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AI Is Dampening Tech Spending, For Now
Anticipation of AI advancements causes enterprises to hesitate, but a spending surge is on the horizon.
3 Min Read
Bulat Silvia via Alamy Stock
The hype surrounding artificial intelligence has reached a fever pitch across the technology landscape. AI dominates headlines and conference discussions. Promises abound that large language models (LLMs), machine learning (ML), and neural networks will usher in unparalleled efficiency gains, predictive capabilities, and tailored interactions. These innovations aim to reduce costs, reshape business operations, and unlock novel growth and profitability opportunities.
However, that’s an optimistic projection, not the current reality.
Market analysts report that overall IT spending is growing at double-digit rates -- between 20% to 27% annually. While this is impressive, it’s also starting from a modest base. The actual AI spending for 2023 hovers between $20 billion and $25 billion. Though significant, this figure is modest compared to spending on cloud computing, security, and business software.
Some technology analyst firms estimate AI spending in the hundreds of billions of dollars. One prediction even suggests AI spending could reach $300 billion by 2026. Considering conventional technology sales incorporating AI as a primary component or supplementary feature, such a figure seems plausible.
Yet, despite the widespread use of chatbots, virtual assistants, recommendation systems, and analytic tools, AI hasn’t spurred the growth in enterprise IT spending that other revolutionary technologies like cloud, security, and mobility have.
Technology vendors informed Channelnomics of a trend: Businesses either delay or cancel IT projects to conserve budgets, adopting a "wait and see" stance towards AI evolution. As businesses anticipate the incoming wave of AI innovations, they prefer to await the latest advancements rather than invest in current technologies. One prominent tech vendor revealed to Channelnomics that their quarterly revenue suffered due to AI curtailing customer spending across most product categories.
In the tech sector, vendors access the market through indirect channels. This system involves resellers and service providers responsible for pre- and post-sale facets of tech product adoption and deployment. Tech vendors rally their channel partners for the AI revolution, emphasizing the need to fortify infrastructure and hone relevant skills to meet market demand.
Yet, the irony is palpable. Many vendors lack compelling AI narratives or products for their channels and clientele. While numerous tech companies announce AI projects or product development, the reality is that "AI washing" is more pervasive than genuine products. Since AI is the current buzzword, vendors flaunt it as a selling point, even without a legitimate 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 likely written in PowerPoint.”
Today, AI functions as a feature. Corporations like Microsoft, Google, Salesforce, and others integrate AI capabilities into their offerings. While these enhancements are commendable, they aren’t always additional revenue streams. Automated updates to cloud services might ensure customer retention but might not necessarily trigger fresh sales.
Even if AI features catalyze new sales, how do vendors categorize them? Would the revenue fall under AI, CRM, productivity, network, security, or another primary tech category?
The AI boom is imminent. Although the foundations are being laid, AI’s profound influence remains on the horizon. The tech sector and its channel partners are gearing up to capitalize when AI demand peaks. Yet, hurdles persist, from identifying use cases to grappling with integration, data management, skill acquisition, and ethical considerations.
Addressing these obstacles demands collaboration among researchers, vendors, channel partners, and consumers. The channel will spearhead adoption by championing use cases, implementing solutions, upskilling workforces, and offering continued optimization and support.
As these obstacles dissolve and genuine AI products emerge, eager customers will be ready to invest to gain the promised productivity and profit boosts. Yet, currently, AI’s full transformative power is still awaiting realization.
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