Outsourcing today doesn’t look like it did even a few years ago. Not because cost stopped mattering, but because the work did.
AI, automation, and digital self-service have reduced a large share of routine, repeatable tasks. What remains is more complex, more variable, and more tightly tied to growth, change, and customer expectations. Volume still exists, but it shows up differently and requires a different operating model to manage well.
Here’s where we see outsourcing making the biggest impact in 2026:
- Preparing data and processes for AI deployment: Cleaning historical tickets, documenting workflows, and setting up QA rules so AI tools are properly trained.
- Running support during AI rollout: Keeping day-to-day service levels stable while new AI tools are tested, tuned, and introduced.
- Ongoing QA, tuning, and escalation after AI goes live: Reviewing AI outputs, refining prompts and rules, and handling the cases AI can’t resolve.
- Complex, non-standard support work: Managing high-touch customers, regulated processes, and scenarios where human judgement is needed.
- Building custom AI tooling to support proprietary processes: Building and supporting software outsourcing solutions.
This kind of work doesn’t fit traditional outsourcing models. It requires teams that can operate inside live environments, understand how technology and process interact, and stay accountable after implementation.
Solution-focused outsourcing partners like The Functionary are built for this. We help you build teams that integrate directly into your operations, work the way you work, and adapt as needs change. That includes supporting AI adoption, ongoing QA and escalation, and providing flexible coverage where and when it’s needed. The focus isn’t on staffing roles. It’s on running the work and keeping it running as things change.
How The Functionary Supports These Shifts in Practice
The five areas above are where outsourcing is being used differently than it was even a few years ago. Not to offload volume, but to create capacity, stability, and execution during change.
Here is how we are supporting clients across those needs.
Talent Pipeline Management for AI and Operational Readiness
As AI changes roles, keeping the right skills in place becomes a constant challenge. Clients work with The Functionary, so they are not rehiring every time the work shifts. We keep a ready talent pipeline across support and operational functions. This allows teams to scale in as little as three weeks and adjust skills as needed. That stability shows up in lower burnout, fewer handoffs, and retention above 95 percent even as roles evolve.
Customer Experience Operations During Periods of Change
Customer experience is usually the first-place instability shows up when systems and processes change. We make sure service stays consistent during changes by handling extra work, dealing with unusual cases, and maintaining quality. This approach keeps SLA performance above 97 percent across active programs. It also prevents the 30 to 50 percent backlog spikes that many times show up during internal change efforts.
Business Process Optimization Where Ownership Matters
When clients bring us into optimize finance, IT, or operations, they are asking us to run the work, not advise on it. We clean up the process, own execution, and support automation as it is introduced. That usually reduces rework and escalations within the first 60 days and keeps leadership out of the weeds.
Custom Software for AI-Driven Operations
Today we build custom software for healthcare, SaaS, and transportation companies scaling AI inside live operations. When off-the-shelf tools do not fit, we design and build systems around how the work actually runs. Clients own the software. We stay involved as it is used and improved, supporting platforms that handle millions of transactions and interactions in production.
Help Desk Support Before, During and After AI Adoption
During AI adoption projects, clients can add Tier 1 coverage, QA, and escalation support to keep service levels stable while systems are being tuned. This absorbs the short-term increase in operational load that most teams experience early on. This approach typically reduces Level 1 ticket volume by about 40 percent and lets teams focus on quality and exceptions instead of volume.
What Our NPS Data Confirms
High satisfaction doesn’t come from outsourcing more work. It comes from running work differently. When teams are embedded, supported by AI, and accountable for outcomes, performance feels in-house because it effectively is. That’s the model behind our 2025 NPS results, and it’s the direction we’re continuing to invest in as we move through 2026.
Outsourcing isn’t going away. But the expectations have changed. The partners that focus on delivering solutions across people, process and technology, not just staffing cost reduction, will be the ones that succeed in the future.