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    From potential to performance by design

    TCS AI for Business Study – Key findings for logistics

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    Reimagining business with AI

    Artificial intelligence (AI) offers transportation and logistics companies new opportunities to provide safe, flexible, and convenient journeys for their customers and cargo.

    The TCS AI for Business Study shows that nearly two-thirds of senior executives in logistics companies are optimistic about the potential impact of AI in their organization. This report provides unique insights about how these companies are moving forward to create effective AI strategies for their enterprise. It examines:

    • The driving factors for AI implementations in logistics companies.
    • AI’s role in redefining the logistics industry.
    • Emerging AI trends in the customer experience.
    • Evolving skills and roles in the logistics industry.
    • AI strategies for logistics firms.
    • Alignment of AI implementations with business results.

    Download the full report

    The transformative power of AI

    Many logistics companies surveyed have a positive sentiment toward AI.

    Logistics associates survey

    An image depicting the logistics associates has a positive sentiment toward AI.

    Logistics associates survey

    Close
    Logistics associates survey
    Logistics associates survey

    According to the study, the majority of logistics companies are preparing for AI with:

    • 66% are currently reworking or planning to rework their business strategy or operations.
    • 93% have AI implementations planned, in process, or completed.

    Yet, there’s no consensus on AI adoption strategies and not enough metrics to measure success. As many as 73% of the logistics companies surveyed say they need better KPIs for their AI implementations.

    Current state of AI

    57% of corporate functions have AI implementations in process or have completed AI projects.

    36% of corporate functions are planning AI implementations.

    Yet there is a gap between aspiration and reality with only 7% of senior logistics executives saying AI is a differentiating factor for business transformation. So, what is hampering AI progress in logistics companies?

    Top AI challenges for logistics companies

    An illustration listing the top three challenges faced by logistics companies. The top three challenges are customer expectations, industry standards/regulations, and cost of deployment.

    Top AI challenges for logistics companies

    Close
    Top AI challenges for logistics companies
    Top AI challenges for logistics companies

    Challenges around generative AI

    When it comes to concerns about AI, especially with the hype around generative AI (GenAI), five strategic challenges are top of mind for logistics companies. They are:

    • Redesign customer experiences.
    • Cultural shifts.
    • Pivot toward automation and efficiency.
    • Increased investment in AI research and development.
    • Ethical and responsible AI use.

    Not enough metrics for ROI

    As the integration of AI into business processes accelerates, the expected financial return on such an investment becomes increasingly significant.

    But only 17% of logistics companies said they have "good enough" metrics and KPIs for their current stage of AI deployments. Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in is challenging.

    Key findings—future of AI

    Most logistics executives believe AI will augment and enhance human capabilities, enabling people to focus on higher-value activities that require creativity, empathy, and strategic thinking.

    • 63% think that human strategic decision-making and creativity will remain essential to their competitive advantage.

    As AI becomes more advanced and part of “business as usual,” the role of humans in the workplace will evolve.

    • 46% of logistics companies expect up to half of their employees will be using GenAI on a daily basis in the next three years.

    Innovation and revenue growth will be a focus for future AI implementations.

    • 82% of Pacesetters in logistics companies—the more financially successful companies we surveyed—are primarily focused on using AI to spur innovation.

    TCS recommendations

    • Data readiness
    • Culture
    • Upgrade
    • Strategy
  • Data readiness
  • Culture
  • Upgrade
  • Strategy
  • Prioritize data across systems

    Understand your data landscape by identifying and standardizing data sources that need to be integrated. Establish common data definitions, formats, and categories. Where possible use AI-driven or rule-based tools to automate repetitive data cleansing tasks.

    Centralize data for better accessibility and analysis

    Select a centralized data storage solution, whether a data warehouse, a data lake, a hybrid solution, a cloud-based solution, or a combination of these.

    Ensure guidelines for data ownership and security

    Clearly define data ownership and access permissions and ensure the centralized data platform complies with relevant regulations such as GDPR and HIPAA). Also, ensure that appropriate security measures are in place to protect sensitive data. 

    Build an AI culture

    Invest in an AI-skilled workforce by developing programs for employees. In addition, collaborate with external organizations to accelerate AI adoption.

    Upgrade infrastructure

    Upgrade IT infrastructure to ensure sufficient computing power and storage for AI applications.

    Use AI strategically

    Enhance inventory management and resource allocation to improve demand forecasting and minimize equipment downtime and maintenance costs.

    Employ AI-powered chatbots and virtual assistants for efficient customer support.

    Utilize AI to reduce fuel consumption and delivery time, which will help to optimize transportation routes.

    Ensure AI systems are fair, unbiased, and data protected.

    Empower your enterprise for the AI-driven future

    Prepare for success by harnessing AI's potential to expand revenue opportunities and drive innovation. Embrace AI not just as a tool for automation, but as an accelerator for growth that will redefine roles, empower your workforce, and unlock new value. In the semiconductor industry, Generative AI is key to revolutionizing chip design, streamlining operations, and setting new benchmarks for best practices. By strategically adopting AI, your enterprise can lead the way in the digital era, staying ahead of the curve and thriving in a rapidly evolving landscape.

    Scale

    Prioritize enterprise readiness for scaling up successful pilot programs.

    Success in the controlled environment of a pilot/POC exercise is no guarantee of success in scaled productionization. Invest in initiatives to prepare your data, tooling, architectures, and people for enterprise-wide AI adoption.

    About the study

    TCS’ Thought Leadership Institute conducted an anonymous study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having an annual revenue of $5 billion to $100 billion. The logistics industry findings are based on feedback received from 59 survey respondents. This global study examines how CEOs, LOBs, directors, and business line managers prepare their businesses to be AI-ready, focusing on their strategy around operations, talent, and future implementation plans. The study also provides best practice recommendations based on these insights.

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