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PUBLISHER: VDC Strategy | PRODUCT CODE: 2141115

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PUBLISHER: VDC Strategy | PRODUCT CODE: 2141115

2026 Buyer Behavior Guide

PUBLISHED:
PAGES: 265 PPT Slides/PDF; 225 Exhibits/Excel
DELIVERY TIME: 1-2 business days
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Technology priorities look very different depending on the operating environment. VDC Strategy’s latest buyer research breaks down how organizations across seven frontline industries are approaching mobility, automation, connectivity, AI, security, and workflow modernization.

This upcoming research gives technology providers a clearer view into where demand is forming, what buyers care about most, and what can prevent new technologies from scaling.

Explore findings across:

  • Healthcare: Mobile EHR integration, workforce productivity, cybersecurity, connected care, and clinical AI
  • Public Safety: CAD/RMS modernization, situational awareness, frontline mobility, interoperability, and AI-enabled response
  • Field Service: Asset visibility, predictive maintenance, mobile workflow integration, connectivity, and operational resilience
  • Manufacturing: Automation, production visibility, maintenance technology, cybersecurity, and AI-enabled optimization
  • Retail: Inventory accuracy, omnichannel fulfillment, frontline mobility, analytics, and loss prevention
  • Transportation & Logistics: Real-time shipment visibility, driver mobility, delivery workflows, and route optimization
  • Warehousing: Automation, data capture, labor productivity, and connected fulfillment workflows

The research is based on 840 enterprise mobility decision-makers and examines the operational challenges, investment priorities, purchasing requirements, deployment barriers, and AI use cases shaping frontline technology decisions in 2026.

Download the preview to compare buyer priorities across industries and identify where your solutions align with emerging demand.

2026 Buyer Behavior Guide

Technology priorities look very different depending on the operating environment. VDC Strategy’s latest buyer research breaks down how organizations across seven frontline industries are approaching mobility, automation, connectivity, AI, security, and workflow modernization.

This research gives technology providers a clearer view into where demand is forming, what buyers care about most, and what can prevent new technologies from scaling.

Explore findings across:

  • Healthcare: Mobile EHR integration, workforce productivity, cybersecurity, connected care, and clinical AI
  • Public Safety: CAD/RMS modernization, situational awareness, frontline mobility, interoperability, and AI-enabled response
  • Field Service: Asset visibility, predictive maintenance, mobile workflow integration, connectivity, and operational resilience
  • Manufacturing: Automation, production visibility, maintenance technology, cybersecurity, and AI-enabled optimization
  • Retail: Inventory accuracy, omnichannel fulfillment, frontline mobility, analytics, and loss prevention
  • Transportation & Logistics: Real-time shipment visibility, driver mobility, delivery workflows, and route optimization
  • Warehousing: Automation, data capture, labor productivity, and connected fulfillment workflows

    The research is based on 840 enterprise mobility decision-makers and examines the operational challenges, investment priorities, purchasing requirements, deployment barriers, and AI use cases shaping frontline technology decisions in 2026.

List of Exhibits

Healthcare

  • Exhibit I-1 Healthcare organization type
  • Exhibit I-2 Healthcare technology investment decision-makers
  • Exhibit I-3 Technology evaluation and approval timeline
  • Exhibit I-4 Leading healthcare sector challenges
  • Exhibit I-5 Operational initiatives prioritized over the next 12 months
  • Exhibit I-6 Healthcare technology investment priorities over the next 12 months
  • Exhibit I-7 Primary challenges in ensuring effective EHR use
  • Exhibit I-8 Important technologies for addressing EHR challenges
  • Exhibit I-9 Concerns when adopting automated EHR documentation solutions
  • Exhibit I-10 Patient-facing technology priorities over the next 12 months
  • Exhibit I-11 Solutions for mobile governance and device management challenges
  • Exhibit I-12 Current and planned use of healthcare technologies
  • Exhibit I-13 Scanning and identification technology use by workflow
  • Exhibit I-14 Factors influencing technology purchasing decisions
  • Exhibit I-15 Typical device replacement cycle
  • Exhibit I-16 Responses to higher device costs
  • Exhibit I-17 Mobile device selection criteria in healthcare settings
  • Exhibit I-18 Leading mobile device deployment challenges
  • Exhibit I-19 Healthcare inventory and asset management approaches
  • Exhibit I-20 Most difficult inventory-related challenges
  • Exhibit I-21 Organization connectivity capability and performance
  • Exhibit I-22 Cybersecurity challenges affecting frontline technology strategy
  • Exhibit I-23 Primary reason technology pilots fail to scale
  • Exhibit I-24 Current and future value of AI-enabled workflows
  • Exhibit I-25 AI-enabled capabilities influencing mobile device purchases
  • Exhibit I-26 Barriers to AI-enabled solution deployment
  • Exhibit I-27 Areas addressed by the organization’s AI policy

Public Safety

  • Exhibit II-1 Public safety operational/technical environment
  • Exhibit II-2 Public safety technology investment decision-makers
  • Exhibit II-3 Technology evaluation and approval timeline
  • Exhibit II-4 Leading public safety industry challenges
  • Exhibit II-5 Operational initiatives prioritized over the next 12 months
  • Exhibit II-6 Public safety technology investment priorities over the next 12 months
  • Exhibit II-7 Incident documentation, digital evidence, and case information challenges
  • Exhibit II-8 Technologies for improving incident documentation and evidence workflows
  • Exhibit II-9 Interagency information-sharing challenges
  • Exhibit II-10 Technologies for improving interagency information sharing
  • Exhibit II-11 Situational awareness and emergency response challenges
  • Exhibit II-12 Technologies for improving situational awareness and response coordination
  • Exhibit II-13 Devices used by public safety mobile workers
  • Exhibit II-14 Evaluation of mobile-driven workstations
  • Exhibit II-15 Perceived benefits of mobile-driven workstations
  • Exhibit II-16 Perceived challenges of mobile-driven workstations
  • Exhibit II-17 Expected in-vehicle computing setup in three to five years
  • Exhibit II-18 Factors influencing technology purchasing decisions
  • Exhibit II-19 Typical device replacement cycle
  • Exhibit II-20 Responses to higher device costs
  • Exhibit II-21 Mobile device selection criteria in public safety settings
  • Exhibit II-22 Leading mobile device deployment challenges
  • Exhibit II-23 Organization connectivity capability and performance
  • Exhibit II-24 Primary reason technology pilots fail to scale
  • Exhibit II-25 Current and future value of AI-enabled workflows
  • Exhibit II-26 AI-enabled capabilities influencing mobile device purchases
  • Exhibit II-27 Barriers to AI-enabled solution deployment
  • Exhibit II-28 Areas addressed by the organization’s AI policy

Field Service

  • Exhibit III-1 Utilities & energy organization type
  • Exhibit III-2 Utilities & energy technology investment decision-makers
  • Exhibit III-3 Technology evaluation and approval timeline
  • Exhibit III-4 Leading utilities & energy industry challenges
  • Exhibit III-5 Operational initiatives prioritized over the next 12 months
  • Exhibit III-6 Technology investment priorities over the next 12 months
  • Exhibit III-7 Field inspection and maintenance challenges
  • Exhibit III-8 Technologies for improving field inspection and maintenance
  • Exhibit III-9 Work order execution and field service coordination challenges
  • Exhibit III-10 Technologies for improving work order execution and coordination
  • Exhibit III-11 Asset and inventory management challenges
  • Exhibit III-12 Technologies for improving asset and inventory management
  • Exhibit III-13 Field inventory and operational asset management methods
  • Exhibit III-14 Devices used by utilities and energy mobile workers
  • Exhibit III-15 Workflows supported by vehicle-mounted and in-vehicle workstations
  • Exhibit III-16 Vehicle-mounted computer requirements and deployment challenges
  • Exhibit III-17 Factors influencing technology purchasing decisions
  • Exhibit III-18 Typical device replacement cycle
  • Exhibit III-19 Responses to higher device costs
  • Exhibit III-20 Mobile device selection criteria in utilities and energy settings
  • Exhibit III-21 Leading mobile device deployment challenges
  • Exhibit III-22 Workflows suited to head-worn wearable technologies
  • Exhibit III-23 Benefits of head-worn wearable technologies
  • Exhibit III-24 Frontline field communication systems
  • Exhibit III-25 Field communication challenges
  • Exhibit III-26 Future priorities for frontline communication technologies
  • Exhibit III-27 Organization connectivity capabilities
  • Exhibit III-28 Primary reason technology pilots fail to scale
  • Exhibit III-29 Current and future value of AI-enabled workflows
  • Exhibit III-30 AI-enabled capabilities influencing mobile device purchases
  • Exhibit III-31 Barriers to AI-enabled solution deployment
  • Exhibit III-32 Areas addressed by the organization’s AI policy

Manufacturing

  • Exhibit IV-1 Manufacturing organization type
  • Exhibit IV-2 Manufacturing technology investment decision-makers
  • Exhibit IV-3 Technology evaluation and approval timeline
  • Exhibit IV-4 Leading manufacturing industry challenges
  • Exhibit IV-5 Operational initiatives prioritized over the next 12 months
  • Exhibit IV-6 Manufacturing technology investment priorities over the next 12 months
  • Exhibit IV-7 Production line efficiency and throughput challenges
  • Exhibit IV-8 Technologies for production line efficiency and throughput
  • Exhibit IV-9 Equipment maintenance, uptime, and reliability challenges
  • Exhibit IV-10 Technologies for equipment maintenance, uptime, and reliability
  • Exhibit IV-11 Inventory accuracy and material movement challenges
  • Exhibit IV-12 Technologies for inventory accuracy and material movement
  • Exhibit IV-13 Worker productivity, safety, and enablement challenges
  • Exhibit IV-14 Technologies for worker productivity, safety, and enablement
  • Exhibit IV-15 Devices used by manufacturing frontline workers
  • Exhibit IV-16 Factors influencing technology purchasing decisions
  • Exhibit IV-17 Typical device replacement cycle
  • Exhibit IV-18 Responses to higher device costs
  • Exhibit IV-19 Mobile device selection criteria in manufacturing settings
  • Exhibit IV-20 Leading mobile device deployment challenges
  • Exhibit IV-21 Views on emerging manufacturing technologies
  • Exhibit IV-22 Benefits of industrial robotics
  • Exhibit IV-23 Benefits of autonomous mobile robots
  • Exhibit IV-24 Benefits of industrial IoT sensor networks
  • Exhibit IV-25 Benefits of wearable and AR-assisted technologies
  • Exhibit IV-26 Organization connectivity capability and performance
  • Exhibit IV-27 Primary reason technology pilots fail to scale
  • Exhibit IV-28 Current manufacturing traceability challenges
  • Exhibit IV-29 Current and future value of AI-enabled workflows
  • Exhibit IV-30 AI-enabled capabilities influencing mobile device purchases
  • Exhibit IV-31 Barriers to AI-enabled solution deployment
  • Exhibit IV-32 Areas addressed by the organization’s AI policy

Retail

  • Exhibit V-1 Retail organization type
  • Exhibit V-2 Retail technology investment decision-makers
  • Exhibit V-3 Technology evaluation and approval timeline
  • Exhibit V-4 Leading retail industry challenges
  • Exhibit V-5 Operational initiatives prioritized over the next 12 months
  • Exhibit V-6 Retail technology investment priorities over the next 12 months
  • Exhibit V-7 Omnichannel order fulfillment challenges
  • Exhibit V-8 Technologies for improving omnichannel fulfillment
  • Exhibit V-9 Inventory visibility and demand alignment challenges
  • Exhibit V-10 Technologies for improving inventory visibility and demand alignment
  • Exhibit V-11 Checkout experience challenges
  • Exhibit V-12 Technologies for improving the checkout experience
  • Exhibit V-13 Devices used by retail mobile workers
  • Exhibit V-14 Factors influencing technology purchasing decisions
  • Exhibit V-15 Typical device replacement cycle
  • Exhibit V-16 Responses to higher device costs
  • Exhibit V-17 Mobile device selection criteria in retail settings
  • Exhibit V-18 Views on emerging retail technologies
  • Exhibit V-19 Primary RFID investment drivers
  • Exhibit V-20 Current and planned in-store RFID read points
  • Exhibit V-21 Benefits of personal shopping devices and applications
  • Exhibit V-22 Benefits of smart carts
  • Exhibit V-23 Benefits of scanning self-checkout solutions
  • Exhibit V-24 POS transaction form factors
  • Exhibit V-25 Benefits of mobile POS devices
  • Exhibit V-26 Current and planned use of loss prevention solutions
  • Exhibit V-27 Effectiveness of solutions for reducing theft and shrink
  • Exhibit V-28 Retail Media Network expansion touchpoints and technologies
  • Exhibit V-29 Organization connectivity capability and performance
  • Exhibit V-30 Primary reason technology pilots fail to scale
  • Exhibit V-31 Current and future value of AI-enabled workflows
  • Exhibit V-32 AI-enabled capabilities influencing mobile device purchases
  • Exhibit V-33 Barriers to AI-enabled solution deployment
  • Exhibit V-34 Areas addressed by the organization’s AI policy

Transportation & Logistics

  • Exhibit VI-1 Transportation and logistics organization type
  • Exhibit VI-2 Transportation and logistics technology investment decision-makers
  • Exhibit VI-3 Technology evaluation and approval timeline
  • Exhibit VI-4 Leading transportation and logistics industry challenges
  • Exhibit VI-5 Operational initiatives prioritized over the next 12 months
  • Exhibit VI-6 Transportation and logistics technology investment priorities over the next 12 months
  • Exhibit VI-7 Participation in and management of last-mile delivery
  • Exhibit VI-8 Last-mile delivery services and delivery types supported
  • Exhibit VI-9 Primary last-mile delivery execution challenges
  • Exhibit VI-10 Technologies for addressing last-mile delivery challenges
  • Exhibit VI-11 Returns, pickups, and reverse-logistics execution challenges
  • Exhibit VI-12 Digitization and integration across last-mile workflows
  • Exhibit VI-13 Use of mobile applications and devices in last-mile workflows
  • Exhibit VI-14 Proof-of-delivery and delivery-verification methods
  • Exhibit VI-15 Leading causes of failed, late, or disputed deliveries
  • Exhibit VI-16 Most important last-mile performance metrics
  • Exhibit VI-17 Warehouse, fulfillment, and staging issues affecting last-mile performance
  • Exhibit VI-18 Adjacent operational areas constraining delivery performance
  • Exhibit VI-19 Last-mile workforce and task-execution challenges
  • Exhibit VI-20 Devices used by transportation and logistics mobile workers
  • Exhibit VI-21 Factors influencing technology purchasing decisions for last-mile workers
  • Exhibit VI-22 Typical device replacement cycle
  • Exhibit VI-23 Responses to higher device costs
  • Exhibit VI-24 Mobile device selection criteria in transportation and logistics settings
  • Exhibit VI-25 Leading mobile device deployment challenges
  • Exhibit VI-26 Current and planned adoption of emerging last-mile technologies
  • Exhibit VI-27 Organization connectivity capability and performance
  • Exhibit VI-28 Primary reason technology pilots fail to scale
  • Exhibit VI-29 Current and future value of AI-enabled workflows
  • Exhibit VI-30 Barriers to AI-enabled solution deployment
  • Exhibit VI-31 Areas addressed by the organization’s AI policy

Warehousing

  • Exhibit VII-1 Manufacturing industry type
  • Exhibit VII-2 Wholesale distribution industry type
  • Exhibit VII-3 Retail industry type
  • Exhibit VII-4 Transportation and logistics industry type
  • Exhibit VII-5 Warehouse facility types owned or operated
  • Exhibit VII-6 Primary job function
  • Exhibit VII-7 Warehouse technology investment decision-makers
  • Exhibit VII-8 Total warehouse facility footprint
  • Exhibit VII-9 Expected change in warehouse facility footprint
  • Exhibit VII-10 Warehouse automation investment appetite
  • Exhibit VII-11 Daily outbound order-line volume
  • Exhibit VII-12 Leading warehouse operations challenges
  • Exhibit VII-13 Familiarity with warehouse workflows
  • Exhibit VII-14 Current automation level by warehouse workflow
  • Exhibit VII-15 Expected automation change by warehouse workflow
  • Exhibit VII-16 Past impact of automation on warehouse labor requirements
  • Exhibit VII-17 Expected impact of automation on warehouse labor requirements
  • Exhibit VII-18 Warehouse labor allocation by workflow
  • Exhibit VII-19 Workforce impacts of warehouse automation
  • Exhibit VII-20 Receiving and inbound automation technology adoption
  • Exhibit VII-21 Receiving and inbound processing challenges
  • Exhibit VII-22 Putaway and storage automation technology adoption
  • Exhibit VII-23 Putaway and storage challenges
  • Exhibit VII-24 Inventory management automation technology adoption
  • Exhibit VII-25 Inventory management challenges
  • Exhibit VII-26 Order picking and fulfillment automation technology adoption
  • Exhibit VII-27 Order picking and fulfillment challenges
  • Exhibit VII-28 Shipping and outbound automation technology adoption
  • Exhibit VII-29 Shipping and outbound operations challenges
  • Exhibit VII-30 Returns and reverse-logistics automation technology adoption
  • Exhibit VII-31 Returns and reverse-logistics challenges
  • Exhibit VII-32 Warehouse automation pilot scaling outcomes
  • Exhibit VII-33 Barriers to scaling warehouse automation
  • Exhibit VII-34 Stage where warehouse automation initiatives stall
  • Exhibit VII-35 Perfect order rate
  • Exhibit VII-36 Outbound shipment-error rate
  • Exhibit VII-37 Change in shipment-error rate
  • Exhibit VII-38 Handling of perishable or time-sensitive inventory
  • Exhibit VII-39 Inventory waste and write-off rate
  • Exhibit VII-40 Causes of inventory waste and write-offs
  • Exhibit VII-41 Impact of warehouse automation on operational KPIs
Have a question?
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Jeroen Van Heghe

Manager - EMEA

+32-2-535-7543

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Christine Sirois

Manager - Americas

+1-860-674-8796

Questions? Please give us a call or visit the contact form.
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