Support operations are at an inflection point. Customer expectations are rising, budgets aren’t, and AI is evolving faster than ever. Support leaders are under pressure to scale efficiently while maintaining quality — often without additional headcount.
In a recent webinar on the future of support operations, Assembled Head of Product Olivia Teich unpacked the trends shaping 2025 — drawing from Assembled’s State of Support Ops in 2025 report and hundreds of conversations with support teams across industries. The report found that 40% of support leaders rank scaling as their top priority, while 33% focus on improving customer experience. The challenge? Doing both at the same time.
“The expectation for support teams today isn’t just ‘do more with less’ — it’s do more, better,” Olivia noted. “And the reality is, the tools available to support leaders are changing at an insane rate.”
The most forward-thinking teams are blending automation, self-service, and workforce management to meet demand without compromising quality. Here’s a look at the macro trends shaping support in 2025.
AI has moved past the hype cycle — it’s no longer a futuristic add-on but a core pillar of how modern support teams operate. However, with rapid adoption comes new challenges: how to implement AI effectively, avoid automation pitfalls, and ensure human agents remain empowered in an AI-driven world.
AI is no longer just a test case — it’s becoming a foundational part of support operations. What was impossible six months ago is now viable, and support leaders are facing aggressive mandates to automate volume and reduce costs.
But AI alone isn’t enough. The most effective implementations don’t just replace agents — they empower them to focus on complex, high-value work. Rather than taking a blunt-force approach to automation, leading teams are making incremental, strategic optimizations, testing and refining AI deployments step by step.
“You don’t just turn AI on and let it run. The teams that see the biggest impact take an iterative approach — ensuring accuracy, building trust, and continuously optimizing their AI deployments,” Olivia explained.
This careful approach preserves customer trust, improves efficiency, and prevents the risk of over-automation leading to frustration, escalations, and workflow breakdowns.
While AI is revolutionizing support, poorly implemented AI can create frustrating, disconnected experiences. Olivia highlighted the risk of AI hallucinations and conflicting answers across channels — a growing issue as multiple AI systems interact in a single support flow.
“One of the biggest challenges I hear about is when customers get instant resolutions from AI in chat, but then escalate and wait days for an agent — who doesn’t have context and gives a different answer,” Olivia noted. “That’s a terrible experience.”
The solution? A more coordinated AI strategy, where automation and human agents work together seamlessly.
Customers expect fast, high-quality resolutions, regardless of staffing challenges or budget constraints. Thanks to companies like Amazon and Uber, same-day resolutions, proactive service, and seamless experiences are now the standard.
To meet these expectations, support leaders are turning to BPOs for flexibility, self-service for scalability, and AI-driven automation for efficiency. But adopting these tools is only part of the equation — orchestrating them effectively is what separates thriving teams from struggling ones.
Olivia pointed out that many support teams struggle to align AI, outsourced teams, and internal agents into a cohesive strategy. The most effective teams aren’t just implementing AI; they’re ensuring:
“Too often, AI and outsourcing are treated as separate strategies — but the best teams integrate them into a single, well-coordinated system,” Olivia said. “That’s how you scale efficiently without losing quality.”
Effective AI and outsourcing strategies aren’t just about who handles which tickets — they’re about designing a workforce that can scale without breaking.
The pressure to do more with the same (or fewer) resources is at an all-time high. Many teams are being asked to handle significantly more volume without increasing headcount. While AI and automation can help, rushed or misaligned implementations often lead to frustrated customers and more escalations.
Successful teams take a measured approach, using AI for routine inquiries while ensuring complex issues are quickly escalated to human agents. At the same time, BPOs are under increasing pressure to adopt AI-driven efficiencies — making staffing strategies more dynamic than ever.
Scaling efficiently isn’t just about handling more tickets — it’s also about ramping up new agents faster and ensuring consistency. Olivia highlighted that AI is playing a growing role in:
“Support teams don’t just need more people — they need smarter ways to onboard, train, and upskill their teams,” Olivia said. “AI isn’t just changing customer interactions — it’s changing how support teams work.”
Support leaders are navigating a fundamental shift — AI is unlocking new efficiencies, but without the right orchestration, automation alone can create more problems than it solves. Poor implementation can lead to broken workflows, inconsistent customer experiences, and frustrated agents.
Unlike AI-only solutions that lack visibility or WFM tools that don’t adapt in real time, Assembled Assist bridges the gap, bringing AI-powered automation and workforce intelligence together in one platform.
With Assist, teams can:
With Assist, teams don’t just automate — they continuously optimize staffing and workflows in real time, ensuring AI, agents, and BPOs work in sync. By combining AI, automation, and workforce management, teams can operate at peak efficiency — without sacrificing quality or adding unnecessary headcount.
AI is now a core part of support operations, but success depends on thoughtful integration. Companies that thrive won’t just implement AI — they’ll design their entire support strategy around it.
Winning teams blend automation, workforce planning, and human expertise to create an efficient, scalable support function. AI agents and copilots improve workflows, workforce management optimizes staffing, and self-service reduces ticket volume.
“We’re at a turning point,” Olivia emphasized. “Support leaders who invest in the right balance of AI, automation, and human expertise today will define success in the years ahead.”
The goal isn’t just to keep up with change — it’s to build a support function that is resilient, adaptable, and prepared for what’s next.
