Seyfarth Synopsis: On April 29, 2024, the
U.S. Department of Labor’s Wage and Hour Division released a
Field Assistance Bulletin addressing the application of the Fair
Labor Standards Act to use of artificial intelligence and other
automated systems in the workplace.
Artificial Intelligence (AI) is seemingly ubiquitous. By 2025,
half of Human Resource departments are predicted to use AI in some capacity.
Employers are increasingly using AI-powered timekeeping systems or
applications that can generate timecards, determine schedules and
staffing, monitor performance, and process payroll (among many
other benefits). Against this backdrop, and pursuant to Executive Order 14110 (Oct. 30, 2023), the
U.S. Department of Labor’s Wage and Hour Division (WHD)
released a Field Assistance Bulletin (FAB) highlighting
some of the compliance risks under the Fair Labor Standards Act
(FLSA) associated with the use of AI in the workplace.
Tracking Work Time
The FLSA generally requires that covered employees be paid at
least the federal minimum wage for every hour they work and at
least one and one-half times their regular rate of pay for each
hour worked in excess of 40 in a single workweek. One issue that
often arises in wage-hour litigation is whether the employer had
knowledge of any uncompensated work performed by an employee. As
noted here, courts generally hold that compensable
work under the FLSA is work that employers require, know about, or
should have known about.
Traditionally, employers tracked time worked through either time
clock machines or timesheets. Increasingly, however, AI is being
used for automated timekeeping in which software tracks when
workers sign in and out of work and then determines an
employee’s “active” and “idle” time. For
example, some AI-driven software monitors remote workers by taking
screenshots of their computers at set intervals and collecting
data, including keyboard activity and application use, to generate
a timecard every 10 minutes throughout the day. The software only
records as time “worked” when the system detected
“active” work, such as moving a mouse or a keystroke. Any
periods of perceived inactivity are considered non-compensable idle
time, which would not be reflected in the employees’ pay.
WHD notes that this type of software may lead to wage-hour
liability. “An AI program that incorrectly categorizes time as
non-compensable work hours based on its analysis of worker
activity, productivity, or performance could result in a failure to
pay wages for all hours worked.” Although WHD does not provide
examples of incorrectly categorized idle time, such examples may
include AI-powered monitoring software failing to fully account for
the time employees spend working away from their workstation;
offline time spent thinking, strategizing, or resolving problems;
time employees spend reviewing and researching hard copy documents
or taking handwritten notes; or any offscreen engagement with
clients or customers (among other “offline”
activities).
Monitoring Break Time
The FAB also provides that employers must ensure that any
AI-powered monitoring software recognizes compensable breaks.
Generally, short breaks of 20 minutes or less taken during the
workday are generally counted as compensable hours worked, while
uninterrupted breaks of 30 minutes or more are not. See 29
C.F.R. §§ 785.18, 785.19.
Traditionally, employers monitored break time through employees
recording the start and end of their break. By as WHD notes,
“[s]ome timekeeping systems now incorporate AI to make
predictions and to auto-populate time entries based on a
combination of prior time entries, regularly scheduled shift times
and break times, business rules, and other data.” Moreover,
automatic meal and break deductions are often a preferred default
setting for employer timekeeping software, where a set period of
time (e.g., 30 minutes) is automatically deducted from non-exempt
employees’ pay for any given lunch period.
According to WHD, such software may result in an FLSA violation,
and provides the following example: “an employee usually takes
a 30-minute unpaid meal break but skips the break on a particular
day due to their workload. Without appropriate human oversight, a
system that automatically deducts the break from the employee’s
work hours based on the employee’s past time entries could
result in the employer failing to properly record and pay the
employee’s hours worked.”
Waiting Time
Not all idle time is compensable. Instead, under the FLSA, idle
time is compensable when employees are “engaged to wait,”
but not when they are “waiting to be engaged.”
Many companies have relied (and are relying) on AI tools and
AI-driven software to manage staffing levels in a manner more
finely tuned to changing demand, including having employees
“on standby” and thus ready to work as needed. For
example, WHD found that “automated systems used by some hotels
independently prioritize and assign tasks to housekeeping workers.
When a guest checks out of their room or requests service, these
systems automatically delegate the task of cleaning that hotel room
to a worker based on their availability and other
factors.”
The efficiencies achieved through use of this technology may
also, however, pose wage-hour compliance risks. “When the
employee is not provided with sufficient time that they can use for
their own purposes, is not completely relieved from their duties,
or is expected to remain nearby their workstation and is not given
a set time when to report back to work, they are generally
considered to be ‘engaged to wait.'” Therefore, WHD
states that “employers must ensure that they accurately
account for increments of time when the employee was waiting for
their next assigned task,” unless the employee was
sufficiently able to use his or her time effectively for personal
activities.
Work Performed at Multiple Geographic Locations
Another area WHD identified where AI can result in unforeseen
wage-hour risk involves the continuous workday rule, which provides
that the period between the start and finish on the same workday of
an employee’s principal activity or activities is generally
considered compensable. See 29 C.F.R. § 790.6. Thus,
travel from job site to job site during the workday is also
generally compensable. See id. § 785.38.
WHD found that some employers use location-based monitoring to
track employees, which an automated system processes to determine
whether an employee is “working.” According to WHD, using
such technology may inadvertently lead to wage-hour liability, and
WHD provided the following example: “A system that records
only the time the worker spent at the worksite as compensable work
hours when the worker is performing work away from the worksite may
fail to account for travel time between worksites or hours worked
at other locations and may result in minimum wage or overtime pay
violations.”
Calculating Overtime Compensation Owed
The amount of overtime pay due to an employee is based on the
employee’s “regular rate of pay,” which is found by
dividing the total pay for employment in any workweek (minus
certain statutory exclusions) by the total hours worked during a
given workweek.
Issues sometimes arise when non-exempt employees are paid
multiple wage rates (e.g., different hourly rates for different
types of work). In such a scenario, the employee’s regular rate
of pay for that week is typically the “weighted average”
of such rates. See 29 C.F.R. § 778.115.
WHD found that some AI-driven “systems have the ability to
automatically recalculate and adjust a worker’s pay rate
throughout the day . . ., which may result in significant different
regular rates from one workweek to the next. Similarly some
automated task assignment systems have the ability to determine the
number of types of tasks assigned to individual workers, based on a
variety of factors and metrics,” and then pay workers at
different rates based on tasks performed.
WHD instructs that employers who use such technologies
“must ensure that the different rates are properly calculated
into the regular rate of pay[.]”
Conclusion
AI and the use of automated technologies for scheduling,
timekeeping, and calculating overtime may pose wage-hour risk. Any
such technologies, therefore, should be vetted to ensure that they
do not lead to wage-hour liability.
The content of this article is intended to provide a general
guide to the subject matter. Specialist advice should be sought
about your specific circumstances.
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