When ChatGPT launched on November 30, 2022, generative AI exploded into the public consciousness. Less than two years later, it has transformed the world. Consumers and businesses alike use large language models (LLMs), and generative AI solutions now fuel processes ranging from data management to software development.
But the generative AI revolution, like the original Industrial Revolution, is distributed. The spinning jenny emerged from the factory floor, not the boardroom, and it is practitioners—not the C-suite—who are driving innovation.
Our 2025 Generative AI Innovation Report found that the V-suite sees opportunities that the C-suite may well miss. Harnessing the power of a bottom-up approach requires confidence, courage, risk tolerance, and people skills.
“Harnessing the power of a bottom-up approach requires confidence, courage, risk tolerance and people skills.”
—Daniel Liebermann, Managing Director at Publicis Sapient
The V-suite sees back-office generative AI potential that the C-suite misses. More than half of C-suite respondents ranked generative AI as extremely important to customer service, customer experience, and sales. Just 12 percent of the C-suite thought generative AI would be extremely important in finance over the next three years, as opposed to 30 percent of their executives.
The V-suite is aware of generative AI tools the C-suite ignores. Almost 60 percent of CEOs thought chatbots and other generative AI tools would be extremely important in customer service, as opposed to just 24 percent of customer service specialist executives. Just 17 percent of CEOs thought AI agents and automation would be extremely important, compared to 33 percent of data and analytics executives.
The C-suite and V-suite have different attitudes toward generative AI risk. The C-suite was more than twice as concerned about generative AI risk compared to the V-suite: 51 percent of the C-suite were more concerned about risk and ethics of generative AI than other emerging technologies, as opposed to just 23 percent of V-suite respondents.
More than 99 percent of respondents felt their organizations were making at least some progress with generative AI, even if it was only in defining use cases. From shopping assistants to content creation to contract generation, organizations and individuals are already using AI tools in their workflow. AI is integrated across many enterprises in transcription, translation, and help with emails, spreadsheets, and presentations.
But most experimentation is taking place far from the C-suite, so it’s as hard for leaders to learn how individuals within their organization are using ChatGPT or Microsoft Copilot as it is to understand how they’re using the internet. Many executives don’t know how far their organization is along the generative AI adoption journey.
Harnessing the power of this decentralized, bottom-up approach unlocks value—but presents real risks. Firstly, there is the danger of “shadow IT,” where different sections of the business create their own IT policy, leaving the organization exposed to reputational, regulatory, and data security risks. Secondly, entities risk duplicating effort as different teams repeat projects colleagues have already attempted.
Nobody knows what generative AI maturity looks like. Organizations that described themselves as of limited maturity were doing roughly the same things as organizations that described themselves as very mature. Almost exactly the same percentage of limited maturity (35 percent) and very mature (34 percent) companies were initially exploring publicly available generative AI tools.
“It’s as hard for leaders to learn how individuals within their organization are using ChatGPT or Microsoft Copilot as it is to understand how they’re using the internet.”
—Daniel Liebermann, Managing Director at Publicis Sapient
Transformative generative AI use cases the C-suite may ignore include synthetic data, data quality management, natural language search, and software development. Generative AI search is yielding a veritable goldmine of data for early adopters, while synthetic data is informing decision-makers and customer choice algorithms alike.
To move forward with generative AI adoption, executives need to create a balanced portfolio of innovation projects rather than committing funds solely to flagship projects. Leaders should:
“Just like staking out your first e-commerce position 25 years ago, that’s likely to involve some failures.”
—Daniel Liebermann, Managing Director at Publicis Sapient
More broadly, organizations need to work to upskill people at all levels to maximize the value of generative AI in the enterprise—which is likely to change as the technology evolves. They need to encourage and motivate team members at all levels to seek out innovation and disruption and find opportunity in a rapidly changing world.
“Organizations need to encourage and motivate team members at all levels to seek out innovation and disruption.”
—Simon James, Managing Director, Data & AI at Publicis Sapient
“A zero-risk policy is a zero-innovation policy.”
—Simon James, Managing Director, Data & AI at Publicis Sapient
iResearch conducted global online research in 12 countries across North America, Europe, Middle East, and Asia Pacific in June and July 2024 to create this Generative AI Innovation Report. Respondents were drawn evenly from consumer products, energy & commodities, financial services, healthcare, retail, telecommunications, media & technology (TMT), transportation & mobility, and travel & hospitality. They worked for companies with an annual revenue between $1 billion and $10 billion, either at the C-suite level or at the VP level in strategy and innovation, customer experience, or data and analytics.
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