In a recent discussion, Gartner has cautioned that companies integrating artificial intelligence (AI) technology could see their expenses increase significantly, potentially by as much as 1000 percent. The findings were presented during Gartner's Symposium in Australia, emphasizing the need for careful oversight in handling both the financial and emotional impacts that AI could bring.
Financial Implications of AI
Gartner Vice President and Analyst Mary Mesaglio discussed how easily companies might overspend on generative AI, akin to the early surprises faced during the initial adoption of cloud services. Mesaglio mentioned that costs for AI could be underestimated by large margins, suggesting a possible spike in expenditures ranging from 500 to 1000 percent.
Several factors could contribute to this financial strain, including increased charges from vendors and excessive spending on cloud resources during AI experiments. Mesaglio advised against using AI for simple inquiries better suited for traditional searches, as this could lead to needless expenses. She noted that longer and more complex user queries could drive up costs under token-based pricing structures.
Emotional and Productivity Effects
Gartner also addressed how AI adoption might influence employee morale and overall productivity. Mesaglio introduced the term “productivity leakage,” referring to situations where the time saved by AI—estimated at 43 minutes per day per worker—doesn't necessarily translate into more productive work. Instead, employees might use this time for personal tasks, such as getting a coffee, potentially resulting in a loss of 10 to 30 percent of AI's intended productivity gains.
It was highlighted that AI's advantages might not be evenly distributed among all employees. For instance, a new call center worker might gain substantial productivity from AI, while a more experienced employee might not feel the same benefit due to their existing expertise. The imbalance can lead to frustration among seasoned employees if their less-experienced colleagues achieve similar performance levels with AI assistance.
Strategizing AI Integration
Gartner recommended a tailored approach to AI adoption based on industry needs and the pace of AI-driven changes within each sector. Industries not experiencing significant transformations due to AI can adopt a gradual approach with a focus on a few proof-of-concept projects. On the other hand, companies aiming to be at the forefront of AI progress should consider an accelerated strategy.
The analysts reassured that organizations are not bound by vendor timelines and can set their own pace for AI adoption, allowing them to develop strategies that match their unique requirements and operational contexts.
Microsoft Issues a Similar Warning
Gartner's concerns of the cost implications of AI adoption have been echoed by Microsoft. Arun Ulag, corporate VP for Azure Data at Microsoft, pointed out the financial implications of extensive AI projects on IT budgets during the Citi 2024 conference.
Ulag noted that firms are reallocating financial resources to support AI projects, often at the expense of other business functions. The increased emphasis on AI necessitates a rebalancing of budgets. As he stated, “If this expenditure increases significantly, then something else will need to adjust,” implying the need for careful resource allocation to fund AI initiatives.
The use of large language models in customer service and other applications presents unique challenges. Mr. Ulag highlighted the potential for these models to exhibit unpredictable behavior, leading to AI hallucinations or the generation of inappropriate content. Despite Microsoft's commitment to responsible AI practices, he acknowledged that the technology still faces limitations and may not always produce the desired outcomes.
