Global business leaders are embracing generative AI (GenAI) as a transformative force, with 97% of CEOs expecting it to have a material impact on their organizations.
According to a report from NTT Data, nearly all surveyed executives are planning further investments in the technology, signaling its growing importance across industries.
Despite this optimism the study found barriers remain, with 90% of leaders citing legacy infrastructure as a key obstacle to effectively leveraging GenAI.
Just over half (51%) of respondents admitted their GenAI strategies are not yet aligned with broader business goals.
While 83% reported having robust GenAI teams, the misalignment hinders the return on investment and satisfaction with current outcomes.
GenAI is already being deployed across industries, with top use cases including personalized service recommendations, quality control and R&D.
Two-thirds of C-suite respondents see GenAI as a “game changer” over the next two years, identifying key benefits such as enhanced productivity, sustainability, compliance and security.
Anurag Malik, president & CTO of ContractPodAi, said IT leaders can bridge the gap for AI adoption by taking a phased approach that prioritizes measurable value.
“The first step must be to evaluate computational resources, data quality and quantity and infrastructure readiness,” he said. “Determine the level of AI and ML expertise within the team.”
Malik said companies must ensure their systems can handle the operational demands of AI, and they must have high-quality, relevant data to reduce the risks of models producing irrelevant outputs that influence decision-making.
“The next step to adopting GenAI is addressing immediate pain points and demonstrating ROI with tools like productivity dashboards that quantify time saved and operational efficiencies,” he said.
He recommended starting with smaller, more manageable projects to create early success stories, and build confidence and momentum for broader adoption.
“Identify high-impact areas where GenAI can add value,” he added.
As AI becomes more ingrained in the organization, IT leaders can work with teams to reimagine workflows, focusing on how AI can enhance processes and drive greater efficiency instead of replicating existing roles.
Employee Readiness Challenges Persist
Employee readiness remains another challenge, with about two-thirds (67%) of respondents noting a skills gap in their workforce, prompting many organizations to plan training initiatives.
Concerns around ethics, safety and security also persist. The report found that 72% of organizations lack clear GenAI usage policies, while 82% of leaders see unclear government regulations as a hindrance.
Additionally, 45% of CISOs expressed feeling “pressured or overwhelmed” by the risks associated with GenAI adoption.
Despite these challenges, optimism abounds, with more than two-thirds of respondents describing themselves as “excited” and “amazed” by the potential of GenAI to reshape industries.
Daniel Barchi, SEVP, CIO at CommonSpirit Health, said every initiative they undertake, including GenAI, must have a meaningful impact on either efficiency or output.
“By marrying ROI-focused prioritization with an evergreen AI governance model, IT leaders can strategically invest in AI while remaining nimble to changes in the regulatory landscape,” he said.
He added the company is participating in Gen AI working groups organized by coalitions including CHAI and Vital AI and they have signed the Rome Call for AI Ethics.
“To properly steward this innovation, we complement AI tools with a dedicated data governance team that guides our employees in data literacy and responsible AI use,” Barchi explained.
He said while progress has been made, organizations should view GenAI as an ongoing improvement journey, rather than a destination.
“Even before the GenAI boom, we have been building AI-powered components into our technology stack and clinical processes for years,” he said. “AI does not need to be complicated.”
Barchi explained the company’s strategy is to look for ways to automate routine processes, enhance established systems, and reduce manual bandwidth so IT teams can spend more time solving the problems that matter most to those they serve.
