In supply chain and across industries, artificial intelligence (AI) has become an indispensable tool for driving innovation and efficiency. However, the hype surrounding generative AI (GenAI) technology has raised critical questions for supply chain leaders: When is GenAI the right choice, and when should alternative AI techniques be considered? 

To offer valuable guidance for navigating these questions, John Galt Solutions is pleased to offer the complimentary Gartner® research: When Not to Use Generative AI.

Why It Matters

As companies explore the AI-driven landscape, it's crucial to look past the buzz and delve deeper into understanding the nuances of GenAI—when to harness its potential and when to opt for alternative approaches. According to Gartner; “Organizations that solely focus on GenAI and do not consider other AI techniques risk both an increased failure in their AI projects and missing out on most AI opportunities.”

This report highlights the challenges IT leaders face in understanding when to effectively apply GenAI, emphasizing key findings that underscore the importance of strategic decision-making in AI adoption.

We believe that the insights in this research can help you:

  • Understand use case suitability. The report warns against the temptation to apply GenAI indiscriminately, as it may lead to increased project complexity and failure rates. It states it’s important to “Systematically categorize each use case and evaluate its relative GenAI feasibility. Use cases in the categories of prediction and forecasting, planning and optimization, decision intelligence, and autonomous systems are not currently a good fit for the use of GenAI models in isolation.”
  • Gain insights to effectively balance and combine AI models and techniques. Gartner affirms that “AI techniques are not mutually exclusive; they can often be combined in a way that makes for a stronger overall system. Organizations that develop an ability to combine the right AI techniques are uniquely positioned to build AI systems that have better accuracy, transparency and performance, while also reducing costs and need for data.”
  • Access recommendations for successful AI implementation. For example: “Utilize alternative AI techniques when GenAI models are not the right fit. The most prominent alternative techniques are the use of nongenerative machine learning (ML), optimization, simulation, rule-based systems and graphs. For many use cases, these alternatives are often more reliable and better-understood than GenAI models.”

Read this research to gain actionable insights for evaluating AI adoption strategies. By categorizing use cases and considering alternative AI techniques, organizations can ensure they are making informed decisions that align with their business objectives.

John Galt Solutions is pleased to offer this complimentary report as part of our continuous efforts to support companies in their journey to supply chain planning maturity and success.

Gartner, When Not to Use Generative AI Leinar Ramos, Ben Yan, Haritha Khandabattu, Gabriele Rigon. 19 March 2024.

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