CIOs eager to scale AI despite difficulty demonstrating ROI, survey finds

CIOs rank AI as a top priority alongside cybersecurity for IT departments. However, barriers such as adoption speed and security concerns hinder rapid AI integration, according to a new survey.

There is a promising surge in the use of AI technologies across various industries. Of the 750 CIOs around the world surveyed by Lenovo, 81% said they are already leveraging third-party AI Tools or deploying a mix of third-party and proprietary AI.

The survey underscores a significant shift in the role of CIOs, who are now being evaluated primarily on business outcomes rather than operational maintenance. This transition has propelled AI and machine learning to the forefront, with 51% of CIOs identifying these technologies as among their most urgent priorities, alongside cybersecurity, highlighting their crucial role in driving organizational success.

“Today’s CIOs are working in a tornado of innovation. After years of IT expanding into non-traditional responsibilities, we’re now seeing how AI is forcing CIOs back to their core mandate,” Ken Wong, president of Lenovo’s solutions and services group, said in a statement. There is a sense of urgency to leverage AI effectively, but adoption speed and security challenges are hindering efforts.

Despite the enthusiasm for AI’s transformative potential, which 80% of CIOs surveyed believe will significantly impact their businesses, the path to integration is not without its challenges. Notably, large portions of organizations are not prepared to integrate AI swiftly, which impacts IT’s ability to scale these solutions. CIOs were least likely to identify as AI-ready business areas such as new product lines (22% of respondents), corporate policy on ethical AI use (24%), or their supply chain (26%) as the least AI-ready, while 49% rated their IT departments’ own technical skills as AI-ready.

According to a separate study on the AI readiness of Indian enterprises conducted by EY and Indian IT industry body Nasscom, enterprises are also holding back the deployment of AI due to concerns about data security, privacy, brand reputation, and the safety and security of people and equipment.

Security and AI

Among the IT leaders taking a cautious approach to AI is Saurabh Gugnani, the global head of cyber defense and application security at Dutch compliance firm TMF Group. “Adopting AI poses several security challenges, such as data privacy, attack vulnerability, and strict regulation compliance. Protecting sensitive data and ensuring the integrity of AI models against cyber threats, such as adversarial attacks, are key concerns for CIOs,” he said.

Additionally, traditional security measures often fall short of addressing the unique demands of AI technologies. To mitigate these risks, CIOs must implement AI-specific security protocols and conduct regular security audits, which take time, he added. “Crucially, framing comprehensive policies that govern AI use, ethical standards, and security practices is essential to safely integrate AI into organizational workflows, ensuring a secure and compliant adoption process.”

For Neeraj Kumar, CTO of Arkreach, the speed with which AI technologies are being developed itself poses a threat. “Even tech giants like Google and Meta sometimes rush to launch immature tech, leading to a wreckage of failed AI products. However, rushing to ship some underdeveloped AI solutions in your product pipeline because of FOMO (fear of missing out) is not a good idea. It can throw your entire delivery system into meltdown,” he said. “It is time to shift away from the launch first, think later, mentality and concentrate on creating the future by not repeating yesterday’s mistakes, even if it leads to a delay.”

Another challenge is the critical shortage of skilled professionals that, according to Gugnani, makes it challenging and costly for companies to hire and retain talent in machine learning, data science, and AI integration. “Upskilling existing staff to manage AI technologies requires significant time and financial investment. Many organizations hesitate to commit the necessary resources, slowing the integration of AI capabilities,” he said.

The ROI dilemma

IT leaders also face the ongoing challenge of demonstrating and calculating the return on investment (ROI) of technology initiatives. The Lenovo survey found that 61% of CIOs find it extremely challenging to prove the ROI of their tech investments, with 42% not expecting positive ROI from AI projects within the next year.

One of the main difficulties is calculating ROI to convince CFOs to approve budgets, and this challenge is also present when considering AI adoption, according to Abhishek Gupta, CIO of Dish TV. “Quantifying tangible benefits such as cost savings, productivity improvements, and top-line growth is relatively straightforward. However, calculating returns on softer aspects, such as improvements in user experience, can be challenging,” Gupta said. “Ultimately, AI initiatives should be viewed as a necessary business investment that can yield results over time as the portfolio of AI projects begins to deliver results.”

Resource constraints and investments

Focusing resources on AI also affects IT sustainability efforts, the survey found, with 38% of CIOs reporting that they had de-prioritizing sustainability initiatives as a result. However, a majority still view AI as a net positive for meeting IT sustainability goals, with only 22% saying that the environmental impact of AI workloads will make it harder to meet them.

Financial and human resources are another area of concern: While 96% of CIOs anticipate increasing their investments in AI, only around 20% expect their IT budgets to grow by more than 10% to accommodate that expenditure.