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Navigating the AI Evolution Insights from the 2023 Gartner Hype Cycle

The 2023 Gartner Hype Cycle offers a deep dive into the AI evolution, providing critical insights that help decipher the transformative impact of generative AI on today's dynamic business landscape.

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Amit Puri

Advisor and Consultant

Posted on 18 Aug 23

Reference - What’s New in Artificial Intelligence from the 2023 Gartner Hype Cycle from Gartner:

Overview: The 2023 Gartner Hype Cycle™ for Artificial Intelligence (AI) focuses on identifying innovations and techniques in AI that promise transformative benefits while addressing the challenges and risks of imperfect systems. The article emphasizes the importance of considering AI strategies that offer credible cases for investment. Notably, generative AI and decision intelligence are expected to gain mainstream adoption within the next two to five years. Early adoption of these innovations can provide a competitive edge and simplify the integration of AI models into business processes.

Key Points:

  1. Generative AI’s Dominance:
    • Generative AI has significantly increased productivity for developers and knowledge workers, exemplified by systems like ChatGPT.
    • This has led organizations to reevaluate their business processes and the value of human resources.
    • Generative AI has reached the “Peak of Inflated Expectations” on the Hype Cycle.
  2. Two Facets of the Generative AI Movement:
    • Innovations Fueled by GenAI: This category includes areas related to content discovery, creation, authenticity, regulations, and the automation of human tasks. Some of the technologies in this category are:
      • Artificial General Intelligence (AGI)
      • AI Engineering
      • Autonomic Systems
      • Cloud AI Services
      • Composite AI
      • Computer Vision
      • Data-centric AI
      • Edge AI
      • Intelligent Applications
      • Model Operationalization (ModelOps)
      • Operational AI Systems (OAISys)
      • Prompt Engineering
      • Smart Robots
      • Synthetic Data
    • Innovations that Fuel GenAI Advancement: The exploration of generative AI is accelerating, with many organizations experimenting with it. Some technologies driving generative AI forward are:
      • AI Simulation
      • AI Trust, Risk, and Security Management (AI TRiSM)
      • Causal AI
      • Data Labeling and Annotation (DL&A)
      • First-principles AI (FPAI)
      • Foundation Models
      • Knowledge Graphs
      • Multiagent Systems (MAS)
      • Neurosymbolic AI
      • Responsible AI
  3. Generative AI’s Growing Popularity:
    • Generative AI exploration is gaining momentum due to the popularity of stable diffusion, midjourney, ChatGPT, and large language models.
    • Many startups in 2023 are innovating with generative AI, and governments are considering regulations for its impacts.


  • Afraz Jaffri is a Director Analyst at Gartner, focusing on Analytics, Data Science, and AI. He advises Data and Analytics leaders on maximizing their investments in modern data science, machine learning, and analytics platforms.

  • Svetlana Sicular is a VP Analyst at Gartner, focusing on the intersection of data and AI. She believes in the combined intelligence of humans and AI and is passionate about helping organizations achieve digital transformation using AI.

The article provides a comprehensive overview of the current state and future trajectory of generative AI, highlighting its transformative potential and the need for strategic investment and adoption.

The rapid advancements in generative AI have the potential to significantly reshape industries and job roles in various ways:

  • Automation of Routine Tasks:
    • Many repetitive and routine tasks across industries, from data entry in offices to quality checks in manufacturing, can be automated using generative AI. This could lead to job displacements in roles that primarily involve such tasks.
    • However, it also means that employees can be redirected to more value-added activities, fostering innovation and strategic thinking.
  • Enhanced Creativity:
    • In creative industries like advertising, music, film, and design, generative AI can assist human creators by suggesting designs, composing music, or even writing scripts. This could lead to new hybrid roles where humans and AI collaborate closely.
  • Personalized Services:
    • In sectors like retail and healthcare, generative AI can tailor services to individual preferences or needs. For instance, personalized shopping experiences or customized medical treatments. This might lead to an increased demand for roles that manage and interpret AI-driven insights.
  • Research and Development:
    • In pharmaceuticals, biotechnology, and materials science, generative AI can propose new molecular structures or materials. This could accelerate R&D processes and might require professionals who can bridge the gap between traditional research methodologies and AI-driven approaches.
  • Financial Services:
    • Generative AI can be used for fraud detection, credit scoring, and investment strategies. This might shift the focus from traditional financial analysis to more tech-centric roles within financial institutions.
  • Education and Training:
    • With AI-driven personalized learning, the role of educators might shift from general instruction to mentorship, guidance, and addressing individual needs.
  • New Ethical and Regulatory Roles:
    • As generative AI, especially in areas like deepfakes, becomes more prevalent, there will be a growing need for professionals who understand the ethical implications and can work on regulations and standards for AI use.
  • Job Creation in AI Management:
    • As businesses adopt generative AI solutions, there will be a surge in demand for roles related to AI training, maintenance, and management. This includes AI trainers, AI ethics officers, and AI solution architects.
  • Real Estate and Urban Planning:
    • Generative AI can be used to design efficient urban spaces or building layouts. This might lead to a collaboration between traditional architects and AI-driven design systems.
  • Supply Chain and Logistics:
    • AI can optimize routes, inventory management, and demand forecasting. This could change roles within supply chain management, emphasizing data-driven decision-making.

-. Media and Journalism:

  • Generative AI can assist in content creation, from writing articles to producing video content. Journalists and content creators might work alongside AI tools, focusing more on analysis, interviews, and investigative work.

In essence, while generative AI will undoubtedly lead to the automation of certain tasks and possibly the obsolescence of some roles, it will also create new opportunities, roles, and ways of working. The key for industries and professionals is adaptability, continuous learning, and understanding how to leverage AI to augment human capabilities.

In the rapidly evolving landscape of GenAI, organizations face a pivotal choice: to harness the innovations powered by GenAI or to pioneer the very innovations that propel GenAI forward. Where will you position yourself in this transformative journey?

  • Innovations that will be fueled by GenAI.
  • Innovations that will fuel advances in GenAI.

Read on

If you are interested in Citizen Development, refer to this book outline here on A Guide to Citizen Development in Microsoft 365 with Power Platform, Now, available on, Select the Amazon marketplace based on your location to purchase and read the book on Kindle or on the web
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If you wish to delve into GenAI, read Enter the world of Generative AI

Also, you can look at this blog post series from various sources.

  • Hackernoon
  • Hashnode
  • Medium
  • Stay tuned! on Generative AI Blog Series

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    Certain part of this post was generated through web-scraping techniques using tools like Scrapy and Beautiful Soup. The content was then processed, summarized, and enhanced using the OpenAI API and WebPilot tool. We ensure that all content undergoes a thorough review for accuracy and correctness before publication

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