Table of contents
Highlights
- AI in logistics now extends beyond routing and forecasting to support the workforce that keeps goods moving.
- Warehouse, driver, and dispatch teams often lack a desk, inbox, or reachable help desk during their shift.
- Agentic AI can resolve IT and HR requests end-to-end, rather than only routing a ticket.
- Mobile-first, conversational delivery reaches deskless logistics workers on the channels they already use.
- The clearest value comes from onboarding, access, and everyday policy questions handled consistently across sites.
- Moveworks delivers an agentic AI Assistant that can resolve frontline IT and HR requests for logistics teams on mobile and chat.
Your warehouse, driver, and dispatch teams keep goods moving every shift, and most of them do it without a desk. They may lack a company inbox to check or a simple way to reach IT or HR for support.
So when a driver is locked out of a scanning app mid-route or a picker needs a fast answer on a safety policy, there's nowhere obvious to turn. Most workplace support tools were designed for office workers with ready access to a computer. As a result, requests can pile up and work can slow.
Artificial intelligence can help you avoid these issues, but industry adoption still has room to grow. According to recent reports, only about 10% of logistics companies have fully adopted generative AI, even as executive interest continues to grow. Much of that attention goes toward moving freight faster, with less focus on the people who manage supporting workflows.
But the same AI technology used to optimize routes can also support workers directly, even on their mobile devices.
Below, we'll discuss what AI in logistics means, why support for frontline teams tends to fall short, and how AI can help to address this issue.
What is AI in logistics?
AI in logistics applies machine learning, generative AI, and agentic AI to forecast demand, optimize routing and warehousing, monitor cargo, and support the teams who run operations.
Artificial intelligence can also produce measurable improvements in routing. Using algorithmic route optimization, one carrier cut average empty-truck miles from about 30% to 10%–15%.
Different types of technology come together to deliver these results, and they're designed to complement one another:
- Machine learning: Reads large volumes of operational data to identify patterns and predict what's next. This type of technology supports predictive analytics and the computer vision used in automated scanning tools.
- Generative AI: Processes a user prompt to produce outputs like emails or summaries, as well as providing basic answers to questions.
- Agentic AI: Automated technology that can plan tasks against a given objective and carry out multi-step workflows across connected systems.
Used together, these approaches can improve forecasting, monitor equipment, and increase visibility across a supply network.
Why traditional support falls short for frontline and deskless workers
Most logistics operations already run help desks, self-service portals, and HR systems. The trouble is that these tools are often built for employees working from a computer, and frontline teams rarely fit that mold.
Many enterprises already invest in supporting these teams, but accessibility and interconnectivity between systems can still fall short.
Three gaps tend to show up again when it comes to logistics technology and team support:
- Warehouse and dispatch staff have no easy way to reach support during a shift.
- Drivers and field workers often lack the required corporate devices or portals.
- IT, HR, and operations take on too much manual overflow, pulling teams away from higher-value work.
Warehouse and dispatch staff without a help desk
During a shift, floor workers who need additional support often have to rely on slower options:
- Try to use shared terminals at the end of an aisle
- Submit tickets that sit in a queue
- Wait for answers on support lines with longer hold times
Although these support tools may be necessary, relying on them can slow work on the floor. A picker who hits a login error or a dispatcher who needs a quick approval can lose real time waiting for answers, and the work can begin to back up while they wait.
That friction can make it hard for teams to complete their tasks on time. In a recent survey, 82% of frontline workers said better technology and controls would improve their productivity.
Drivers and deskless workers without corporate devices or portals
Most drivers and field staff spend their day on the road, moving between suppliers and job sites. Many of these teams don't receive corporate laptops or company email, so the self-service tools that office employees use every day may not be readily accessible.
Because these teams often don't have the same level of access as others, they can easily miss updates that reach everyone else. Even a simple digital task, like acknowledging a policy or confirming a delivery window, can turn into a time-consuming phone call to get support from in-office teams.
The manual burden on IT, HR, and Ops teams
Requests a frontline worker can't handle on their own often land with IT, HR, or operations teams. When this happens, password resets, access requests, and policy questions can flow into IT and HR queues by the hundreds. A repetitive case can quickly pull a specialist away from critical work that needs their attention.
Onboarding workflows are one example of where these issues can quickly compound. A new seasonal hire might have to wait for system access while HR chases the right approvals across systems and IT provisions accounts by hand. Depending on the size of the enterprise, days can go by before that employee is fully set up, and the same cycle repeats with every new hire.
Interested in learning how agentic AI can help you support your global workforce? Download your free guide.
How agentic AI closes the support gap
Agentic AI can reason, plan, and take governed action across systems to resolve requests end to end with minimal human intervention. For logistics teams, this functionality allows them to connect their AI-driven answers with real action in the moment.
Agentic AI can act as a connective layer across the tools you already use. This allows you to link IT, HR, and operations systems so an employee's request can be automated across systems without manual handoffs.
Recent research indicates that 23% of companies are already scaling agentic AI across at least one business function, with many more experimenting with the technology. For frontline teams, benefits of this connective layer can show up in a few practical ways.
Unifying search, support, and action across systems
A single request often crosses several tools. Today, getting to a resolution usually means an employee has to:
- Hunt through multiple systems just for an answer
- Wait on another employee to confirm policy updates
- Loop in an approver to make final changes
The problem is that each handoff adds another delay.
Agentic AI can help handle these three steps within a single exchange, whether the request starts in IT, HR, or on the floor. Because AI agents can reach across connected systems, employees don't have to know where the answer lives or who owns the fix.
Resolving IT requests end to end
Access and password reset requests are some of the most common tickets a logistics IT team handles. Unfortunately, they're also some of the most repetitive.
Picture a warehouse associate starting a shift who can't log into the handheld scanner app that tells them what to pick and where. They file a ticket, join a queue, and wait, while pallets sit and the shift clock runs.
Agentic AI can help resolve that request directly by confirming eligibility under existing permissions, provisioning the access, and letting the employee know when it's ready.
Handled this way, routine requests are less likely to pile up. With that volume reduced, teams can spend more time on complicated tasks that require a specialist.
Answering HR and policy questions on the floor
Frontline workers handle a steady stream of everyday questions like:
- How much PTO do I have left?
- When does my next shift start?
- Does my benefits plan cover a family member?
- What's the lifting limit for this load?
Many of these questions may not require a specialist to answer. Or they could go unanswered due to a current backlog.
Agentic AI can help to surface these answers in the moment, using the worker's role and location to keep them relevant. A part-time driver in one region and a full-time picker in another can ask the same question, and each receives an answer relevant to their situation.
Meeting workers on mobile, Slack, and Teams
Self-service workflows tend to deliver the most value when they're accessible to employees already working. For frontline teams, that's usually on a mobile device rather than a work computer.
A conversational AI assistant can run on mobile, Slack, and Teams, so support lives on the same devices workers already carry. They can ask questions in plain language from supported channels, without relying on a corporate laptop or company email.
Because that support can reach several channels at once, help stays within reach throughout a shift when a question comes up. A driver between stops or a picker mid-aisle can get the answer they need when they need it, well before the shift ends.
Where AI in logistics delivers the most value for the workforce
AI-driven support in logistics settings can be especially useful where request volumes and friction are already highest.
For frontline teams, a few areas typically stand out:
- Onboarding and access for new and seasonal hires
- Knowledge and policy guidance delivered across sites
- High-volume frontline requests that cover IT, HR, and operations
Onboarding and access for shift and seasonal workers
Once a new hire signs on, getting them ready to work usually requires coordination across different departments and systems:
- HR sets up the employee record
- IT provisions accounts and logins
- Facilities assigns equipment, security badges, and lockers
When teams complete each of these steps manually, employees can spend their first day waiting instead of working.
Agentic AI can help coordinate these processes across departments and connected systems.
As soon as a record is created, an AI agent can open an account, assign a device, or queue up the appropriate training module. This type of automation typically matters most during seasonal peaks, when a single site might bring on hundreds of workers in a week. Faster setup shortens time to productivity and helps prevent the backlog from building up.
Knowledge, policy guidance, and proactive support across sites
Policies and procedures in a logistics operation tend to live in a lot of places. Safety rules sit in one binder, standard operating procedures in another system, and HR policies somewhere in the middle. If an employee needs a quick answer, they first need to know where to look, and the answer can differ from one site to the next.
Agentic AI can draw from connected, approved data sources to provide an employee with a role-specific answer within the flow of their work. It can also surface reminders before a task, like a certification that's about to lapse, and flag potential issues for a supervisor to review.
When delivered consistently across sites, this kind of support can help improve safety and engagement across logistics.
Cross-system support for high-volume frontline issues
A large logistics operation can generate a high volume of small requests each day. Individually, a password reset or a shift-swap question may take only a few minutes, but delays and handoffs can sometimes take hours. At scale, these requests can overwhelm the teams fielding them, leaving workers waiting in line for simple answers.
By using AI agents, teams can offload this repetitive workload while automatically resolving requests across the systems it touches without adding to the queue. Clearing everyday volume this way frees IT, HR, and operations to focus on the exceptions that need a human touch.
Choosing AI that supports your logistics workforce
The strongest AI in logistics is the type that actively supports your workforce. So when you weigh different AI-driven support tools, you should consider two points:
- What's the extent of the tool's reach?
- How much of a request can be effectively automated?
Basic chatbots or AI tools might be able to provide a driver with a link to the password reset page. Agentic AI can reset the password, confirm access, and get the driver back on the road. One shows you a solution, while the other provides it.
Moveworks is an agentic AI platform designed to provide the latter for enterprises. With AI Assistant, Moveworks can provide deskless logistics teams with end-to-end IT and HR support across web platforms, Slack, Teams, and mobile applications.
As employees submit their requests, the platform's Reasoning Engine can interpret the request's intent and support resolution using data from systems such as ServiceNow, Workday, and identity providers.
These integrations are designed to operate with secure, permissioned access and within the policies your governance systems define.
Learn more about how Moveworks can support frontline teams with agentic AI-powered logistics.
Frequently Asked Questions
In logistics, artificial intelligence forecasts demand, optimizes routes and warehouse operations, and monitors cargo conditions. Increasingly, it also supports the workforce by answering questions and resolving IT and HR requests for teams on the floor and on the road.
AI in logistics is the use of machine learning, generative AI, and agentic AI to run operations more efficiently and support the people who keep goods moving. It spans routing and forecasting as well as instant, conversational help for frontline teams.
Yes. Mobile-first, conversational AI can reach warehouse associates, drivers, and dispatch staff who lack a desk or corporate inbox. It lets them ask questions and resolve requests during a shift, rather than waiting in a help-desk queue.
A basic chatbot follows scripted flows and usually hands off or links out. Agentic AI reasons over a request, plans the steps, and takes action across systems to resolve it end to end, such as verifying access and provisioning it automatically.
The biggest gains tend to come from high-volume, repetitive work: onboarding and access for shift and seasonal staff, plus everyday knowledge and policy questions. Proactive support that flags issues early can add further value across sites.
