In a bold move that unites finance with cutting-edge innovation, Wedbush Fund Advisers has launched the Ives AI Revolution ETF, a thematic exchange-traded fund built on proprietary artificial intelligence (AI) research from tech analyst veteran Dan Ives. Named after Ives, a managing director at Wedbush Securities, the ETF capitalizes on the exponential advancements in AI that are disrupting virtually every sector, from enterprise software and semiconductors to cloud infrastructure and robotics. This product represents not just a bet on technology but a strategic framework for accessing top-tier, future-forward equities based on deep research grounded in Ives’s decades-long expertise in the tech sector.
The Vision Behind the Ives AI Revolution ETF
The ticker “BOTS“, listed on the Cboe exchange, signifies more than a clever acronym—it emphasizes the fund’s focus on companies leading the AI disruption wave. According to an exclusive report by Reuters on June 4, 2024, Wedbush structured this ETF as an actively managed vehicle that leans into Dan Ives’s proprietary frameworks to determine exposures across approximately 50 AI-centric stocks. Ives’s strategy combines fundamental and technical screens along with qualitative assessments to uncover what he describes as the “fourth industrial revolution” (Reuters, 2024).
Ives, who has previously gained national recognition through accurate calls on FAANG stocks and Tesla, contends that AI is not just another buzzword but the core platform shift upon which the next generation of corporate innovation and capital investment will be built. This thesis finds growing affirmation in recent AI industry developments: OpenAI’s GPT-4o launch, Nvidia’s record quarterly earnings, and Microsoft’s Copilot expansion—each reflecting real monetization timelines and not just experimental nascent tech (OpenAI Blog; NVIDIA Blog).
How BOTS Selects Its Holdings: A Proprietary AI Evaluation Framework
Unlike traditional thematic ETFs that passively track an index, BOTS is an actively managed fund which enables faster allocation shifts based on new market trends or breakthroughs in machine learning, generative AI, or robotics. According to Wedbush’s filings and statements, Dan Ives applies a comprehensive framework combining several types of data:
- Quantitative Assessments: Financial metrics such as earnings growth in AI-related divisions, R&D expenditure, and EBITDA margins.
- Technical Signal Integration: Momentum indicators, moving averages, and price-volume analyses to capture breakout AI growth stocks.
- Qualitative Research: Management interviews, product roadmap insights, M&A patterns in AI, and patent activity tracking.
As of June 2024, early disclosed holdings in the ETF include blue-chip AI trailblazers such as Nvidia, Microsoft, AMD, Palantir, C3.ai, Snowflake, and Alphabet. These corporations are among the most critical players in AI software platforms, large language models, edge computing infrastructure, and AI-integrated analytics (VentureBeat; AI Trends).
Key Drivers of the AI Investment Boom
Economic Expansion Through AI Adoption
Global investment in AI, projected to reach over $200 billion in 2025, is not merely speculative—it reflects real productivity gains and margin expansion right in the boardrooms and coding platforms of Fortune 500 companies (McKinsey Global Institute). AI is improving decision-making accuracy, inventory management, customer interaction analysis via generative models, and supply chain automation. The ETF’s top holdings embody these themes in action. For example, Microsoft’s Copilot integration across enterprise suites is increasing employee productivity while Nvidia continues to dominate AI GPU markets for deep learning and inference tasks (OpenAI Copilot documentation; Nvidia Earnings).
Geopolitical and Corporate Investment Pressures
The Biden administration’s executive orders on AI safety and developments in EU regulation around AI ethics haven’t slowed momentum. In fact, geopolitical focus has driven more capital into AI defenses—cybersecurity, national language models, and critical infrastructure resilience. According to Gartner, more than 75% of enterprises plan to significantly increase AI spending by mid-2025, especially in financial services, defense, and manufacturing sectors (Gartner).
Infrastructure and Semiconductors—The Backbone of AI
Every AI model—from OpenAI’s GPT-4o to Google’s Gemini—requires vast computing infrastructure. Companies like Nvidia and AMD dominate the AI chip market, delivering the processing power required for both training and inference. AI chip demand is expected to triple from 2024 to 2027 (MarketWatch, 2024). Capital-intensive platforms like AWS and Microsoft Azure are expanding their GPU fleets to accommodate enterprise needs, pushing a second-order effect into data center REITs and cloud operators—many of whom are secondary plays held inside BOTS.
BOTS vs. Competing AI-Themed ETFs
The AI-centric ETF space has grown competitive, featuring products such as the Global X Robotics & Artificial Intelligence ETF (BOTZ), the iShares Robotics and AI Multisector ETF (IRBO), and the ROBO Global Artificial Intelligence ETF. However, BOTS differentiates itself through the combination of human insight and active rebalancing.
| ETF | Strategy | Number of Holdings | Expense Ratio |
|---|---|---|---|
| BOTS (Wedbush) | Active, Selective AI-centric research | ~50 | 0.85% |
| BOTZ (Global X) | Passive, Index-tracking | ~40 | 0.68% |
| IRBO (iShares) | Equal-weighted, multisector | ~100 | 0.47% |
The clear edge with BOTS is its agility. Passive funds often take months to recalibrate even after major AI breakthroughs. For example, few passive funds reacted rapidly to the announcement of OpenAI’s GPT-4o in April 2024, which significantly advanced voice-to-action interactivity models (MIT Technology Review).
AI Trends Supporting BOTS’ Strategy
New AI trends directly back Ives’s thesis. Consider OpenAI’s latest feature releases which power integrations with enterprise apps through multi-modal capabilities. Amazon AWS’s Bedrock expansion now supports fine-tuning across foundational models, enhancing personalization in use cases from marketing to insurance underwriting (Technology Review). At the same time, models like Google’s Gemini and Anthropic’s Claude 3 are narrowing the race in language model supremacy, underscoring the broader AI toolkit growth trajectory (DeepMind Blog).
BOTS leverages these developments indirectly by investing in firms at all infrastructure layers—chips, cloud app developers, enterprise deployers, and end-use vertical adopters—essentially offering vertical exposure to the AI stack.
Looking Ahead: Risks and Opportunities
While BOTS offers compelling exposure, risks persist. Regulatory scrutiny—particularly through the FTC and European Commission—may add legal hurdles for firms deploying sophisticated AI systems without clear transparency policies (FTC News). Additionally, the AI landscape remains rapidly evolving. Dominance today may not predict innovation tomorrow, making active management all the more pertinent.
Still, with data, cloud, chips, and AI workflows converging fast, investors seeking long-term tech exposure would find in BOTS a curated microcosm of the modern AI revolution, managed by one of Wall Street’s most technology-savvy teams.