By: Deepak Khosla, Vice President – Enterprise AI and AWS Business Head, LTIMindtree

Innovation is the lifeblood of a business. The arrival of generative AI (Gen AI) heralds a new and exciting chapter in innovation. With its ability to generate new data indistinguishable from existing data, the technology—with Large Language Models at its core—delivers new ideas, processes, designs, content, and code. It is, therefore, no surprise the technology has captured the interest of businesses across industries.

In the fashion industry, Gen AI has surprised us by using the style of legendary fashion designers to create a realistic catwalk with futuristic clothes and environments[i]; it is helping research legal libraries, summarize cases, and draft legal documents using natural language conversations[ii]; it can generate characters, dialogues, and movie scenes (as was done for Everything Everywhere All at Once that won 7 Oscars in 2023[iii]); it can optimize component placement in semiconductor chip design.[iv]

These are eye-popping examples of transformation. They capture our imagination but are not illuminating when determining how the new technology can be leveraged to solve common, everyday problems. To understand this, LTIMindtree decided to follow the breadcrumbs of early adopters. For a study called The State of Generative AI Adoption – The Current Landscape and Lessons from Early Adopters, LTIMindtree surveyed 450 decision-makers in large organizations across the US, Europe, and the Nordics that were early adopters of Gen AI. The survey results provide an interesting panorama of insights for organizations waiting to create a Gen AI roadmap.

Our study shows that organizations widely using Gen AI improve operational efficiency by 20 to 40%. By contrast, those who have adopted it in a partial and limited manner enhance operational efficiency by a mere 14%. Shoring up operational efficiency around procurement, production/maintenance, distribution, sales and marketing, communication, fraud/anomaly/leakage detection, sustainability, customer experience, and decision-making enables scalability and profitability. Our study also showed that 8% of Gen AI users who had embraced it quickly and widely also saw a 20 to 40% decrease in costs. The study reaffirmed our belief that the most extensive adopters begin their journey by targeting improvements in operational efficiency.

Once these early adopters have tasted success, they use Gen AI to improve personalization, enhance customer experience, and aid product design.

A major fallacy around Gen AI is that the technology is used to generate creative content. Our study shows that two in five companies have reported this as a key reason to adopt the technology—with retail, CPG, travel, transport, and hospitality leading the trend— but streamlining creative content is a low priority for leaders. There is considerable wisdom in making content generation a low priority. The creative process is fueled by freedom and experimentation, not by rules and algorithms. It should remain in the hands—and heads—of humans. Using Gen AI for content, however, may benefit smaller organizations that may not have the budgets to create the large volume of content required to feed today’s marketing and business programs.

The survey shows that 81% of organizations that have adopted Gen AI extensively across multiple functions or the entire organization use it to improve customer experience. In comparison, 68% use it to optimize processes and enhance efficiency. A mere 36% of these organizations use technology to streamline creative content generation.

The inability to logically place Gen AI in the technology roadmap is the primary barrier to harvesting the potential of the technology. However, the lack of Gen AI skills and capabilities can also hinder the creation of a well-rounded roadmap.

The challenge is in being able to use Gen AI applications and frameworks. These require natural language processing and deep learning expertise—skills that are in short supply. However, one of the most sought-after roles currently is that of a prompt engineer. These experts can “talk” to Gen AI platforms to deliver the required results. Salaries for the role can range between US$250,000 and US$375,000[v]. The task of a prompt engineer is becoming even more sophisticated with the emergence of new applications that improve prompts iteratively. Called Promptbreeders[vi], they use a self-referential loop to trigger a prompt mutation. The result is specialized high-performance prompts for specific applications outperforming state-of-the-art prompt strategies.

Early adopters are shedding light on where the Gen AI roadmap should lead. Organizations that are considering Gen AI as a business tool should examine the trends they are setting (download The State of Adoption of Generative AI – Lessons from Early Adopters now) to guarantee faster returns. But the supply of talent to help follow the roadmap has, unfortunately, not kept pace. Organizations have two options: wait for universities to offer formal courses in Gen AI that create the talent pool or leverage the existing talent available with their technology partners. It does not take much to place a bet on the fact that practical and ambitious organizations will choose the latter option for the next several years.

Our study distills the strategies of 450 leading decision-makers around Gen AI. It looks at who is adopting the technology, why it is being adopted, and the best ways to guarantee successful adoption

[i] Hyper-Realistic Meta Catwalk, Fashion Innovation Agency: https://www.fialondon.com/projects/hyper-realistic-meta-catwalk/

[ii] Generative AI for Lawyers: What It Is, How It Works, and Using It for Maximum Impact, LexisNexis, May 22, 2023: https://www.lexisnexis.com/community/insights/legal/b/thought-leadership/posts/generative-ai-for-lawyers

^[iii] How AI tools are creating new possibilities for movies and visual design, according to this AWS-powered startup, Amazon, March 29, 2023: https://www.aboutamazon.com/news/aws/how-ai-tools-are-creating-new-possibilities-for-movies-and-visual-design-according-to-this-aws-powered-startup

[iv] Beyond ChatGPT: The Future of Generative AI for Enterprise, Gartner, January 26, 2023: https://www.gartner.com/en/articles/beyond-chatgpt-the-future-of-generative-ai-for-enterprises

[v] Anthropic, last retrieved October 4, 2023: https://jobs.lever.co/Anthropic/e3cde481-d446-460f-b576-93cab67bd1ed

[vi] Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution, Fernando, C., Banarse, D., Michalewski, H., Osindero, S., & Rocktäschel, T., September 28, 2023: ArXiv. /abs/2309.16797