2026 will be the year of monetization of artificial intelligence, says expert
Global spending on artificial intelligence is expected to grow significantly in 2026, driven by expanding AI infrastructure and broader adoption of AI-enabled software and devices. Instead of being concentrated just in the big tech giants, this investment is increasingly coming from a broader base of companies.
Gartner predicts global spending on AI will surpass $2 trillion by 2026, led by the integration of AI into products such as smartphones, PCs and other critical infrastructure. Regional economic conditions, regulatory environments and access to qualified professionals will influence the speed at which each company scales its initiatives. Not all companies will invest in major hardware upgrades or move forward with large-scale deployments at the same pace.
Also read: Study shows how people are using artificial intelligence in 2025
To understand how the market is shaping up, I spoke with Dan Ives, managing director and senior equity research analyst at Wedbush Securities. “We believe 2026 will be the year of AI monetization as infrastructure paves the way for enterprise and consumer use cases,” said Ives. “This is just the beginning, and we look forward to an optimistic 2026 for the technology sector and the AI revolution.”
Wedbush analysts wrote in a report released Monday morning that they are seeing AI-related businesses accelerating faster recently, and that this momentum is expected to extend into 2026 as end-user companies accelerate implementations.
Analysts also reject the idea that the market is showing signs of an AI bubble, highlighting that adoption is still at a very early stage as CIOs and business leaders assess where AI can generate real value within their organizations.
A recent Deloitte report also predicts continued expansion in AI investments in sectors such as technology, media and telecommunications, but emphasizes that the focus will shift from experimentation to execution.
“New fundamental models, or even new enterprise applications with shiny ‘smart agents,’ continue to impress — but translating them beyond pilots and testing requires work that is often less glamorous, such as data organization, integration into existing workflows, governance, new pricing models, and regulatory compliance,” the report says.
These projections indicate a common tipping point: 2026 will be less about impressive AI models and more about transforming existing capabilities into measurable business results.
