Looking ahead to 2026: The year AI becomes autonomous
2025 was the year AI was put into production (by some, gracefully; by others, more painfully). It follows that 2026 is the year AI stops being just tool and becomes a true operational partner. It’ll be a part of the team.
Even breakthrough represents major improvements in how our machines and robots work. The past couple of years have been about natural language and interpreting communication, which is ideal for providing information, searching for answers or handling a single step process. This year will be about smarts. Smart processes. Complex sequences. Multiple steps, often with multiple decision points, to get to an outcome. Smarts means that our bots can handle complex sequences and multi-step tasks, guide processes start to finish, and act independently of steady user direction. These tools won’t need to wait for step-by-step cues; they move ahead on their own once set in motion.
What this means for how customers are treated, where and how support teams operate, and how staff are organized changes everything.
Where companies will win or lose in 2026
In 2025, it was very common for organizations to fall into the trap of replicating their human workflows inside a bot. That’s not always efficient or desirable – as almost all of us have experienced. But in 2026, we need to focus on choosing to do things differently. This year, it will be interesting to observe how some businesses handle shifts while others stall.
To fully benefit from AI, leaders should start by asking these questions:
What experience do customers actually want?
Where should people expect and receive service from a human?
Where can automation deliver a better experience than people?
How should the entire process change and not just the task?
2026 is when we need to stop playing “automation whack-a-mole” and start by designing entirely new journeys.
Here are some of my other predictions for 2026:
Pricing models for AI platforms will face massive pressure
Right now, most conversational AI providers price per minute, which amounts to a 20-30% discount off human voice interactions. Their actual cost can be as much as 60-80% lower, and they will need to start building that savings into their pricing model if they want to succeed and deter enterprises from building their own internal platforms.
In 2026, as volume scales, large enterprises will refuse to pay overinflated per-minute rates. We will begin to see early signs of commoditization like movement toward flat fee pricing and bundled usage models.
This won’t collapse the market, but it determine who grows and who gets acquired in the coming years. It will also test how many enterprises really want to build on their own for a variety of reasons – cost, data control, security, and others.
2. Contact Center quality programs will undergo big changes…finally
In 2025, teams started experimenting with quality automation. This is the year those programs become the norm.
What does this mean?
100% call analysis becomes standard with new insights about how to automate, how to troubleshoot and why are customers really calling. No more guesswork, no more sampling
Coaching also becomes statistically relevant – not just one or two calls, but data on hundreds of thousands of calls to highlight best practices and how to get to them in real situations
Roles within quality change with these new opportunities - the new QA role becomes part data analyst, part AI operator, part CX strategist, part process improvement guru
QA will be more about training the AI than scoring calls. And what happens here affects how teams are hired, coached, trained, retained, scheduled and compensated.
3. Workforce management (WFM) will begin its AI transformation.
By my estimation, the evolution of WFM won’t reach full growth until 2027 or 2028, but there will be a lot of groundwork laid in 2026.
As more and more customer interactions shift from agents to bots:
Companies will hold the line on hiring – it will remain common to allow attrition without backfill and to eliminate agent roles as automation further penetrates work processes
Demand forecasting and predicting channel specific load will get more complicated
Staffing models will need new baselines based on changes in call handling time and human-serviced call or chat deflection
Service level strategy changes will take place based on demand shifts and cost structure shifts, and companies will continue to incentivize using chatbot and AI-driven automation as the one place you don’t have to wait. Customers will follow that design…as long as the automation works
Occupancy and shrinkage assumptions will become outdated as teams become smaller and lower occupancy plus higher shrinkage has to be considered
Operations and WFM leaders will be accountable for understand shifts proactively and adjusting based on future headcount and desired customer experience.
4. The end of satisfaction surveys
I mentioned this in my 2025 retrospective newsletter (link) and it bears repeating: 2026 will be the year satisfaction surveys finally die.
Folks rarely reply these days – or at least, hardly enough to matter. What used to be low response rates of 2-5% now look like sky high response rates. Meanwhile, machines quietly track how people engage. The end result is metrics based on real data, no guesswork, which ends up revealing behavior-driven patterns in escalations, exit from automation, customer and agent sentiment, and bot accuracy.
Companies who choose to rely on post-call surveys in 2026 will be choosing weaker and incomplete or inaccurate feedback. While organization may want to maintain some survey tools, especially qualitative ones or focus groups for future strategic planning and other marketing purposes, when it comes to customer care processes, better tools exist now. Ignoring them will cut you off from helpful and easily accessible data.
5. A new type of employee emerges
The talent landscape will continue to tilt in 2026, with AI creating demand for new hybrid roles. You might see any of these floating around:
AI quality strategist
Conversation designer
Multi-modal journey architect
Agentic AI technician
Automated coaching analyst
Most of the new roles require a blend of skills, some tradition and some new. These include demonstrated understanding or expertise in operational expertise, data literacy, process thinking, AI fundamentals, and human-centered customer experience design
Some organizations will upskill well, some early-career workers will thrive. Others will struggle. Companies that invest in skill building or retraining will have structured programs that teach, incent and give opportunities to perform and learn. The age of tossing an LLM to the team and saying go figure it out as an acceptable way to achieve efficiency is over (if it ever was effective, which I doubt).
The most important strategic shift leaders must make
If I had to give just one piece of advice for this new year, here it is:
What if AI isn’t just another tool? Imagine it woven into how things actually run and stop thinking about AI as another feature. Start thinking of it as part of your operating model. Let that shift how you view what comes next.
What does this mean? In customer experience, leaders need to:
Map end-to-end journeys
Define where human value is irreplaceable
Design “outcome forward”, not step by step
Align governance, data and testing
Prepare teams for new workflows and new roles
Check and adjust every step of the way
But remember – AI does not replace fundamentals. What it does do is raise the bar for them.
2026 will be the most transformative year yet
Companies who scale AI thoughtfully in 2026 will save money and, most importantly, differentiate their customer experience, which will allow them to continue growing both revenue and profit.