More than three years after ChatGPT helped ignite the artificial intelligence boom, businesses across industries are increasingly integrating AI into their operations. However, experts say the technology has yet to deliver the sweeping productivity gains or workplace transformation promised by its most enthusiastic advocates, The Wall Street Journal reported Sunday.

Companies are using AI to summarize meetings, draft emails, generate reports, and automate routine tasks as corporate spending on the technology continues to rise. Recent surveys of chief executive officers and chief information officers indicate businesses plan to increase AI investments through this year, reflecting growing confidence in the technology's potential.

Research released by Deloitte in January and a separate study conducted by the Wharton School found that many large companies have moved beyond experimentation and are incorporating AI into core business functions. The Wharton survey of 801 executives found that roughly three-quarters reported positive returns on their AI investments.

The technology is being deployed across a broad range of sectors. Retailers are using AI to adjust prices in real time and personalize product recommendations. Private-equity firms have developed AI-powered research tools to support investment decisions, while manufacturers are relying on computer vision systems to identify defects on production lines.

One of the most significant advances has occurred in software development, where AI tools are increasingly capable of generating computer code from plain-language instructions, reducing the time required for certain programming tasks.

"Saying we're stuck in pilot mode is this outdated idea that's wrong," said Ethan Mollick, a professor at the Wharton School who studies AI adoption. "I'm talking to companies all the time getting real value out of AI."

Despite AI's growing use, businesses continue to face significant challenges in deploying the technology at scale. Corporate boards and investors are increasingly demanding evidence that AI investments are generating measurable returns, while questions remain about whether current systems are capable of fundamentally transforming industries.

Analysts describe the uneven performance of AI systems as a "jagged frontier," a term used to explain why AI can excel at some tasks while performing poorly at others.

According to independent technology analyst Benedict Evans, AI performs particularly well on structured tasks such as software coding, legal document review, and financial analysis. However, it often struggles with work that depends on context, judgment and institutional knowledge.

Current AI systems can also produce inaccurate responses with high confidence, limiting their usefulness in many decision-making environments.

That limitation has led some economists to caution against expectations that AI will quickly replace large segments of the workforce.

"Whether you're a CEO, a manager, a journalist, a professor or a construction worker, I see your skills as beyond what AI can perform," said Daron Acemoglu, who argues that today's AI tools are likely to affect only a portion of existing jobs.

Experts also note that successful AI deployment requires substantial infrastructure beyond the models themselves — including access to reliable data, security safeguards, governance frameworks, and clearly defined human oversight.

Because each organization's systems and workflows differ, companies often must build those structures from the ground up — a process that can be costly and time-consuming.

Industry observers say the greatest obstacles may be organizational rather than technological.

Many companies operate on long planning cycles and remain cautious about replacing systems that were implemented only a few years ago. Employees may also resist adopting technologies they fear could threaten their jobs.

"What is being sold is this idea of productivity and efficiency," said Kate Brennan. "And what that means for the people doing the actual work is rarely part of the conversation."

Businesses frequently use AI to automate portions of existing processes rather than redesign workflows around the technology, experts say.

For example, insurers may use AI to speed up paperwork associated with auto accident claims while maintaining traditional review structures. A more transformative approach would allow AI to assess damage from photographs, approve claims and trigger payments with minimal human intervention. Such changes, however, often require companies to rethink long-established practices and management structures.

Technology historians note that major innovations have traditionally taken years, or even decades, to produce broad economic effects.

Electricity required decades before its impact became visible in productivity data, while the internet took more than a decade to fundamentally reshape commerce and business operations.

"The early years looked, from the inside, a lot like AI does now: spectacular promise, uneven results and an industry with every incentive to tell you the revolution was already here," said James Landay.

Landay said organizations often need years to adapt their structures and processes to take full advantage of transformative technologies.

"My sense is more like five to 10 years — not the next two or three," he said.

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