5 AI Workforce Management Takeaways for Today’s Contact Center
In a recent webinar, “Life Happens: Can Your WFM Software Keep Up?” Verint WFM experts shared 5 key reasons why contact centers need the next generation of AI workforce management.
Key takeaways
Traditional WFM builds the plan. AI workforce management keeps it alive.
WFM forecasting accuracy is a P&L line item, not a vanity metric.
Continuous, intraday alignment turns firefighting into foresight.
Long-term capacity planning is where service levels are won or lost.
Schedule flexibility is now a retention lever that pays for itself.
Thousands of contact centers using Excel spreadsheets or traditional workforce management (WFM) solutions are struggling to meet their cost and service goals. Verint WFM experts, Trudy Cannon, Sr. Director, GTM Strategy, and Florian Garnier, Sr. Manager, GTM Strategy, shared industry trends and changes in channel and customer behaviors that make using these tools so challenging.
Here are five ways AI workforce management helps organizations manage the complexity and volatility of today’s contact center and ride the wave of automation and change.
1. Traditional WFM builds the plan. AI workforce management keeps it alive
Traditional WFM software does three things well:
- Produces a solid staffing plan.
- Gives agents structured flexibility.
- Holds the historical record of interaction volumes and past events.
What it does not do is adapt to life as it happens, or the changes in volumes, availability, or handle times that occur after the day has begun. As Florian Garnier explained: “Adapting in real time still means reacting, and reaction is expensive.”
AI workforce management, however, adds an adaptive layer on top of your traditional WFM foundation. It provides highly accurate forecasts for scheduling intervals, comprehensive long-term capacity plans and what-if scenarios for informed decisions, and continuous AI-powered analysis that predicts where the day will land and recommends the right move to take before the wave of change hits.
The pressure for a more adaptable, efficient workforce planning tool is growing. In 2026 and going forward, contact centers will experience:
- Fewer people: Gartner found that more than 80% of organizations plan to cut agent headcount within 18 months.
- Higher customer expectations: Verint’s The State of Customer Experience 2025 report found that 36% of consumers now expect better service than they did a year earlier.
- More complex work: Verint’s The State of the Agent Experience 2026 report found that 94% of agents expect AI to change their role within three years, replacing routine work with more complex tasks as chatbots absorb the easy contacts.
Forecasts exclusively based on historical data, static schedules, and after-the-fact insights cannot solve for these challenges.
2. WFM forecasting accuracy is a P&L line item, not a vanity metric
Traditional WFM software can be very effective for building out a basic forecast from historical data for a standard 4- to 6-week scheduling period. But the workforce planner then needs to modify it by hand for everything happening outside the tool, such as:
- Known events like marketing campaigns and product launches
- Internal business changes and trends: handle-time fluctuations, system upgrades, changes to IVR prompts
- External changes such as new regulations
Every manual adjustment to a forecast degrades its statistical accuracy, and the result can be overstaffing and wasted cost or understaffing and poor service. In fact, every 1% forecasting error costs a typical contact center roughly $400,000 a year (Verint research, unpublished), and the average forecast runs +/- 10% to 12% accurate. The cost can be incurred on two levels:
- Overstaffing burns budget outright
- Understaffing puts agents on back-to-back contacts all day and pushes customers into longer queues
AI workforce management helps contact centers achieve 95%+ accuracy in complex, multi-channel, multi-skill environments while keeping interval-level control over workload, SLAs, shrinkage, occupancy, and efficiency. One multi-line specialized insurer tightened forecast accuracy from +/- 12% to 6%. At a $400K-per-point cost curve, they potentially saved $2.4M.
3. Continuous intraday alignment turns firefighting into foresight
Intraday reforecasting is the practice of rebuilding the remainder of the day’s forecast and staffing picture as live volume, handle time, and adherence data arrives. In traditional WFM, reforecasting is manual, slow, and simulation-heavy, which is why most teams skip it. However, the need for it is growing.
Deviations from plan can happen for many reasons.
- Volume changes: A competitor runs a promotion, and your customers suddenly call to see what kind of counter offer you may have.
- Availability: The flu runs through your center, resulting in seven unplanned absences.
- Handle times: New legislation requires added explanations and disclosures, pushing handle times up.
- Channel shift: Failed IVA and digital sessions get dumped back into chat and voice as sudden, unplanned intraday spikes.
Today, AI workforce management, and capabilities like Verint’s Workforce Intelligence Operations Assist, are simplifying and automating the process of adapting to intraday changes to plan. The solution was released in June as part of Calabrio WFM and Workforce Intelligence, with Verint WFM support coming, and demonstrated live in the July 29 webinar, “Life Happens. Can Your WFM Software Keep Up?”
Operations Assist identifies every skill or metric at risk of missing its SLA and puts them on one pane of glass with a predictive, end-of-day service level for each. One click opens the schedule with the affected skill preselected. The solution generates an AI summary of what is driving the risk, e.g., negative staffing deviations, higher-than-forecast traffic, breaks and lunches clustered in the wrong intervals. It then offers specific, AI recommended actions to proactively resolve the risk, such as shifting breaks for three agents between 2:45 and 3:00 p.m. or moving five agents off phones to cover live chat for 30 minutes.
4. Long-term capacity planning is where service levels are won or lost
Interval forecasting, and intraday forecasting certainly impact SLAs. But as Trudy Cannon explained, “The plan that matters most is built long before the schedules are.” As a workforce planner, she says you have to think at least six months out. Hiring takes roughly three months, training takes six weeks, and locking in an outsourcer, 90 days.
If you only plan to the six-week scheduling horizon, the decision about whether you will be staffed at an appropriate level has already been made for you.
You cannot do long-term planning on an Excel sheet anymore, not when you are optimizing a skill-set mix, planning work types with very different handle times, and accounting for customers who move between channels mid-journey.
For example, Trudy shared that in 2016 consumers used one to two channels to reach a company, predominantly phone and email. Today the average consumer uses nine.
Traditional WFM plans for roughly half those channels, which means you don’t even have the full historical data needed to build an accurate capacity plan. Forecasting for just phone volume, or phone plus email, means you are planning for a fraction of the demand, and it ignores channel shift: the abandoned call that reappears as an email or chat, and then as a callback.
Long-term capacity planning is also where the business decisions get made. Tools like Verint’s Long-Term Capacity Planner play a key role in testing the impact of different scenarios on your cost and service goals. For example, when the budget will not cover projected demand, what’s the cost/benefit tradeoff of different sacrifices? Do you:
- Make certain contact types/channels absorb the wait? Which ones are more tolerant of a longer wait?
- Turn on the call-back feature or push more customers to self-serve channels?
- Protect/retain certain skills if reducing headcount? Which skills will be needed most?
- Spend on overtime or an outsourcer? What’s the cost differential?
Building capacity plans that factor in business decisions and changing channel and customer behavior can reduce the occurrence of intraday SLA risks and unmet cost and service goals.
5. Schedule flexibility is now a retention lever that pays for itself
Nine out of ten contact center agents rank scheduling flexibility as a top priority, and 46% cite the lack of it as one of the two biggest challenges in their role. Replacing an agent costs between $10,000 and $20,000. With an average attrition rate of 32% (Verint research, unpublished), a 200-agent center could spend $640K to $1.28M a year in replacement costs alone.
Traditional WFM offers shift swaps and shift bids for advanced planning, but limits flexibility precisely when agents need it the most — in-the-moment changes as life happens: a sick child, a broken-down car, a last-minute appointment.
Verint TimeFlex puts the power to modify schedules in the hands of the agent. Using a coin-based, gamified model, agents are given visibility into when the organization is over- or under-staffed. Agents can adjust their schedules to either earn points by working timeslots that are understaffed or use points to take time when it’s not as beneficial to the business. The model continually looks at the staffing needs in 15-minute increments and can automatically approve changes that work for the agent and the business, adhere to work rules that enforce labor law requirements for breaks and lunches, and protect activities like mandatory training.
One insurer reduced attrition by 30% and unplanned absences by 23%, saving $4.5M. A large telco cut attrition and unplanned absences by 24% while improving schedule efficiency by 4.5%.
Watch the webinar on demand
The full session, including the live Operations Assist demo and the Q&A on multi-skill long-term planning and TimeFlex guardrails, is available on demand.
To learn more about AI workforce management capabilities, check out our WFM Buyer’s Guide.
To see where AI workforce management might benefit you, start with the challenge causing you the most grief:
• Cost pressures and flat budgets point to AI-powered forecasting and the Long-term Capacity Planner
• Meeting SLAs at lower cost points to Workforce Intelligence and Operations Assist
• Agent retention and experience point to TimeFlex.
Together these solutions enable Workforce Excellence. Learn how Verint enables Workforce Excellence.
About the speakers
Trudy Cannon is a Senior Director of Go-To-Market Strategy at Verint, with more than two decades in contact center operations and workforce management. Her focus is long-term capacity planning, forecasting accuracy, and how WFM software has to change to support omnichannel, multi-skilled, AI-assisted operations.
Florian Garnier is a Senior Manager of Go-To-Market Strategy at Verint and previously ran workforce management teams in high-volume contact centers, including at Lyft. He works on real time workforce management — intraday management, real time adherence, and intraday reforecasting — and led the Operations Assist demo in this session.
Frequently asked questions
AI workforce management sits on top of a traditional WFM foundation and leverages AI to automate workflows for workforce planners, supervisors and agents alike. It can generate in real-time early warning signs of SLA risk with recommended actions, and provide AI insights for faster, better decision making.
Traditional WFM is very effective at building a basic forecast and schedule for a standard four- to six-week period, but everything happening outside the tool — campaigns, product launches, handle-time shifts, new regulations — has to be modified by hand, and every manual adjustment degrades the statistical accuracy of the forecast. AI workforce management ingests those events and all channels automatically, applies multiple AI models, and keeps the plan current as conditions change instead of leaving planners to react after the fact.
It protects service levels on two horizons. Long-term capacity planning makes sure the people, skills, and outsourcing capacity are in place months before the schedule is built, since hiring takes roughly three months and training another six weeks. Intraday, capabilities like Verint’s Workforce Intelligence Operations Assist flag every skill or metric at risk of missing its SLA, summarize what is driving the risk, and recommend a specific action (shifting breaks, moving agents between channels, offering overtime or VTO) early enough to change the outcome.
Intraday reforecasting is the practice of rebuilding the remainder of the day’s forecast and staffing picture as live volume, handle time, and adherence data arrives. In traditional WFM it is manual, slow, and simulation-heavy, which is why most teams skip it, even though volume swings, unplanned absences, rising handle times, and channel shift from failed digital sessions create complexity and volatility that directly impact your cost and service goals.
Long-term capacity planning models the FTE, skill mix, and budget constraints to help determine the resources you will need six months to several years out, and tests how different scenarios affect your cost and service goals. A spreadsheet cannot keep up once you are optimizing across a skill-set mix, work types with very different handle times, and customers who move between channels mid-journey. The average consumer now uses nine channels, up from one or two in 2016. Traditional WFM plans for roughly half of them, so not even complete historical data needed for an accurate plan is there.
Every 1% of forecasting error costs a typical contact center roughly $400,000 a year (Verint research, unpublished), and the average forecast runs only +/- 10% to 12% accurate (Verint research, unpublished). The cost shows up as overstaffing that burns budget outright or understaffing that puts agents on back-to-back contacts and pushes customers into longer queues. One multi-line specialized insurer tightened accuracy from +/- 12% to 6% with Verint Workforce Management, a potential $2.4M saving against that cost curve.
Nine out of ten agents rank scheduling flexibility as a top priority, and 46% cite the lack of it as one of the two biggest challenges in their role — while replacing a single agent costs $10,000 to $20,000 (Verint research, unpublished). Verint TimeFlex lets agents adjust their own schedules within a coin-based model that automatically approves only the changes that also work for the business and comply with work rules. One insurer reduced attrition by 30% and unplanned absences by 23%, saving $4.5M.
It reduces cost on two fronts. More accurate forecasting cuts the overstaffing that burns budget outright, and continuous intraday adjustment prevents the understaffing that drives overtime and long queues. One multi-line insurer tightened forecast accuracy from +/- 12% to 6%, a potential $2.4M saving.
Real-time adherence tracks whether agents are doing the activity they are scheduled for right now. Intraday reforecasting rebuilds the rest of the day’s forecast and staffing picture as live volume and handle-time data arrives. Adherence tells you who is off-plan; reforecasting tells you whether the plan itself still holds.
AI models ingest campaigns, product launches, handle-time shifts, and all channels automatically instead of leaving planners to adjust by hand — and every manual adjustment degrades statistical accuracy. Verint customers reach 95%+ forecast accuracy in complex multi-channel, multi-skill environments.