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Generative AI Use Case Library for the Goods Transportation Industry

Identify value-driven generative AI use cases to transform your organization.

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  • Adoption has been slow. The benefits of Gen AI technologies for goods transportation are understood but the adoption has been slow despite rapid growth in investment and development.
  • Goods Transportation leaders are unaware of relevant use cases.
  • Goods Transportation leaders lack insights for developing a business-aligned Gen AI strategy as part of a transformation effort nor have an understanding of how AI and ML can impact the business and provide significant value.

Our Advice

Critical Insight

Goods Transportation should approach a Gen AI adoption strategically and methodically within a larger digital strategy context, with a clear understanding of the specific use cases and benefits.

Impact and Result

Info-Tech’s use case library provides practical guidance to help Goods Transportation accelerate value-driven Gen AI use case adoption.

Generative AI Use Case Library for the Goods Transportation Industry Research & Tools

1. Generative AI Use Case Library for Goods Transportation Deck – Identify value-driven Gen AI use cases to transform your organization.

Leverage a robust set of Gen AI use cases to identify potential initiatives that can accelerate value creation. Use cases cover a range of technologies and capabilities and include insight into sources of value.

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Generative AI Use Case Library for the Goods Transportation Industry

Identify value-driven generative AI use cases to transform your organization.

Analyst Perspective

Artificial intelligence is disrupting every industry, but you can get ahead of the shift.

This is beginning to feel like another business revolution. Every communication channel has something to say about artificial intelligence (AI), and “ChatGPT” has become the de facto standard term used for generative AI.

However, ChatGPT is only one tool for generative AI, and nobody knows whether it is, in fact, the best tool. This should scare anyone who is thinking about how they can leverage AI as a holistic solution for their business.

AI has come a long way. The first recorded AI program was written by Christopher Strachey in 1951 as a checkers program, but there is some debate as to whether Alan Turing conducted the first real theoretical work in AI as early as 1935. Geoffrey Hinton, known as the godfather of AI, has more recently raised concerns that AI could be weaponized to cause serious damage to society as it takes over from being used for chatbots to owning all conversations.

Hinton’s 2012 research paper on deep neural networks – an approach to teaching machines to think like humans, only faster than all of humanity put together – set off a race. OpenAI took the first mover advantage to scale rapidly, while Google worked slowly with Bard. Google recently opened Bard to the developer community to counteract ChatGPT by accelerating product development.

Photo of Kevin Tucker, Principal Research Director, Manufacturing Research, Info-Tech Research Group. Kevin Tucker
Principal Research Director, Manufacturing Research
Info-Tech Research Group

Executive Summary

Your Challenge

  • The production operation lacks predictability, and those involved can’t see what is happening throughout the process. The CIO must work closely with operations leaders to identify ways to enable better technology support.
  • It is important to implement a program that avoids run-to-failure and the ripple effects of catastrophic outages.
  • Downtime is unpredictable and longer than necessary because service people are often unavailable when equipment or assets go down.

Common Obstacles

  • The organization is not capturing enough information for decision making or is capturing all the information manually.
  • The organization typically does reactive maintenance, without the skills or knowledge of other programs.
  • Shop floor equipment or assets have not been connected by the internet of things (IoT).
  • Equipment has proprietary sensors that are not easy to connect into a central data lake for planning purposes.

Info-Tech’s Approach

  • Improve your maintenance plans by using this research to understand the needs of your business and how predictive maintenance can help.
  • Use Info-Tech’s tools to structure and evaluate your current state of maturity, identify software tools to help, and assist with the implementation.
  • Adopt a sensing-based approach that considers a holistically interconnected environment for end-to-end capture of information to provide usage lifecycle visibility.
  • Info-Tech advisors work closely with our customers to provide both strategic and tactical decision-making advisory services.

Info-Tech Insight

Predictive maintenance is used in conjunction with the industrial internet of things (IIoT) and maintenance services to help organizations make the most of their data in order to increase uptime, improve safety, reduce maintenance costs, and identify hazardous situations before they occur.

Gen AI is an innovation in machine learning

Image of multi-level platforms.

Icon of a planted seed sprout. Generative AI (Gen AI)

Gen AI is a form of machine learning. In response to prompts, a Gen AI platform can generate new outputs based on the data it has been trained on. Depending on its foundational model, a Gen AI platform will provide different modalities and thereby different use case applications.

Icon of a tree chart. Machine Learning (ML)

ML is an approach to implementing AI, whereby the AI system is instructed to search for patterns in a dataset and then make predictions based on that set. In this way, the system “learns” to provide accurate content over time. (Think of Google’s search recommendations.)

Icon of a flow chart. Artificial Intelligence (AI)

AI is a field of computer science that focuses on building systems to imitate human behavior. Not all AI systems have learning behavior; many systems, such as customer service chatbots, operate on preset rules.

Info-Tech Insight

Many vendors have jumped on “Gen AI” as the latest marketing buzzword. When vendors proclaim to offer Gen AI functionality, you need to pin down exactly what is “generative” about it. The solution must be able to induce new outputs from inputted data via self-supervision – not trained to produce certain outputs based on certain inputs.

Other industries are already using AI, whether or not transportation is prepared

Bar chart comparing the 'Share of service professionals using AI in 2022, by industry'. 'Supply Chain & Logistics' is highlighted and sits in the lower half of the chart at 43%.(Source: Statista, 2022)

“The most relevant use cases today that you see of AI are in customer support and customer service, with so much time spent emailing and answering phone calls.”

— Michael Wax, CEO of Forto, as told to the Journal of Commerce
(Source: Cello Square, 2023)

Measure the value of this document

Document Objective

Highlight best-in-class use cases to spur the initiative planning and ideation process.

Measuring Your Success Against This Objective

There are multiple qualitative and quantitative direct and indirect metrics you can use to measure the progress of your initiative pipeline’s development. Some examples are:

  • Increased initiative pipeline value
  • Number of capabilities impacted by your initiative pipeline
  • Enhanced understanding of the impacts of the initiatives, aligned to your organization’s capability map
  • Better understanding of which sources of value are being addressed or under-addressed in your organization’s initiative pipeline

See Establish Your Transformation Infrastructure in Info-Tech’s Digital Transformation Center

Info-Tech’s approach and team can help irrespective of where you are in your digital journey


Arrow pointing right.


Where are you in the journey?

Establish your digital North Star

Quantify the value of digital use cases

Create the digital roadmap

Deliver digital use cases and realize impact

Create the infrastructure to drive and sustain change

Set aspiration: Vision setting with key business unit (BU) stakeholders to discuss and align on digital aspiration (e.g. big T vs. mini T, self-funded and slow burn vs. investments) Assess opportunity: Comprehensive end-to-end (E2E) understanding of the digital opportunity across BU/functions (e.g. data analysis, process walks, and interviews) Design and plan: Bottom-up initiative design and planning (e.g. opportunity to initiatives, financials, phasing, design principles) Execute: Detailed initiative builds and implementation, execution with rigor and transparency (e.g. process optimization then automation, test, measure, and scale) Enable: Transformation infrastructure, operating model, and culture to drive value capture and sustain change

Examples of how Info-Tech can help

Digital North Star placemat
(e.g. industry trends, top-down opportunity, high-level planning)
Digital maturity assessments
(e.g. current state digital adoption and transformation readiness)
Initiative bottom-up design
(e.g. initiative ideation and business case creation, workplan, investments)
Initiative build
(e.g. zero-based process redesign with technology)
Transformation infrastructure
(e.g. transformation program design, transformation office)
Opportunity assessments*
(e.g. BUs/function value creation diagnostics, opportunity levers)
Holistic initiative planning
(e.g. phasing, interdependencies, investments)
Initiative implementation
(e.g. testing and pilot, scale-up roadmap, performance tracking)
IT modernization
(e.g. technology infrastructure required to execute digital levers)
Value assurance assessment
(e.g. course correcting and accelerating initiatives underway)
Change management
(e.g. org-wide change program and stories, comms, governance)
The following content will provide an overview of AI/ML use cases in goods transportation. This will support opportunity assessments across your organization’s value chain. Note: This does not provide the value/ROI specific to your organization. To do that, detailed current state assessments and opportunity assessments need to be executed. Performance management
(e.g. KPIs – leading and lagging, people mgmt. for continuous imp.)
Workforce management
(e.g. upskilling, right people, right place, right time)

*Applicable framework element(s) for this document

About Info-Tech

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Kevin Tucker


  • Bob Verret VP, Dupree Logistics
  • Mick Kelley, CIO, Mesilla Valley Transportation Services

Search Code: 102975
Last Revised: October 18, 2023

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