The State of Generative AI

There is no denying the impact of generative AI’s recent emergence. It seems most organizations are now at least exploring possible use cases for AI/LLM.

ETR’s market research survey on generative AI and large language models (LLMs) focused on budget plans, evaluation and production rates, anticipated ROI, and generative AI vendors. 

Use the form below to download a summary of our State of Generative AI Survey.

While this summary provides some key insights, reach out to our sales team to review complete survey results or to see other examples of ETR’s market research and custom survey capabilities.

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Download the Gen AI Findings Summary

State of Generative AI Feedback Panel

As a follow-up to our State of Generative AI report and survey, ETR Insights hosted an interview with a panel of veteran IT executives who began by emphasizing how generative AI is deployed within organizations to enhance operational capabilities rather than replacing human roles. Our panel highlighted using AI for creating marketing drafts, code generation managing compliance, and improving reporting and underwriting processes while emphasizing the importance of human oversight to audit AI-generated outputs. Concerns were raised about legal liabilities, the need for transparency in AI interactions with customers, and integrating AI governance with existing data management frameworks to manage vendor-related risks and inherent AI biases. Many executives see AI funding as part of a broader commitment to emerging technologies, necessitating new budget allocations. 

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Our panelist discusses his financial services company’s approach to generative AI.

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One panelist shares his legal team’s reaction to using AI within their organization.

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Our panelist shares her thoughts on how to use generative AI “to win the market”.

An additional clip from our State of Generative Panel, as well as other content, is available on our YouTube Channel. Want to here the full panel interview? Contact our service team.

About Generative AI

Gen AI, (Generative Artificial Intelligence) represents a groundbreaking leap in technology. Powered by deep-learning models, it has the ability to generate diverse forms of content, including ideas, text, imagery, audio, conversations, videos, and even synthetic data.

While gen AI has been used since the 1960s, it took a spotlight in 2022 with the unveiling of OpenAI’s ChatGPT. The debut of ChatGPT marked a watershed moment, captivating the press, businesses, and popular culture in a manner unprecedented by any previous generative AI or large language model (LLM) tool. Widely regarded as a “Sputnik moment,” ChatGPT ignited a new era of competition and innovation in the field of AI.

Today, organizations across diverse industries are exploring the vast potential of ML/AI technologies. Use cases include code generation, customer support, content creation, text and data summarization, as well as image editing and design.

As the AI/LLM landscape continues to evolve, tailor-made solutions cater to the unique needs of organizations at various stages of their advanced analytics journey. Major players such as Microsoft, AWS, and Google lead the charge, offering comprehensive MLOps capabilities tailored to mature data science operations. Meanwhile, open-source champions like TensorFlow and Anaconda, coupled with popular libraries and languages like Jupyter Notebook and Python, empower developers worldwide to push the boundaries of AI innovation. Specialized vendors like Databricks and Dataiku provide sophisticated data management solutions that fuel both data science endeavors and business intelligence initiatives.

Looking for a deeper dive into the ML/AI space? Try reviewing/downloading the ETR Observatory for Machine Learning and Artificial Intelligence.

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