beyond won’t be the ones adding AI on top of existing structures.
They’ll be the ones fundamentally rethinking how work is done.
That’s where HUMAND comes in.
This week, I spoke with Phil Whelan on Hong Kong’s RTHK3 Radio about this shift—and why AI is forcing businesses to ask smarter questions, not just automate tasks.
One of the key insights from our conversation?
This isn’t just about replacing tasks—it’s about strategically rethinking why we do them, who or what should be doing them, and how we adapt as conditions change.
Listen to the full podcast here:
Introducing HUMAND (= HUMAN AND): A Smarter Approach to Work
HUMAND is more than a framework—it’s a forced strategic thinking exercise that challenges everything we assume about work.
It’s a method I’ve developed and refined over decades, used successfully by business leaders across 160 industries to unlock efficiency, innovation, and profitability.
At its core, HUMAND answers one critical question:
“Based on what needs to be done and the resources we have available, what is the best way to complete this task?”
HUMAND isn’t about eliminating jobs.
It’s about elevating work—making it more strategic, more human, and more adaptable.
Why This Matters Now
Work is evolving beyond static job descriptions. The most successful businesses won’t just “hire employees”—they’ll design dynamic workforces. AI, automation, and global shifts are accelerating change. Those who adapt will lead.
The companies that embrace this new way of structuring work will thrive, while those that cling to outdated job models will struggle to keep up.
The HUMAND Process: How It Works
H.U.M.A.N.D. is built around six clear steps that shift the focus from jobs to dynamic workforces:
Horizon Scan → Audit the Task
Why are we doing this? What’s the actual goal?
Before deciding who (or what) should do a task, we must determine if it even needs to be done at all.
Is this task outdated or unnecessary? Can it be simplified or automated? What does “success” look like?
Example: Answering the Phone Is the goal to answer calls, or to provide fast, useful information? Does the person want a human conversation, or do they just need a quick answer? Would automation help, or would it damage the customer experience?
Unpack → Deconstruct the Work
What parts require human skills, machine precision, or AI intelligence?
Most jobs are a mix of different types of tasks. HUMAND helps unpack each job into its core components:
Human-led tasks → Creativity, empathy, relationship-building Machine-led tasks → Physical labour, automation, repetitive processes AI-led tasks → Data analysis, pattern recognition, real-time decision support
Example: Retail Checkout Is the goal scanning items, or getting customers out quickly and efficiently? If speed and accuracy matter most, is a self-checkout better? If upselling and personal connection matter, should more staff be reallocated to customer experience rather than checkout lines?
Mobilise Humans → Align People with Their Strengths
Are we using our people in the best possible way?
Does this task need a full-time employee, freelancer, or remote worker? Should we outsource it or keep it in-house? Do we need to retrain staff for higher-value roles?
Example: Medical Triage in Hospitals Is the goal gathering patient symptoms, or ensuring patients get care quickly? Can AI handle symptom collection so nurses focus on treatment and decision-making?
Allocate Machines → Let Technology Do the Heavy Lifting
Where can automation reduce errors and increase speed? Are people performing tasks that machines could do better?
Example: Warehousing & Logistics Autonomous forklifts and robotic arms now handle heavy lifting, reducing workplace injuries and increasing efficiency.
Navigate AI → Make Smarter, Faster Decisions
Where can AI improve decision-making, automate workflows, or enhance accuracy? How can AI free up human capacity for higher-value tasks?
Example: Banking & Fraud Detection AI can detect suspicious transactions instantly, reducing fraud losses. AI-powered chatbots handle 80% of routine customer queries, allowing human staff to focus on complex cases.
Design & Deploy → Implement & Continuously Refine
How do we integrate, test, and refine this new workforce model? How do we train staff to work alongside AI and automation?
Example: AI in Recruitment AI screened applications and improved hiring speed by 60%, but initially missed diverse candidates due to biased training data. The company adjusted AI algorithms, introduced human oversight, and achieved a better balance of automation and human expertise.
Try HUMAND for Yourself: A DIY Exploration
If you want to get started right now, here’s a simple step-by-step exercise you can run with your leadership team, HR, or department heads.
Identify a Key Process or Role
Choose a process, job role, or department that feels outdated, inefficient, or ripe for change. Example: Customer service, IT support, logistics, onboarding, or sales.
Ask the Fundamental HUMAND Question
“Based on what needs to be done and the resources we have available, what is the best way to complete this task?” Push yourself to challenge existing assumptions.
Horizon Scan: Audit Every Task
Break the process down into individual tasks (not job roles). Identify what actually needs to be done vs. legacy tasks done “because we’ve always done it this way.”
Unpack: Categorise Tasks
Label each task as: Human-Led → Requires creativity, empathy, or deep strategic thinking. Machine-Led → Repetitive, physical, or process-driven work. AI-Led → Data-heavy, analytical, or decision-support tasks.
Assign Resources
Ask: Who or what is best suited to each task? Consider: Full-time employees, part-time/gig specialists, outsourced partners, machines, automation, AI tools.
Identify Gaps & Opportunities
Where are you over-relying on humans for tasks machines could do? Where are you missing AI-powered decision support? Where could humans add more value if they weren’t bogged down by routine work?
Design a Pilot & Test It
Choose one area to implement small changes and measure the impact. Example: Automate FAQs in customer service, reassign repetitive data entry to AI, introduce workflow automation for HR onboarding.
What You’ll Discover
If you’ve done this properly, you’ll likely realise:
You’re wasting human talent on tasks that could be automated. You have massive inefficiencies in your work structure. Your HR, IT, and leadership teams are working in silos instead of aligning on a smarter strategy.
This exercise is a powerful first step—but the real impact comes when it’s done holistically, across the entire organisation, with expert guidance.
That’s where expert guidance comes in…
Next Steps: Make This a Strategic Conversation
Most companies attempt this alone—only to realise:
They underestimate the complexity of workforce redesign They struggle to align HR, IT, and leadership on a unified strategy They lack a clear roadmap for implementation
That’s why I work with leadership teams to facilitate this process through:
Keynotes → Shifting mindsets on workforce transformation Executive Strategy Sessions → High-level planning for boards & leadership teams Leadership Workshops → Hands-on HUMAND strategy sessions Full-Team Retreats → Deep-dive workforce transformation programs Ongoing Advisory Partnerships → Long-term support to embed HUMAND into operations
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Book a FREE no obligation chat about a HUMAND Strategy Session
Email: Morris@MorrisFuturist.com
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