In 2022, Klarna laid off 700 employees to embrace AI.
They weren’t alone. In the years that followed, companies like Microsoft and PayPal also leaned into an “AI-first” approach and cut back on human staff, especially in areas like customer service.
Customer experience (CX) leaders have always been under pressure to cut costs while keeping customers happy. AI simply became the latest lever to pull.
Fast forward to 2025: Klarna, despite being an early champion of an AI-first approach, began rehiring human customer service agents.
The lesson is clear. In the rush to embrace AI, many leaders are missing a bigger opportunity.
Instead of replacing people, companies should use AI to upskill and elevate their human customer service agents into “superagents.” Pairing AI with the Gig Economy can become a secret weapon for many companies.
The Gig Advantage in Customer Experience
An Ogilvy Consulting report found that by 2027, half of the developed world’s workers will be part of the gig economy. CX leaders are among those increasingly turning to these workers to cut costs while still delivering a high-quality experience.
Gig workers can answer customer support calls and handle technical inquiries at less cost. But cost savings don’t mean compromising on quality. They are remarkably efficient, spending up to 90% of their paid time serving customers, compared to just 65% for a traditional business process outsourced teleworker. Less time, more impact.
“Gig workers aren’t just ways to cut costs,” says Mohit Thukral, CEO of Arise. “They are the force multipliers that can make-or-break consumer loyalty in some of the most high-stakes moments of interaction.”
During a holiday rush or a new product launch, gig workers make it easy to scale support up or down quickly. Companies can tap into this expertise without adding more full-time roles, and customers get fast, around-the-clock service.
Beyond scalability, gig workers often bring specialized skills to the job, like multilingual support, technical troubleshooting, or local cultural skills that strengthen customer-brand interactions. Many gig workers also operate across multiple brands and industries, spurring a cross-pollination of ideas that sharpens their work, fuels continuous improvement, and creates a more empathetic, modern approach to customer experience.
Companies can’t get all those benefits with AI. But what they can do is use it to elevate their gig agents and turn them into superagents.
Complementing AI IQ with Human EQ
Even if AI could handle customer experiences from beginning to end, human customers aren’t there yet. According to a recent Prosper Insights & Analytics survey, over 70% of respondents said they’d rather interact with a real person than an AI chat program for tasks like handling banking issues, online shopping inquiries, or booking travel.
The reason likely comes down to IQ (intelligence quotient) versus EQ (emotional quotient). IQ drives logical reasoning, structured problem-solving, and technical expertise. EQ drives self-awareness, impulse control, and empathy.
AI can handle IQ. It can field basic customer queries, optimize workflows, and identify patterns in large datasets. What AI cannot do (yet) is fully understand complex emotional cues, navigate the nuances of human emotion, and make decisions from those factors that brands can trust.
This is where human-in-the-loop (HITL) models come in. Instead of leaving systems to run unchecked, HITL ensures experts are embedded in AI workflows: validating edge cases, correcting mistakes and making sure outputs are enterprise ready. Reinforcement learning with human feedback (RLHF) takes it a step further, creating continuous feedback loops where experts teach models what “good” looks like. Together, HITL and RLHF are how companies get AI that not only is scalable, but also accurate, safe, and aligned with brand values.
Companies can unlock opportunities by pairing the IQ of AI with the EQ of human agents.
- Recognizing patterns for humans to address. AI-based analytics can flag recurring customer issues, product questions, technical complaints, or process bottlenecks. Gig workers can then intervene proactively by suggesting updates or escalating emerging problems before they snowball.
- Spotting negative sentiments across multiple channels. AI sentiment analysis can identify frustrated or high-value customers in real time across social media, community forums, or chat. Agents can then prioritize interventions that protect brand reputation and turn potential complaints into brand loyalty.
- Amplifying the impact of human interactions. AI can provide on-the-spot guidance, knowledge prompts, or predictive suggestions to gig agents during calls or chats. This empowers agents to solve problems faster, personalize their responses, and tackle complex scenarios with confidence.
And when complexity requires a live agent, that agent must be skilled, experienced, and adept at problem-solving, pointing back to the value of gig workers. With the help of AI, those workers can pivot seamlessly into upselling, cross-selling, or de-escalating sensitive situations. Customers get quick and personalized service, while companies turn each interaction into a brand-building opportunity.
The glue that makes this balance work is HITL oversight. By embedding experts directly into AI workflows, companies can continuously refine models while keeping outputs compliant and trustworthy. RLHF is already emerging as the gold standard for training generative AI, giving brands confidence that their systems will learn, improve and stay aligned to customer expectations.
“We meet a lot of companies that believe either everything or nothing should be automated for their customers. The truth is somewhere in the middle,” explains Thukral. “The flexibility of a gig model becomes important because sourcing highly skilled workers with high EQ is the perfect complement to the expansive IQ of AI systems. That union is where the frontier firm is born: an organization powered not just by human effort, but by scalable, on-demand, and ambient intelligence.”
The world of work is rapidly changing but pouring all resources into AI and letting humans go isn’t the answer. Like Thukral said, the answer is somewhere in the middle. Together, AI and gig workers can create a CX model that’s not just efficient but genuinely human-centered to deliver faster resolutions, deeper customer connections, and measurable brand impact.
