GenAI adopters tentative now but confident soon: Survey

The U.S. is projected to see $1T in annual productivity growth by 2032 through the use of generative AI. The GenAI watcher making the prediction also expects the global economy to exit early adoption and enter confident implementation between next year and 2030.

The observer is the global business consultancy Cognizant. In a new survey-based report, the company advises senior leadership in all industries and sectors to focus GenAI more on growth than cost-cutting. 

After all, the report authors comment, GenAI initiatives are complex and—in some cases—costly. “As such, the main rationale for pursuing them needs to be business growth, not workforce reductions,” they write. 

To conduct the survey on which the report is based, Cognizant queried 2,200 business executives across 23 countries and 15 industries about their GenAI strategies. 

Cognizant analysts drew five key observations from the responses. 

1. Strong leadership commitment highlights AI’s strategic importance.

With 71% of respondents rating their leadership commitment in the highest two levels of maturity, it is clear that leaders are prioritizing generative AI adoption, the authors write. “Executives recognize that generative AI is crucial to business success,” they add, “with 74% of respondents rating it as important or critically important.” More: 

‘The urgency is palpable, with 70% believing their business is not moving fast enough with adoption.’

2. Strategies emphasize productivity over cost cutting. 

“In our study, the productivity gains of generative AI were a bigger strategic priority than using the technology to revamp business and operating models or drive disruptive innovation,” the authors report. “This aligns with a key promise of generative AI: enhancing employee efficiency and enabling more output.” Meanwhile:

‘Leaders recognize that generative AI is not merely a tool to reduce costs while maintaining the status quo. Instead, it represents a catalyst for business growth.’

3. Organizational agility remains a major challenge. 

Confidence in organizational agility is shaky at best, with only 36% of respondents rating this area as mature. “These low ratings were based on respondents’ assessment of their change management capabilities and the new processes needed to manage AI lifecycles and scale AI initiatives,” the authors clarify. 

‘Ultimately, integrating generative AI will require a fundamental rethink of existing processes to leverage these innovations. Few organizations currently feel prepared to undertake this challenge.’

4. Talent management shifts toward reskilling over reduction. 

A look at respondents’ talent strategies “reveals a mix of practical skill-building endeavors and some wishful thinking,” the authors write. More than half (54%) are focusing on upskilling employees for roles that critically need AI capabilities, they note, while 25% plan organization-wide training programs to instill foundational AI skills across the board.

‘Despite internal training efforts, 38% of respondents still plan to address skills gaps through external hiring—a potentially challenging and costly prospect given the global shortage of skilled workers.’

5. Confident enterprises turn tech debt into opportunity. 

Only 32% of respondents rate their technology as mature. These low ratings “reflect respondents’ concern that their [enterprise] had not yet evolved their tech infrastructure and data to accommodate generative AI needs,” the authors remark. “While 54% gave their data quality and cleanliness ratings of ‘excellent’ or ‘good,’ respondents were much less confident in their organization’s ability to access and secure data, with half of the respondents rating these areas at the lowest maturity levels.”

‘This gap illustrates that even if it’s of high quality, data is useless if it’s not accessible and secure for use in AI applications.’

There’s more from Cognizant on the survey findings and conclusions here.