ROI Remains Greatest AI Adoption Barrier, Despite Three-Fold Spend Increase: Lenovo Study

Considering the huge number of benefits already available and a potential to deliver even more in the near future, Artificial intelligence use will reach mainstream levels of adoption as organisations devote a greater slice of their IT budgets to AI implementations. As the use of AI is growing by leaps and bounds, IT decision-makers expect that spending on it will nearly triple in 2025 compared to last year, according to new IDC research commissioned by Lenovo. 

However, critical barriers remain in AI adoption, including uncertain financial returns on AI investments and gaps in organisational readiness. Not just that, ever cheaper AI tools are threatening to upend the way things have been going considering that so far it was being assumed that this technology came at a very high cost.

The biggest obstacles to AI adoption are financial risk and uncertain ROI, even though the majority of AI use cases have fulfilled business expectations. The discrepancy between rising AI investments and widespread scepticism about its usefulness among decision-makers exacerbates this friction.

Despite the forecasted surge in AI spending, business decision-makers are not unanimous in their optimism of its impact. The study revealed that 37% of management remains sceptical or have reservations towards AI, while approximately nine of ten AI-adopting respondents, mostly made up of IT professionals, said that AI has met their expectations. This highlights a significant divide between the unbound potential of AI and business confidence.

Because generative AI use cases are being adopted more quickly, IT professionals anticipate that by 2025, AI will make up over 20% of tech budgets. Although just 11% of businesses presently use gen AI-powered apps, in the upcoming year, this percentage is predicted to nearly quadruple to 42%.

The study also highlighted which areas will see the highest levels of adoption. It indicated that IT operations, software development and marketing departments are expected to see the highest level of gen AI applications.

The study identified a number of issues with organisational readiness. More than half of organisations lack an AI Governance, Risk, and Compliance policy, despite ethical concerns and biases in AI and machine learning being identified as the most complex or risky component of AI.

Organisations must also train and upskill employees, update IT systems to integrate AI agents and assistants efficiently, and set up organisational procedures that guide the ethical and responsible use of these tools if they hope to achieve the productivity increases that these technologies offer.

The study highlighted the importance of data quality in delivering successful AI implementation. The most crucial elements of successful AI deployments were data sovereignty and compliance, as well as having access to high-quality data. 

In contrast, the most common causes of AI failures include problems with data quality, IT expenses, and integrating AI with current systems and procedures. For this reason, according to 33% of respondents, their companies plan to build data management capabilities in 2025.