Artificial intelligence (AI)—or, “that thing that’s calling into question entire career choices”—is basically teaching machines to do all the stuff humans thought made us special, like writing, art, music, companionship, and curing illnesses. AI is certainly having quite the moment. So much so that nearly one-third of employees are now lying awake at night wondering, “are our jobs safe from AI?”1
Just a year ago, organizations were tiptoeing around AI, trying to figure out what to do with it. Now we’ve hit an inflection point where not having AI can be worse than the AI slop suddenly crowding out the internet. In this technological arms race, businesses have discovered that keeping up now means deploying AI agents that are redefining the very definition of work, itself.
Flash forward to today, and everyone is talking (and worrying) about agentic AI, which can proactively sense needs, plan with reasoning, and execute complex tasks. But instead of contemplating the “automation of the workforce,” businesses should actually be getting excited about the possibilities of “automation and the workforce.”
Where Does Collaboration Between Humans and AI Begin?
“All of these industries are being fundamentally changed by AI,” says Craig Cotton, Concentrix Global Vice President of Product Management, “but here’s the plot twist nobody saw coming—the machines literally cannot take over until we teach them how.”
That training doesn’t just mean loading documents into a large language model (LLM) or even uploading a human-curated Q&A dataset. It’s also about monitoring AI’s answers, reviewing them for accuracy, and retraining the model on the correct answers. That takes human insight—which can’t (yet) be replicated—along with an understanding of the complexities, nuances, and semantics of the question.
“AI can generate answers and get it right a scary high percentage of the time,” says Cotton, “call it at least 80%, but we’ve not found a single brand or a client that said, ‘you know what, 80% is close enough, let’s go with it.’ They’re just not willing to expose their customers to that inaccuracy.”
Acknowledging this need for human-AI collaboration—not competition—reinforces why integrating AI into business strategies is a pathway for sustained growth and staying competitive.
Where Do Humans Fit in Operationalizing AI?
One of the terms we’re hearing more in the industry is operationalizing AI. In simple terms, it’s the strategic integration of AI technologies into everyday business practices. But implementing it is a whole other matter.
This process transcends the casual use of AI tools—such as virtual assistants or rudimentary applications—and involves establishing a comprehensive framework. This framework is designed to leverage data, technology, and human intelligence, to enable enhanced decision-making and operational efficiency.
“In an ideal world,” explains Emily Derfler, Concentrix Senior Product Lead, “when we think about operationalizing AI, the whole operation or process should be a single step for a human.” Again, it sounds simple, but it requires taking all of the necessary inputs and decisions from different platforms and databases, with AI performing a myriad of processes and decisions on the back end, and presenting the user with a one or two-step process.
“But when we look at going enterprise level for enabling agentic workflows,” says Emily, “we not only need the process and the multi-agent workflows, but we also need human oversight, human checks, and human judges to ensure that each of those pieces is truly following the correct process.”
This synergy goes beyond automation, transforming the way businesses operate and enabling agile, adaptable responses to market shifts.
Will There Always Be Human Roles in AI Implementation?
The short answer is yes, humans will always have a role in AI implementation—even if it’s likely to change as AI advances. Nobody really knows what artificial general intelligence will bring, but for now, humans in the loop is essential for AI success. At minimum, AI needs humans to:
- Define goals and needs: AI needs humans understanding of what we want to fix or automate, and to determine realistic targets for improvement.
- Choose the right tools: There are AI tools that can compare vendors, but they haven’t mastered the art of weighing the pros and cons to consider things that can’t be quantified, like personality conflicts with a vendor.
- Customize and train the AI: While AI excels at digesting data, it still needs humans to explain the ins and outs of your business—the processes that drive results, the nuances of your industry, or what sets your customer experience apart.
- Set ethical guardrails: Humans have morals and ethics, yet only 11% of executives have bothered implementing responsible AI practices.2 We need to proactively teach AI how to behave responsibly, including privacy and legal rules.
- Maintain human oversight: Without it, AI risks crossing the ethical boundaries of hate speech, discrimination, or outright deception. Even with them, it risks hallucinations and inaccuracies, which is where humans in the loop make the difference.
By implementing a structured framework for AI operationalization that begins and ends with humans, businesses can enhance efficiency, reduce errors, and create a flexible environment where humans and AI can work together. This successful blending of human insights (I have a weird feeling about this) and AI technologies (the data says you’re wrong) promises improved decision-making and customer experiences.
How Will Humans Fit into the Agentic Future of AI?
Agentic AI represents the moment when AI finally graduates to systems that can act independently with contextual awareness on behalf of users. This goes way beyond traditional AI that waits for prompts or commands. Instead, agentic AI can function autonomously to do things like proactively solving problems, scheduling meetings, negotiating transactions, and providing personalized recommendations.
For instance, AI agents can digest a customer’ extensive datasets—entire purchasing history, browsing habits, favorite TV shows, and most frequently visited locations from GPS history—to tailor interactions at every touchpoint. By analyzing user profiles, AI agents can suggest products that are genuinely useful, making customer service more efficient for everyone involved. They can also handle routine support tasks like answering the same five questions customers ask every day and processing returns.
It may seem like this process doesn’t allow much room for humans, but this is where we get back to the idea of automation and the workforce. By automating the most repeatable tasks, AI frees humans to tackle complex cases requiring uniquely human soft skills: judgment, empathy, and emotional intelligence.
Even in seemingly seamless AI-human partnerships, like translation tools that promise to break down language barriers while maintaining your company’s distinctive voice, humans remain surprisingly indispensable. “AI has knowledge, but it’s the humans who bring the ethos—the governance framework to say what’s right or wrong, what’s good or bad,” says Reagan Miller, Concentrix Global Vice President of Analytics and Voice of the Customer. “Humans also bring the pathos, which is caring about the customer and the outcomes.”
What Are the Future Implications for Employment with AI?
The rise of AI presents what economists like to call a dual narrative—a tale woven with both promise (AI will make work amazing!) and apprehension (AI will make work extinct).
It’s crucial to approach these concerns with a balanced perspective. Far from being a job-destroying apocalypse, AI is expected to generate new roles—potentially two to three positions for every one displaced.3 This embodies the beautiful paradox of AI: economic growth through automation can coexist with a constantly shifting job market.
Addressing job displacement fears requires reskilling and upskilling initiatives—comprehensive training programs that teach employees not just to coexist with AI, but to leverage it as their new digital sidekick. Companies must cultivate a culture of adaptability and continuous learning.
So, Are Our Jobs Safe from AI?
Jobs have always changed alongside technology. And they’ll only continue to evolve with AI.
As organizations graduate from tentative AI pilot projects to full-blown enterprise-wide agentic AI adoption, the journey from data to intelligence—and from intelligence to wisdom starts to make sense. Think of it like watching your awkward intern evolve from someone who didn’t know anything about your business or how it worked, into someone who you trained and now actually knows what they’re doing.
Over the next 12-18 months, we predict the relationship between humans and AI agents will undergo significant growth, characterized by more collaboration and deeper integration across organizational functions. To navigate this transformation companies must:
- Start with strategy, not hype: Define what success looks like (shorter waits? higher NPS?) before investing in AI tools.
- Keep it customer-centric: The best AI agents feel helpful, not gimmicky, and should always include an easy path to human help.
- Measure ROI early: Even simple wins can pay off, building momentum with your human teams and justifying further investment.
- Balance innovation and ethics: Deliberately adopt transparent AI standards that follow regulations to sustain trust and avoid risk.
The Future Is More About Innovation Than Replacement
By embracing “automation and the workforce” rather than “automation of the workforce,” companies can boldly go into a future where humans and machines collaborate like true teammates, driving innovation, without needing to ask, “are our jobs safe from AI?”
1 “28% of workers fear AI will diminish or replace their role: survey,” Alexei Alexis, CFO Dive, November 6, 2024.
2 “PwC’s 2024 US Responsible AI Survey,” PwC, August 22, 2024.
3 “Ethical Considerations of AI Usage in Agentic Commerce,” Paul Andre de Vera, BSPK, April 14, 2025.
