The Truth About AI and Jobs: Why Automation Isn't the Enemy

he headlines scream about mass layoffs and job displacement, but the reality is far more nuanced than most people realize.

Recent developments in the HR tech space offer critical insights that every business leader and automation professional needs to understand. Phenom's acquisition of Included, an AI-native people analytics platform, signals a shift in how we should think about AI's role in the workplace.

The Automation Misconception

Here's what most people get wrong: they assume AI will automate everything end-to-end. It won't.

Phenom CEO Mahe Bayireddi breaks down AI implementation into three distinct categories: automation, augmentation, and agentic workflows. This framework is something I use when consulting with clients, because it forces you to think critically about where AI actually adds value.

The data backs this up. A recent Forrester report projects that AI will affect only 6% of U.S. jobs between now and 2030. That's not the apocalyptic scenario many fear.

Where Automation Actually Works

In my experience deploying automation solutions, I've found that frontline jobs in recruiting and talent acquisition can achieve 70-80% automation of specific workflows. But that doesn't mean 70-80% of jobs disappear. It means certain tasks within those jobs get handled by machines.

The key distinction? Complete end-to-end automation isn't feasible anywhere. Middle-tier tasks in workflows are prime candidates for automation, but the beginning and end stages still require human judgment, creativity, and emotional intelligence.

The Radiology Paradox: A Case Study in AI Augmentation

Let me share an example that perfectly illustrates why AI creates opportunities rather than just eliminating them.

Ten years ago, experts predicted radiology would be automated out of existence. Today, demand for radiologists is higher than ever. Why? Because AI didn't replace radiologists—it transformed their role.

When AI automated portions of scan analysis, the cost of CT scans and MRIs plummeted. Combined with an aging population, this created a fourfold increase in the number of scans being performed. Even with AI handling 30% of the workload, the remaining 70% still requires human expertise. The radiologist's job didn't disappear; it evolved into something new.

This pattern repeats across industries. When the cost of a service drops and usage volume increases, jobs don't vanish—they fundamentally transform.

Which Jobs Are Actually at Risk?

Not all roles face equal impact from AI. Based on current trends and my work with various clients, here's the realistic breakdown:

Knowledge Workers: Highest Impact

Developers, programmers, and customer support roles are seeing significant AI integration. This is where replacement is most likely, though even here, we're seeing more augmentation than elimination.

Healthcare: Augmentation, Not Replacement

AI is assisting doctors and nurses, particularly with administrative tasks like billing and documentation. The average doctor spends half their time on paperwork rather than patient care. AI can reclaim that time, but it cannot replace the human element of healthcare.

Frontline Workers: Minimal Impact

Retail workers, nurses, and manufacturing employees aren't going anywhere. Robotics and AI haven't advanced enough to handle the physical and interpersonal complexity of these roles. The market remains tight for these positions.

The Work Reset: What's Really Happening

We're not experiencing job elimination. We're experiencing a work reset.

AI is redistributing tasks between humans and machines. Certain task categories are shrinking while others expand. Some job families will disappear entirely, while roles we never anticipated are emerging.

This creates transitional challenges. People in HR might move into finance. Finance professionals might shift to tech. Tech workers might transition to marketing or sales. These cross-functional movements require new infrastructure and support systems.

Why People Analytics Matter Now More Than Ever

This is where Phenom's acquisition of Included becomes strategically significant.

To navigate the work reset successfully, organizations need clear visibility into three critical questions:

Which tasks can be automated?

Which tasks should be augmented with AI?

Which tasks must remain manual?

You cannot answer these questions without comprehensive people analytics. You need data-driven insights into workforce deployment, skill gaps, and productivity bottlenecks.

The Agentic Analytics Advantage

Included's agentic infrastructure for people analytics converts raw data into actionable workforce insights. This enables HR professionals and business leaders to understand not just what their people are doing, but how to optimize their deployment across the organization.

This diagnostic capability becomes essential when you're managing workforce transitions. Analytics help identify where bottlenecks exist and how talent can be redeployed most effectively.

My Perspective: Building With AI, Not Against It

After years of implementing automation solutions across diverse industries, I've learned that success depends on collaboration between AI and human workers, not replacement of one by the other.

The businesses thriving in this environment are those that:

• Identify specific workflow segments suited for automation
• Invest in augmentation tools that enhance human capabilities
• Develop robust analytics to track workforce deployment and productivity
• Create pathways for employee reskilling and role transitions

The companies struggling are those treating AI as a simple cost-cutting tool rather than a strategic capability that requires thoughtful implementation.

The Path Forward

AI will continue advancing. Automation will expand into new domains. But the narrative of mass unemployment driven by AI doesn't match the data or the practical realities of implementation.

What we're seeing instead is a fundamental restructuring of work itself. Tasks are being redistributed. Roles are transforming. New opportunities are emerging in unexpected places.

The question isn't whether AI will take your job. The question is how you'll adapt your skills and leverage AI to create value in ways machines cannot.

For business leaders and automation professionals, the priority is clear: build the analytics infrastructure needed to understand your workforce, identify automation opportunities strategically, and create pathways for your people to grow alongside these technologies.

The future of work isn't human versus machine. It's human and machine, working in concert to achieve what neither could accomplish alone.