How do executives feel about AI?

By: Verbit Editorial



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For many business leaders, the key question around generative artificial intelligence (Gen AI) is no longer if, but when to use it.

Given recent advancements in generative AI models, the technology remains top of mind for executives wanting to stay on the cusp of new business models and job functions. From automating repetitive tasks to generating insightful predictions on vast datasets, the influence of generative AI ─ like so many innovative technologies ─ can be felt across sectors from retail to defense manufacturing.

Although AI and machine learning have been around since the 20th century, generative AI was a major breakthrough. Generative AI models work by receiving input from text, images, sound and code. Using this input, they identify patterns in language and design, giving the models the ability to create content that can be strikingly similar to human-generated work.

As executives adopt this new technology into their short- and long-term plans, their business decisions also come with both practical and ethical dilemmas ─ including questions about data privacy and security and job displacement. Although the full scope of generative AI’s impact is not yet known, it will also challenge executives and individuals to consider the broader impact on economic inequality and a new digital divide.

With these concerns in mind, Verbit analyzed survey data from Deloitte to see how executives are thinking about AI. Deloitte conducted the study between October-December 2023, surveying 2,835 leaders involved in AI initiatives at their companies, including senior C-suite executives and board members across 16 countries, such as Germany, India, Japan, Canada and the US.

About two-thirds (62%) of surveyed business leaders reported feelings of excitement about the business prospects of AI, followed by sentiments of fascination (46%) and uncertainty (30%) among survey respondents. The percentage of executives expressing fear, confusion and anger remained in the single digits.

The Deloitte report also found that many business leaders favored government regulation in AI, in contrast to their regulation-averse behavior in other business areas. Thus far, most of the AI tools businesses have relied on are commercially available generative AI tools. The current AI use case in companies, according to the consulting firm, focuses on bolstering efficiency and cost-cutting instead of growth and innovation.

Despite some reservations, executives must also consider the benefits AI tools have brought businesses, notably such tools as OpenAI’s ChatGPT, Anthropic’s Claude, Stable Diffusion, Google’s Gemini, and Microsoft Copilot. ChatGPT, for example, is revolutionizing industries by automating “knowledge work” such as copywriting, customer service and data analysis. Claude helps streamline administrative work through functions like document summarization, rewriting and its Google Sheets add-on.

A bar graph showing how execs believe AI will change their industry

Are executives prepared to adopt AI into their organizations?

The Deloitte survey revealed that most executives believe they will adopt AI sooner rather than later. Nearly half (48%) of executives surveyed by Deloitte felt that AI would transform their organization within three years, while around 17% felt that AI would substantially change their organization’s way of doing things within a single year.

In another recent survey, the Pew Research Center complemented these findings. In 2022, 19% of Americans worked jobs most exposed to AI, meaning their vital job tasks could be replaced or assisted by AI. The survey also found that the jobs most susceptible to AI require a college education and analytical skills and tend to be in fields with above-average pay. Women, Asian and white workers were most exposed to AI.

High-exposure jobs involve gathering and analyzing information, such as those of judicial law clerks, web developers, budget analysts, tax preparers and data entry workers. However, according to Pew, AI cannot automate jobs that provide care and physical activities that humans perform.

AI exposure does not necessarily imply a risk of job losses, as the technology could also complement the work of these workers, boosting their productivity by handling iterative tasks.

Despite roadblocks to deploying AI, including having adequate infrastructure, finding the right talent, and being prepared to assess risk, most of the Deloitte survey respondents said they were somewhat or very prepared to implement an AI strategy. However, in areas of risk and governance, such as plagiarism and systemic bias, they felt less prepared to deal with challenges.

A bar graph showing how executives are looking to AI to increase business efficiency

What do executives expect from AI?

Most (56%) surveyed executives expressed their primary expectation for AI was its potential to enhance business productivity; 35% of the respondents were optimistic about generative AI’s cost-saving potential.

Many of the respondents, according to Deloitte, focused on the tactical benefits AI would bring to business, save for a small group (29%) who believed the technology would also bring strategic benefits by helping boost business growth and improve innovation.

The consulting firm expects the AI adoption cycle to follow the same pattern other technologies have followed in the past: awareness of the technology, high expectations of the technology’s possibilities, disappointment when faced with the reality and substantial growth once the adoption of the technology attains critical mass.

AI limitation concerns are among many factors making executives wary of adopting AI tools in their businesses. AI tools occasionally encounter issues such as hallucination, inaccurate information, extrapolating from limited sources or fallacious reasoning. Furthermore, plagiarism is another risk from AI use when AI creates content without citing its sources properly.

Since the technology is still in its inception stage, AI use also involves regulatory uncertainty, which could pose another barrier to AI adoption in businesses.

By Andrew Jose