The hype surrounding artificial intelligence is at a fever pitch across the tech world. AI is dominating headlines and conference discussions. There is a lot of promise that large-scale language models (LLMs), machine learning (ML), and neural networks will deliver unparalleled efficiency gains, predictive capabilities, and customized interactions. These innovations aim to reduce costs, restructure business operations, and unlock new growth and profitability opportunities.
However, this is an optimistic prediction and not the current reality.
Market analysts report that overall IT spending is growing at a double-digit rate of 20% to 27% annually. This is great, but it's also a modest starting point. Actual AI spending in 2023 hovers between $20 billion and $25 billion. While significant, this number is modest compared to spending on cloud computing, security, and business software.
Some technology analyst firms estimate spending on AI in the hundreds of billions of dollars. Some predictions even suggest that spending on AI could reach $300 billion by 2026. Such numbers seem plausible considering the sales of traditional technologies that incorporate AI as a primary component or an auxiliary feature.
However, despite the widespread use of chatbots, virtual assistants, recommendation systems, and analytics tools, AI is not driving as much growth in enterprise IT spending as other innovative technologies such as cloud, security, and mobility. Is not …
Technology vendors informed Channelnomics of a trend in which companies are postponing or canceling IT projects to save money and taking a “wait-and-see” attitude toward advances in AI. Businesses are anticipating the arrival of AI innovation and prefer to wait for the latest advances rather than invest in current technology. One prominent technology vendor told Channelnomics that its quarterly revenue declined as AI constrained customer spending across most product categories.
In the technology sector, vendors access the market through indirect channels. This system involves resellers and service providers who are responsible for the pre-sales and post-sales aspects of technology product adoption and deployment. Technology vendors are rallying channel partners for the AI revolution, emphasizing the need to strengthen infrastructure and hone relevant skills to meet market demands.
Still, the irony is obvious. Many vendors don’t have a compelling AI story or product for their channels or customers. While many technology companies are announcing AI projects and product developments, the reality is that “AI cleaning” is more popular than genuine products. AI is the current buzzword, so vendors tout it as a selling point even if they don't have a formal product in their lineup. To put it humorously, “If it's machine learning, it's probably coded in Python. If it's artificial intelligence, it's probably written in PowerPoint.”
AI is now a feature. Companies such as Microsoft, Google, and Salesforce are integrating his AI capabilities into their products. While these enhancements are laudable, they don't necessarily translate into additional revenue streams. Automatic updates for cloud services may ensure customer retention, but it doesn't necessarily generate new sales.
Even if AI capabilities drive new revenue, how will vendors categorize it? Will the revenue be broken down into AI, CRM, productivity, networking, security, or other key technology categories? ?
The AI boom is just around the corner. Although the foundations are being laid, the big impact of AI is still on the horizon. The technology industry and its channel partners are preparing to take advantage of the peak demand for AI. But hurdles still exist, from identifying use cases to addressing integration, data management, skills acquisition, and ethical considerations.
Addressing these obstacles requires collaboration between researchers, vendors, channel partners, and consumers. This channel leads adoption by championing use cases, implementing solutions, upskilling employees, and providing ongoing optimization and support.
Once these obstacles are resolved and true AI products emerge, passionate customers will be ready to invest to reap the promised productivity and profit gains. But for now, the full transformative power of AI is still waiting to be realized.
