The hype surrounding artificial intelligence (AI) is hitting a speed bump as businesses adopt a cautious “wait and see” approach. Even though people said artificial intelligence would make things super efficient and amazing, it has not turned out as awesome as they hoped.
Recent reports from market analysts reveal that while overall IT spending is growing impressively at double-digit rates, AI spending for 2023 remains modest, ranging between $20 billion and $25 billion. This is a fraction compared to the spending on cloud computing, security and business software, leaving AI somewhat in the shadows.
Some predictions tout AI spending reaching the hundreds of billions, even reaching $300 billion by 2026. However, a noticeable trend is emerging: businesses are delaying or canceling IT projects to conserve budgets, adopting a cautious stance toward AI evolution.
Tech vendors, the middlemen connecting AI developers with businesses, are feeling the pinch. Channelnomics reports that quarterly revenues of a prominent tech vendor suffered due to businesses holding back on spending across various product categories, attributing it to the uncertainty surrounding AI.
It is a bit funny – tech sellers are telling businesses to get ready for the big AI revolution by strengthening their systems and learning new skills. But the funny part is, a lot of these sellers don’t really have cool stories or products about AI to back up their advice. “AI washing,” the practice of flaunting AI as a selling point without a genuine product, is becoming more prevalent. As one tech insider humorously puts it, “If it’s machine learning, it’s probably coded in Python. If it’s artificial intelligence, it’s likely written in PowerPoint.”
In the current landscape, AI functions more as a feature than a revenue stream. Big companies like Microsoft, Google and Salesforce use AI in their stuff. However, it mostly helps them keep their current customers happy instead of bringing in lots of new ones. The challenge lies in categorizing AI features – should they fall under AI, CRM, productivity, network, security, or another primary tech category?
Even though there are problems, the tech industry and its friends are getting ready for a big AI boom. They need to work together – researchers, sellers, friends and customers – to figure out how to use AI, put it together, handle information, learn new things, and deal with ethical issues.