ETFs that focus on AI infrastructure, hyperscalers, and enterprise software are back on investors' screens because of a new Wedbush research note highlighting that the decline in enterprise software stocks is overdone.

Wedbush analyst Dan Ives said the artificial intelligence investment cycle remains in its early stages, describing the current phase as roughly "year 3 of what will be a 10-year cycle of this AI Revolution buildout." Large capital spending from Big Tech, governments, and enterprises could restructure technology leadership, and this trend can be captured by ETFs tracking AI, software, semiconductors, and cloud computing.

Software Panic May Be Overstated - ETF Implications

Ives recently re-added Salesforce Inc (CRM  ) and ServiceNow Inc (NOW  ) to his list of top 30 AI-focused stocks, indicating his belief that worries about permanent damage to traditional software business models from AI are overstated. "We believe the sell-off in tech stalwarts Salesforce and ServiceNow are way overdone and both these tech players will be core participants in the AI Revolution," noted Ives. He believes enterprises are unlikely to abandon existing software ecosystems quickly because of data security risks, integration costs, and established infrastructure.

That narrative could support funds heavily weighted toward enterprise software names for ETF investors. If the sector were to stabilize from recent volatility, ETFs tracking U.S. software or expanded AI software ecosystems, including those linked to cloud platforms, SaaS providers, and enterprise automation, could see fresh inflows.

The software sector has been behind wider equities this year due to concerns that AI agents could take the place of subscription-based software models. However, Ives expects AI deployment to one day complement, not displace, many enterprise platforms.

AI Capex Surge Boosts Broader Tech ETFs

Beyond software, Ives emphasized an increase in AI infrastructure spending led by hyperscalers like Microsoft Corp (MSFT  ), Alphabet, Inc (GOOG  ) (GOOGL  ), Amazon.com, Inc (AMZN  ) and Meta Platforms Inc (META  ), with an estimated $650 billion in AI-related capital expenditure in the year 2026 alone.

This trend has various implications across several types of ETFs. For instance, semiconductor ETFs such as the iShares Semiconductor ETF (SOXX  ) and the VanEck Semiconductor ETF (SMH  ) could stand to gain, particularly since leading chipmakers such as Nvidia Corp (NVDA  ), Advanced Micro Devices Inc (AMD  ), Broadcom, Inc (AVGO  ), and Taiwan Semiconductor Manufacturing Co Ltd (TSM  ) are leaders within the field of AI chips.

Besides this, exposure to cloud players such as Amazon, Alphabet, Microsoft, among others, is available through various ETFs such as the iShares Expanded Tech-Software Sector ETF (IGV  ), Fidelity Cloud Computing ETF (FCLD  ), and Themes Cloud Computing ETF (CLOD  ), who are sure to gain from the increased demand for AI technologies such as cloud services.

Additionally, cybersecurity ETFs such as the Global X Cybersecurity ETF (BUG  ) and First Trust Nasdaq Cybersecurity ETF (CIBR  ) could gain when more firms become engaged in the production, use, or development of AI technology, prompting attacks by digital threats, on which cybersecurity platforms spend significantly.

Ives also pointed to multiplier effects, noting that each dollar spent on advanced AI chips can drive several dollars of broader technology ecosystem investment.

"We continue to estimate for every $1 spent on an Nvidia GPU chip there is an $8-$10 multiplier across the tech sector which speaks to our firmly bullish view of tech stocks for 2026. Nvidia has changed the tech and global landscape as its GPUs have become the new oil and gold in the IT landscape with its chips powering the AI Revolution and being the only game in town for now," Ives said in the research note.

This dynamic typically favors diversified technology ETFs capturing multiple parts of the AI value chain.

AI Themes Expanding Beyond Software

The report also points to other investment areas in AI development, which include data infrastructure, cyber security, robotics, autonomous cars, and power generation linked to the development of data center infrastructure. These areas are also being represented in thematic ETFs spanning AI, automation, clean energy infrastructure, and advanced computing.

From the perspective of the ETF investors, the message may be less about stock selection and more about sector opportunities. If investment in AI continues to build momentum, the most diversified technology-focused ETFs, those covering chips, cloud, software, and cybersecurity, could provide the most upside potential while managing stock-specific volatility.

Bottom Line

In essence, Ives' thesis is simply restating that the selloff in software is merely a cyclical reset and not a structural decline. If that thesis holds, ETFs holding enterprise software and AI infrastructure providers might be a balanced play on what Ives believes to be a long-duration investment cycle in AI without betting the farm on any one tech darling.