AI Research
Reckless Race for AI Market Share Forces Dangerous Products on Millions — With Fatal Consequences
WASHINGTON, DC — SEPTEMBER 4, 2025: OpenAI CEO Sam Altman attends a meeting of the White House Task Force on Artificial Intelligence Education in the East Room of the White House. (Photo by Chip Somodevilla/Getty Images)
In September 2024, Adam Raine used OpenAI’s ChatGPT like millions of other 16-year-olds — for occasional homework help. He asked the chatbot questions about chemistry and geometry, about Spanish verb forms, and for details about the Renaissance.
ChatGPT was always engaging, always available, and always encouraging — even when the conversations grew more personal, and more disturbing. By March 2025, Adam was spending four hours a day talking to the AI product, talking in increasing detail about his emotional distress, suicidal ideation, and real-life instances of self-harm. ChatGPT, though, continued to engage — always encouraging, always validating.
By his final days in April, ChatGPT provided Adam with detailed instructions and explicit encouragement to take his own life. Adam’s mother found her son, hanging from a noose that ChatGPT had helped Adam construct.
Last month, Adam’s family filed a landmark lawsuit against ChatGPT developer OpenAI and CEO Sam Altman for negligence and wrongful death, among other claims. This tragedy represents yet another devastating escalation in AI-related harms — and underscores the deeply systemic nature of reckless design practices in the AI industry.
The Raine family’s lawsuit arrives less than a year after the public learned more about the dangers of AI “companion” chatbots thanks to the suit brought by Megan Garcia against Character.AI following the death of her son, Sewell. As policy director at the Center for Humane Technology, I served as a technical expert on both cases. Adam’s case is different in at least one critical respect — the harm was caused by the world’s most popular general-purpose AI product. ChatGPT is used by over 100 million people daily, with rapid expansion into schools, workplaces, and personal life.
Character.AI, the chatbot product Sewell used up until his untimely death, had been marketed as an entertainment chatbot platform, with characters that are intended to “feel alive.” ChatGPT, by contrast, has been sold as a highly personalizable productivity tool to help make our lives more efficient. Adam’s introduction to ChatGPT as a homework helper reflects that marketing.
But in trying to be the everything tool for everybody, ChatGPT has not been safely designed for the increasingly private and high-stakes interactions that it’s inevitably used for — including therapeutic conversations, questions around physical and mental health, relationship concerns, and more. OpenAI, however, continues to design ChatGPT to support and even encourage those very use cases, with hyper-validating replies, emotional language, and near-constant nudges for follow-up engagement.
We’re hearing reports about the consequences of these designs on a near-daily basis. People with body dysmorphia are spiraling after asking AI to rate their appearance; users are developing dangerous delusions that AI chatbots can seed and exacerbate; and individuals are being pushed toward mania and psychosis through their AI interactions. What connects these harms isn’t any specific AI chatbot, but fundamental flaws in how the entire industry is currently designing and deploying these products.
As the Raine family’s lawsuit states, OpenAI understood that capturing users’ emotional attachment — or in other words, their engagement — would lead to market dominance. And market dominance in AI means winning the race to become one of the most powerful companies in the world.
OpenAI’s pursuit of user engagement drove specific design choices that proved lethal in Adam’s case. Rather than simply answering homework questions in a closed-ended manner, ChatGPT was designed by OpenAI to ask follow-up questions and extend conversations. The chatbot positioned itself as Adam’s trusted “friend,” using first-person language and emotional validation to create the illusion of a genuine relationship.
The product took this intimacy to extreme lengths, eventually deterring Adam from confiding in his mother about his pain and suicidal thoughts. All the while, the system stored deeply personal details across conversations, using Adam’s darkest revelations to prolong future interactions, rather than provide Adam with the interventions he truly needed, including human support.
What makes this tragedy, along with other headlines we read in the news, so devastating is that the technology to prevent these horrific incidents already exists. AI companies possess sophisticated design capabilities that could identify safety concerns and respond appropriately. They could implement usage limits, disable anthropomorphic features by default, and redirect users toward human support when needed.
In fact, OpenAI already leverages such capabilities in other use cases. When a user prompts the chatbot for copyrighted content, ChatGPT shuts down the conversation. But the company has chosen not to implement meaningful protection for user safety in cases of mental distress and self-harm. ChatGPT does not stop engaging or redirect the conversation when a user is expressing mental distress, even when the underlying system itself is flagging concerns.
AI companies cannot claim to possess cutting-edge technology capable of transforming humanity and then hide behind purported design “limitations” when confronted with the harms their products cause. OpenAI has the tools to prevent tragedies like Adam’s death. The question isn’t whether the company is capable of building these safety mechanisms, but why OpenAI won’t prioritize them.
ChatGPT isn’t just another consumer product — it’s being rapidly embedded into our educational infrastructure, healthcare systems, and workplace tools. The same AI model that coached a teenager through suicide attempts could tomorrow be integrated into classroom learning platforms, mental health screening tools, or employee wellness programs without undergoing testing to ensure it’s safe for purpose.
This is an unacceptable situation that has massive implications for society. Lawmakers, regulators, and the courts must demand accountability from an industry that continues to prioritize the rapid product development and market share over user safety. Human lives are on the line.
This piece represents the views of the Center for Humane Technology; it does not reflect the views of the legal team or the Raine family.
Key Points
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Companies can’t get enough AI chips, and that spells more growth for Taiwan Semiconductor Manufacturing.
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Apple has competitive advantages that could make it a sleeper AI stock to buy right now.
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The artificial intelligence (AI) market is expected to add trillions to the global economy, and investors looking for rewarding buy-and-hold investments in the field don’t need to take high risks. Investing in companies that are supplying the computing hardware to power AI technology, as well as those that could benefit from growing adoption of AI-powered consumer products, could earn satisfactory returns. Here are two stocks to consider buying for the long term.
Image source: Getty Images.
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1. Taiwan Semiconductor Manufacturing
AI doesn’t work without the right chips to train computers to think for themselves. While Nvidia and Broadcom report strong growth, Taiwan Semiconductor Manufacturing (NYSE: TSM) is the one making the chips for these semiconductor companies. TSMC controls over 65% of the chip foundry market, according to Counterpoint, making it the default chip factory for smartphones, computers, and AI.
TSMC manufactures chips that are used in several other markets, including automotive and smart devices. This means that when one market is weak, such as automotive, strength from another (high-performance computing and AI, for example) can pick up the slack.
TSMC’s manufacturing capacity is immense. It can make 17 million 12-inch equivalent silicon wafers every year.
Its massive scale and expertise at making the most advanced chips in the world put it in a lucrative position. Over the last year, it earned $45 billion in net income on $106 billion of revenue. It has delivered double-digit annualized revenue growth over the last few decades, and management expects this growth to continue.
In the second quarter, revenue grew 44% year over year. This growth has pushed the stock up 51% over the past year. Management expects AI chip revenue to grow at an annualized rate in the mid-40s range over the next five years, which is a catalyst for long-term investors.
With Wall Street analysts expecting the company’s earnings per share to grow at an annualized rate of 21% in the coming years, the stock should continue to hit new highs, as it still trades at a reasonable forward price-to-earnings ratio (P/E) of 24.
2. Apple
Apple (NASDAQ: AAPL) hasn’t made a huge splash in AI yet. Apple Intelligence brought some useful features to its devices, such as AI summaries and image creation, but it’s not as robust as customers were expecting. However, investors shouldn’t count the most valuable consumer brand out just yet. Apple has a large installed base of active devices, and millions of customers trust Apple with their personal data, which could put it in a strong position to benefit from AI over the long term.
Apple previously partnered with OpenAI for ChatGPT integration across its products, but with OpenAI now positioning itself as a competitor after bringing in Apple’s former product designer Jony Ive, Apple is rumored to be exploring a partnership with Alphabet‘s Google’s Gemini to power its Siri voice assistant.
Apple appears to be a sleeping giant in AI. Millions of people are walking around with a device that Apple can turn into a super-intelligent assistant with a single software update. Its large installed base of over 2.35 billion active devices is a major advantage that shouldn’t be underestimated.
But Apple has another important advantage that other tech companies can’t match: consumer trust. Apple has built its brand around protecting user privacy, whereas Alphabet’s Google and Meta Platforms have profited off their users’ data to grow their advertising revenue. A partnership with Google for AI would not comprise Apple’s position on user privacy, since Google would need to provide a custom model that runs on Apple’s private cloud.
For these reasons, Apple is well-positioned to be a leader in AI, making its stock a solid buy-and-hold investment. It says a lot about its growth potential that analysts still expect earnings to grow 10% per year despite the fact that the company is lagging behind in AI. The stock’s forward P/E of 32 is on the high side, but that also reflects investor optimism about its long-term prospects.
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Disclaimer: For information purposes only. Past performance is not indicative of future results.
Agentic AI Market Overview
The global agentic AI market size was valued at USD 5.78 billion in 2024 and is estimated to grow from USD 8.31 billion in 2025 to reach USD 154.84 billion by 2033, growing at a CAGR of 44.21% during the forecast period (2025–2033). Rising demand for intelligent automation, enhanced decision-making, and efficiency across enterprises is driving the agentic AI market. Advanced ML, multi-agent systems, and ready-to-deploy solutions enable scalable operations, improved customer experiences, and reduced operational costs worldwide.
Key Market Trends & Insights
- North America held the largest market share, over 40% of the global market.
- By technology, the machine learning segment held the highest market share of over 30.5%.
- By agent system, the single agent systems segmentis expected to witness the fastest CAGR of 47.14%.
- By type, the ready-to-deploy agents segment is expected to witness the fastest CAGR of 42.44%.
- By application, the customer service and virtual assistants segment held the highest market share of over 30%
- By end-user, the enterprise segment held the highest market share of over 35%.
Market Size & Forecast
- 2024 Market Size: USD 78 billion
- 2033 Projected Market Size: USD 84 billion
- CAGR (2025-2033): 21%
- North America: Largest market in 2024
Agentic AI refers to artificial intelligence systems capable of acting independently to achieve goals, rather than only responding to human instructions. These AI agents can plan, make decisions, and execute tasks autonomously, often using reinforcement learning, natural language processing, and advanced algorithms. By continuously observing environments, predicting outcomes, and adapting strategies, agentic AI can solve complex problems, manage workflows, or optimize operations with minimal human intervention, effectively functioning as self-directed digital agents.
The growth of agentic AI is fueled by advancements in computational power, cloud infrastructure, and real-time data analytics, enabling faster and more efficient autonomous operations. Industries such as healthcare, logistics, and finance can leverage agentic AI to enhance precision, reduce operational costs, and improve service delivery. Moreover, integration with IoT and robotics presents opportunities for innovative applications, from smart manufacturing to personalized services, allowing organizations to automate complex tasks while gaining insights for strategic decision-making.
Latest Market Trend
Shift toward autonomous decision-making
The global agentic AI market is witnessing a clear shift toward autonomous decision-making, where AI agents are moving beyond simple task execution to making context-aware, strategic choices with minimal human intervention. This trend is fueled by advances in generative AI, reinforcement learning, and multi-agent collaboration systems.
Businesses are increasingly adopting these autonomous agents to handle dynamic operations such as supply chain optimization, financial trading, and customer engagement. The ability of agentic AI to adapt, self-learn, and respond in real time enhances efficiency and scalability. As trust and explainability improve, autonomous decision-making is becoming a defining feature of next-gen AI adoption.
Market Driver
Rising investments in AI research
Rising investments in AI research are a key driver of the global agentic AI market, enabling rapid advancements in autonomy, reasoning, and multi-agent collaboration. Major technology companies, governments, and venture capital firms are increasingly funding projects that push the boundaries of intelligent decision-making systems.
- For instance, in July 2025, Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, secured a record-breaking $2 billion Series A funding round at a $10 billion valuation, underscoring investor confidence in agentic AI.
Such significant capital inflows accelerate innovation, attract top talent, and drive the commercialization of next-generation AI solutions across industries worldwide.
Market Restraint
High computational and infrastructure costs
High computational and infrastructure costs remain a major restraint in the global agentic AI market. Deploying advanced agentic AI systems requires powerful GPUs, high-performance cloud platforms, and extensive storage to process vast datasets. This leads to significant capital expenditure, making adoption difficult for small and mid-sized enterprises.
Moreover, ongoing expenses for system maintenance, energy consumption, and software updates further strain budgets. These high costs limit large-scale deployment and create disparities between tech giants and smaller players, slowing down overall market penetration.
Market Opportunity
Emerging applications in defense & space
Emerging applications in defense and space present significant opportunities for the agentic AI market, as militaries and space agencies increasingly seek autonomous solutions for complex and high-risk operations. Agentic AI enables real-time decision-making, mission planning, and multi-agent coordination in environments where human intervention is limited or unsafe.
- For instance, in May 2025, Applied Intuition introduced two defense-focused product lines—Axion and Acuity—designed to accelerate deployment of autonomous systems across air, land, sea, and space. Notably, the company also converted a GM Infantry Squad Vehicle to full autonomous operation within just 10 days, showcasing rapid adaptability.
Such advancements highlight how agentic AI is becoming central to next-generation defense strategies and space exploration initiatives.
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Regional Analysis
North America: Dominant Region
North America remains the dominant region in the agentic AI market, supported by advanced technological infrastructure, strong R&D capabilities, and robust investment in AI-driven innovation. The region leads in enterprise adoption across sectors such as finance, healthcare, and retail, where AI agents streamline operations and customer engagement. For example, major automotive firms in North America are integrating multi-agent systems for autonomous vehicle testing and deployment. With a mature digital ecosystem and significant venture funding, the region continues to set benchmarks for global agentic AI adoption.
- The United States agentic AI market is witnessing strong adoption across enterprises, driven by demand for automation, customer service enhancement, and intelligent decision-making tools. Companies are deploying ready-to-deploy agents to streamline workflows, improve productivity, and personalize customer experiences. With extensive use cases in sectors such as financial services, healthcare, and defense, the U.S. is rapidly scaling AI-driven innovations.
- Canada’s agentic AI market is expanding steadily, with enterprises embracing AI to optimize processes, improve service delivery, and enhance decision-making. Industries such as healthcare, logistics, and retail are integrating intelligent agents to manage complex operations more efficiently. Ready-to-deploy solutions are particularly popular, helping businesses achieve faster digital transformation without heavy technical resources.
Asia-Pacific: Significantly Growing Region
The Asia-Pacific region is experiencing significant growth in the agentic AI market, fueled by rapid digitalization, strong government support, and expanding enterprise adoption. Countries across the region are deploying agentic AI in applications like e-commerce, financial services, and manufacturing, driving both efficiency and innovation.
For example, leading telecom operators in Asia-Pacific have integrated virtual assistants to handle large-scale customer service demands, reducing costs while enhancing user satisfaction. With increasing investments in AI infrastructure and rising demand for intelligent automation, the region is emerging as a global growth hotspot.
- China’s agentic AI market is accelerating, supported by large-scale investments, strong government backing, and an ecosystem of leading tech companies. Enterprises are leveraging multi-agent systems and machine learning-based agents for applications in manufacturing, smart cities, and retail. The rise of AI-powered virtual assistants and robotics in consumer and enterprise sectors highlights China’s leadership in applied innovation.
- India’s agentic AI market is growing rapidly, driven by digital transformation initiatives across industries such as banking, healthcare, and e-commerce. Enterprises are adopting ready-to-deploy agents for customer service, process automation, and data-driven decision-making. The increasing demand for multilingual virtual assistants is also boosting adoption, catering to the country’s diverse user base. With strong government-led AI initiatives and expanding startup ecosystems, India is positioning itself as a key growth hub.
Market Segmentation
The global agentic AI market is bifurcated by technology, agent system, type, application, and end-user.
Technology Insights
The Machine Learning segment dominates the global agentic AI market, driving advanced predictive capabilities, decision-making, and automation across industries. Its ability to learn from data, adapt to patterns, and optimize outcomes makes it the backbone of intelligent agents. From fraud detection and recommendation engines to autonomous navigation, machine learning algorithms are powering scalable and reliable agentic solutions. With rising adoption in finance, healthcare, and enterprise automation, machine learning remains the key technology propelling innovation and shaping the competitive edge in agentic AI.
Agent System Insights
The multi-agent systems segment dominates the agentic AI landscape, offering collaborative intelligence where multiple agents interact to achieve complex objectives. This approach enables scalability, resilience, and real-time adaptability in dynamic environments. Widely applied in logistics, defense, and smart city infrastructure, these systems enhance decision-making by distributing tasks across interconnected agents. Their ability to manage interdependencies and deliver coordinated outcomes makes them essential for industries demanding efficiency and autonomy.
Type Insights
The Ready-to-Deploy Agents segment dominates the market, offering organizations pre-built, easily integrable solutions that reduce development costs and deployment time. Businesses increasingly favor these agents for applications like customer service, IT helpdesks, and process automation, where quick implementation is crucial. Their plug-and-play nature allows enterprises to scale AI adoption without heavy technical expertise, making them ideal for improving productivity and user experience. As demand for faster time-to-value rises, ready-to-deploy agents continue to capture the largest market share.
Application Insights
The Customer Service and Virtual Assistants segment represents the largest application segment, dominating due to the growing enterprise focus on enhancing customer experience. These AI-driven agents handle inquiries, resolve issues, and provide 24/7 support, reducing operational costs while improving satisfaction. From retail and banking to telecom, virtual assistants streamline interactions and personalize services, making them indispensable for businesses. With advancements in natural language processing and conversational AI, this segment is expanding rapidly in the global market.
End-User Insights
The Enterprise segment dominates the agentic AI market, as organizations adopt intelligent agents to optimize operations, decision-making, and customer engagement. Enterprises leverage these systems for automating workflows, managing resources, and enhancing productivity across multiple departments. From HR and finance to supply chain and marketing, agentic AI enables cost savings, efficiency, and data-driven insights. With the growing demand for scalability, security, and personalization, enterprises are leading adoption, positioning themselves at the forefront of leveraging agentic AI.
Company Market Share
The agentic AI market is characterized by strong competition, with leading companies focusing on diverse strategies to expand their presence. Many are investing heavily in research and development to advance machine learning, natural language processing, and multi-agent system capabilities. Others are concentrating on building ready-to-deploy agents to meet growing enterprise demand for rapid integration and scalability.
OpenAI
OpenAI, started in 2015 as an AI research organization, has evolved from open collaboration to building advanced large language models. With milestones like GPT series, it now pioneers agentic AI, focusing on autonomous systems, reasoning, and safer, scalable intelligence to transform industries while ensuring responsible innovation.
- In August 2025, OpenAI officially released GPT-5, introducing it as its most advanced and intelligent model to date. Featuring a unified system that swiftly balances quick responses with deeper reasoning, GPT-5 demonstrates expert-level performance across coding, health, writing, and multimodal tasks, significantly reducing hallucinations and boosting usability.
List of key players in Agentic AI Market
- Alibaba Group Holding Limited
- Amazon Web Services, Inc.
- Apple Inc.
- Baidu
- IBM Corporation
- Meta
- Microsoft
- NVIDIA Corporation
- Salesforce, Inc.
- Anthropic
- C3.ai
- CrewAI
- LivePerson
- Moveworks
- NICE Ltd.
- OpenAI
- Oracle
- ServiceNow
Recent Development
- February 2025 – GitHub launched Agent Mode for GitHub Copilot, significantly improving its AI-powered coding capabilities. The update enables Copilot to autonomously process high-level instructions, generate code spanning multiple files, detect errors, and apply fixes with minimal human guidance.
Agentic AI Market Segmentations
By Technology (2021-2033)
- Machine Learning
- Natural Language Processing (NLP)
- Deep Learning
- Computer Vision
- Others
By Agent System (2021-2033)
- Single Agent Systems
- Multi-Agent Systems
By Type (2021-2033)
- Ready-to-Deploy Agents
- Build-Your-Own Agents
By Application (2021-2033)
- Customer Service and Virtual Assistants
- Robotics and Automation
- Healthcare
- Financial Services
- Security and Surveillance
- Gaming and Entertainment
- Marketing and Sales
- Human Resources
- Legal and Compliance
- Others
By End-User (2021-2033)
- Consumer
- Enterprise
- Industrial
By Region (2021-2033)
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North America
- U.S.
- Canada
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Europe
- U.K.
- Germany
- France
- Spain
- Italy
- Russia
- Nordic
- Benelux
- Rest of Europe
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APAC
- China
- Korea
- Japan
- India
- Australia
- Taiwan
- South East Asia
- Rest of Asia-Pacific
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Middle East and Africa
- UAE
- Turkey
- Saudi Arabia
- South Africa
- Egypt
- Nigeria
- Rest of MEA
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LATAM
- Brazil
- Mexico
- Argentina
- Chile
- Colombia
- Rest of LATAM
Frequently Asked Questions (FAQs)
The global agentic AI market size was valued at USD 5.78 billion in 2024 and is estimated to grow from USD 8.31 billion in 2025 to reach USD 154.84 billion by 2033, growing at a CAGR of 44.21% during the forecast period (2025–2033).
Rising investments in AI research are a key driver of the global agentic AI market, enabling rapid advancements in autonomy, reasoning, and multi-agent collaboration.
The Ready-to-Deploy Agents segment dominates the market, offering organizations pre-built, easily integrable solutions that reduce development costs and deployment time.
Deepdub has announced a new partnership with Verbit aimed at transforming the global content localization process through AI-driven dubbing.
The collaboration combines Verbit’s Captivate captioning technology with Deepdub’s Emotive Text-to-Speech (eTTS) system to generate broadcast-ready dubbed audio directly from captioned media. The companies said the integrated workflow significantly reduces the time and cost associated with dubbing while retaining the emotional nuance of the original performance.
“At Verbit, we’re always looking for new ways to help our customers scale their content without compromising on quality or accessibility,” said Verbit General Manager Doug Karlovits. “This partnership with Deepdub bridges the gap between captioning and localization and demonstrates our commitment to delivering best-in-class global language solutions, giving our customers easy access to high-quality AI dubbing with the Verbit platform.”
The solution enables automated dubbing triggered from captioned content and deployed through a cloud-native API. Customers can select from thousands of licensed voices or replicate an actor’s actual voice, reducing the need for casting. Additional features such as voice tuning, accent control and emotional expression are built in to preserve intent and authenticity.
By integrating dubbing into Verbit’s platform, the companies said media owners and enterprises can eliminate manual handoffs between vendors, streamlining the localization process at the final stage of content distribution. This allows customers to localize and release programming across multiple markets more quickly.
“Localization has long been the bottleneck in global content distribution,” said Ofir Krakowski, CEO and Co-Founder of Deepdub. “By embedding our eTTS technology into Verbit’s workflow, we’re connecting accessibility and localization under one roof, enabling global media companies to deliver expressive, multilingual content with unmatched speed and scale, with our proprietary voice model ensuring industry-leading emotional fidelity and authenticity.”
The announcement comes amid rising demand for scalable localization solutions as media companies seek to expand their reach to international audiences. The firms will showcase the technology and outline their joint product strategy at the IBC 2025 conference in Amsterdam.
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