An expected boon to IT spending driven by investments in artificial intelligence (AI) may take longer to materialize than expected.
A UBS survey of over 120 IT executives found that only 11 percent are running an AI application in a production environment. The other 89 percent expect to deploy AI applications in either the second half of this year or the first half of 2026.
Struggle to align AI initiatives with business strategies
On the plus side, the survey finds that 61 percent are already using AI products and applications in at least one area of their business. A separate survey conducted by Freshworks suggests most of that usage is being driven by individual end users rather than senior managers.
In fact, a third survey of over 2,300 enterprise decision-makers and influencers conducted by NTT Data finds that 83 percent of respondents work for organizations that have a well-defined generative AI (GenAI) strategy in place. Still, more than half (51 percent) have not yet aligned that strategy with their business plans. Only 43 percent said generative AI technologies are meeting expectations. Nevertheless, 97 percent still expect generative AI to have a material impact on improving productivity. However, only two-thirds (66 percent) view it as a revolutionary game changer.
Operationalizing AI presents a significant challenge
Organizations are finding it challenging to operationalize AI. Many of them still lack the skills and expertise required, which should create significant consulting opportunities for MSPs. The issue, of course, is that many MSPs themselves are still trying to develop the AI expertise required to deliver those services.
MSPs are naturally looking forward to a wave of AI applications that will be deployed on IT infrastructure that they will be asked to manage and secure. Yet, it may be a while before those applications reach a critical mass of adoption. In the meantime, MSPs should spend this time training their internal teams.. Given the overall demand for AI expertise, it’s not likely that MSPs will be able to hire enough IT professionals who already have AI skills, so most of the talent they rely on will need to be homegrown.
Continuous AI skills training is key to success
Unfortunately, identifying the required skills remains a moving target. The reasoning capabilities of the large language models (LLMs) that are at the core of most AI services continue to expand. Many of the tasks that GenAI agents might struggle to perform today adequately will become simpler for them to complete this time next year successfully. MSPs will need to assume that when it comes to acquiring and maintaining AI skills training will more or less need to be continuous.
In the meantime, MSPs need to ensure they remain actively engaged with customers who are less certain than ever about their IT strategies’ evolving. After all, it’s during these times that customers look for guidance from the MSP partners they trust most.
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