Executive Summary
As artificial intelligence (AI) continues to automate Tier 1 (T1) service inquiries, what remains are the high-stakes, complex interactions previously handled by Tier 3 (T3) teams. This shift has effectively turned T3 into T1, transforming the frontline agent role into one that requires deeper knowledge, sharper judgment, and more strategic alignment with brand and customer outcomes.
At the same time, global BPOs are chasing lower-cost labor markets, but not all can deliver the capabilities necessary for this new wave of cognitive customer service. To compete, companies must invest in upskilling their workforce and transforming Learning Management Systems (LMS) into talent development engines.
Key Takeaways
Complexity is the new normal: T1 automation is fundamentally changing the traditional customer service model.
Low-cost labor is lagging: Placing outsourced labor on the new frontlines reveals critical gaps in skills and knowledge.
Upskilling is a business-critical priority: Cost-cutting and outsourcing must be accompanied by workforce reinvention.
Human-AI collaboration is key: AI will permeate all service tiers. The question is how and to what extent.
Human interactions = brand: How your agents adapt and operate will significantly reflect on your organization’s brand.
Leaders are taking specific action: From top leadership to agents themselves, change requires a micro-strategic outlook.
A Shift is Underway Within the Contact Center
Leadership is moving from simple automation to strategic rethinking. It’s happening with remarkable speed, thanks in large part to advancements in contact center AI. Look no further than the rapid transformation of the T1 support tier for a prime example.
Research from Gartner found that automation now resolves more than 70% of T1 tasks in leading enterprises.1 By 2028, service leaders can expect 70% of customer service journeys to begin and resolve via “conversational, third-party assistants built directly into customers’ mobile devices.”
Routine customer service work is disappearing.
It’s moving into the digital hands of intelligent, non-human agents. What’s left are complex, multi-factor interactions that require empathy, domain knowledge, and rapid problem-solving. Moving forward, this 20-30% share of high-touch problems will be the focus of nearly 100% of human customer service agents.
1. Automation Is the Filter. Complexity Is the New Normal.
The automation stack—AI, natural language processing (NLP), robotic process automation (RPA), and self-service platforms—has effectively absorbed the transactional layer. This stack is evolving quickly, with the continued adoption of generative AI (GenAI) and agentic AI capabilities.
Today, half of GenAI-enabled companies plan to launch some form of agentic AI proof of concept by 2027. These technologies are capable of further automating much of the T1 service layer, including:
● Verifying account details
● Order status and billing inquiries
● Basic troubleshooting
● Case pre-qualification and routing
An analysis of millions of service interactions reveals that more than half of most interactions remain transactional in nature—ideal candidates for automation. As a result, the problems that filter through to human agents tend to be more complex, more domain-specific, and more empathy-coded.
What Human Agents Now Primarily Address:
● Technical escalations
● Compliance and regulation-heavy issues
● Financial or emotional risk scenarios
● Multichannel service breakdowns
2024 percentage of revenue by voice
“This isn’t just a workload shift; it’s a value shift.”
2. Global Labor Arbitrage Has Its Limits
There is ample research to suggest that AI-led service automation leads to improved performance. Recent data shows that companies with modernized, AI-led processes see 2.4x better improvements to productivity compared to those without.
Yet the same report found that the vast majority (82%) of companies “at the early stage of operations maturity” lack a strategy for talent reinvention. That is: they’re not training and preparing talent for new AI-led workflows.
This reality compounds an already prevalent trend in the BPO market. As global BPOs rush toward lower-cost markets, capability gaps emerge that include, but extend well beyond, AI preparedness. Challenges in Low-Cost Markets:
● Insufficient broadband infrastructure
● Gaps in domain knowledge or education
● Limited familiarity with Western compliance standards
As a result, cost-cutting often comes at the expense of agent and customer satisfaction.
3. Your Agents Are Your Brand Ambassadors
Today’s agents must do more than follow scripts. They’re expected to interpret, empathize, and act. They use AI tools and CRM systems to make judgment calls that directly impact customer loyalty. Their place in the contact center journey is as critical as ever.
Emerging Agent Profile
● Deep product and policy fluency
● Emotional and cultural intelligence
● Fluent in AI-augmented decision support tools
Compensation Benchmarks
Despite the widespread shift toward T1 service automation, customers still expect excellence from human-to-human service interactions. Today, 71% of Gen Z consider live calls to be the quickest and easiest way to “reach customer care and explain their issues.”7 For baby boomers, that share rises to 94%. Overall, 64% of customers prefer that companies not use AI in customer service at all.
When customers do reach a human, their experience influences their impression of the brand itself.
4. Upskilling Is No Longer Optional
High-performing agents are developed, not hired. A survey of managers and executives found that 66% say their “most recent hires were not fully prepared.”9 Yet employees who receive continuous training are 76% more likely to stay with the company providing it.
Training and upskilling have become critical to contact center operations, especially when transformations promise to change an estimated 23% of global jobs in the next five years.11 What’s more, the people overseeing this talent transformation are overtaxed: 61% say the demands on their teams go well beyond their capacity to deliver.
To succeed in this environment, BPOs must invest in upskilling their workforce. This starts with modernizing LMS platforms to continually account for shifting talent dynamics—including the powerful influence of AI.
LMS Must-Do’s
● Link training to career paths and certifications
● Support real-time coaching and AI integration
● Track skills acquisition and tie to performance metrics
“As Tier 1 roles are increasingly automated or augmented, the role left for humans becomes more complex. Getting someone up to speed gets harder. Thankfully, there’s already a battle-tested precedent for reducing ramp time to proficiency. We see AI-powered practice regularly reduce ramp time 40-50%—in many cases even by 6-9 months. Companies who haven’t put practice + coaching at the heart of their talent strategy are going to struggle as this dynamic plays out.”
Rob Wright, Chief Product Officer, Zenarate
“LMS is no longer an HR tool-it’s a growth engine.”
5. From Macro to Micro: What Must Change Now
As a macro-strategic imperative, the urgency of upskilling is clear. On average, today’s workers could see at least 39% of their existing skillsets transformed or made obsolete by 2030.14 It’s no surprise that 85% of employers plan on prioritizing workforce upskilling.
But what are the micro-strategic actions that business leaders must take to make upskilling happen?
Upskilling: Leadership Action Items
For Global Executives:
● View talent capability as a revenue lever
● Align location strategy with education and tech infrastructure
For Enterprise Leaders:
● Rethink support roles as brand-critical
● Build internal academies for retention and advancement
For National Policymakers:
● Invest in vocational and tech training
● Promote public-private upskilling initiatives
For the Agent:
● Offer clear growth paths and brand-aligned roles
● Compensate for cognitive and emotional labor
What’s Next: A Human-AI Hybrid Model
6. What’s Next: A Human-AI Hybrid Model
AI will not replace agents; it will augment them. The next-generation contact center is:
● Human-led, tech-accelerated
● Data-informed, judgment-driven
● Agile in response, scalable in support
At the T1 service layer, automation frees up human agents to handle higher-touch issues. In a recent survey of contact center leaders, 84% of contact center leaders said they expect to see this happen as soon as this year.
Even within this automation layer—which includes pre-emption, self-healing, and self-service16—augmentation can begin in the form of intelligent routing, predictive issue escalation, and dynamic workload balancing.
AI augmentation continues with the integration of AI assistance within the human agents’ existing workflows. Think: real-time sentiment analysis, compliance monitoring, and live conversation coaching (among other practicable means).
AI Augmentation: Strategic Results
That said, only 1% of leaders consider their companies to have mature AI deployments.20 Achieving the maturity needed to realize these strategic results means preparing human-AI teams. For BPOs, this will include a rethinking of how talent is hired and upskilled vis-a-vis AI. These teams will require clear guidelines on how and when to use AI; and their leadership teams will require new means for measuring and improving performance.
In Closing: Complexity Is the New Entry Point. Prepare Accordingly.
The contact center is no longer a back office cost center. It is the front line of brand, loyalty, and revenue. As Tier 1 disappears through automation, T3 will become the new standard. It will have complexity as its entry point, human-AI synergy as its productivity accelerator.
Leaders must act now to build a workforce capable of delivering on that complexity with speed, empathy, and precision.
