"If we look back on the last 10, 15 years on social media, I think we'd be hard pressed to say that the velocity and the impact and the adverse effect of social media is equal to, or more than, the benefits that have occurred," he said. "And one of the reasons is the fact that there wasn't regulation, and the regulation that has come is too late." He said AI is progressing so fast and "the regulators are so far behind, they don't even know what the questions are because of the speed of this thing."
Many businesses have had to learn in recent years that adopting AI to automate certain organizational tasks or employees' day-to-day workflows won't necessarily translate to financial gain. The technology may make workers more productive in some respects, but it also presents a whole host of risks -- some of them involving cybersecurity, some of them legal, some of them psychological. In some cases, AI actually creates more work for supervisors.
"As we roll out age-gating more fully and as part of our 'treat adult users like adults' principle, we will allow even more, like erotica for verified adults," Altman writes. Earlier this month, OpenAI hinted at allowing developers to create "mature" ChatGPT apps after it implements the "appropriate age verification and controls." OpenAI isn't the only company dipping into erotica, as Elon Musk's xAI previously launched flirty AI companions, which appear as 3D anime models in the Grok app.
Ten major philanthropic organizations are banding together to ensure that regular Americans, not just a small group of tech billionaires, have a say in how AI will shape society and who will benefit. The organizations announced Tuesday the formation of Humanity AI, a $500-million five-year initiative aimed at ensuring artificial intelligence serves people and communities rather than replacing or diminishing them.
At Fortune, we've spent almost a century studying what separates the good leaders from the great ones; the ones who don't just survive disruption, but shape it. The next wave of corporate chiefs is emerging from a radically different playbook. They're products of an economy defined by technological acceleration, and operate with fluency across disciplines that didn't even exist in the CEO vocabulary a decade ago: data science, AI governance, cybersecurity, social trust, geopolitical volatility, and shifting expectations of what leadership should look like.
We study AI and democracy. We're worried about 2050, not 2026. Half of humanity lives in countries that held national elections last year. Experts warned that those contests might be derailed by a flood of undetectable, deceptive AI-generated content. Yet what arrived was a wave of AI slop: ubiquitous, low quality, and sometimes misleading, but rarely if ever decisive at the polls.
AI tools, such as chatbots, promise speed, savings and scalability. But behind each successful interaction, there's a less visible truth: when AI systems operate without active oversight, they silently accumulate risk. These hidden liabilities-spanning brand damage, operational drag, ethical concerns and cybersecurity gaps-often remain undetected until a public crisis erupts. Here are three real-world cases of AI assistant deployment. Each began as a quick win. Each revealed what happens when governance is an afterthought.
According to Rajat Taneja, Visa's president of technology, the global payments company has woven AI into every part of its business. Employees across Visa are tapping AI in their everyday workflows for tasks ranging from data analysis to software development. The company has built more than 100 internal AI-powered business applications tailored to specific use cases and has over 2,500 engineers working specifically on AI. Visa is also using AI to create new products and services for its customers, such as faster onboarding, simplified processes for managing disputes, and infrastructure for agentic AI technologies.
Lisa, Jennie, Rosé, and Jisoo have broken numerous records since their debut in 2016: the first to sell one million, then two million, album copies in South Korea; the first Korean group to top the Billboard 200 album chart; the highest-grossing concert tour by a female artist. Blackpink, and K-pop and K-culture more broadly, are now a source of South Korean "soft power," expanding the country's cultural influence across Asia and beyond.
Over 40 minutes, the panel returned again and again to three themes: data quality, organizational alignment and cultural readiness. The consensus was clear: AI doesn't create order from chaos. If organizations don't evolve their culture and their standards, AI will accelerate dysfunction, not fix it. Clean data isn't optional anymore Allen set the tone from the executive perspective. He argued that enterprises must build alignment on high-quality, structured and standardized data within teams and across workflows, applications and departments.
Hallucinations have commonly been considered a problem for generative AI, with chatbots such as ChatGPT, Claude, or Gemini prone to producing 'confidently incorrect' answers in response to queries. This can pose a serious problem for users. There are several cases of lawyers, for example, citing non-existent cases as precedent or presenting the wrong conclusions and outcomes from cases that really do exist. Unfortunately for said lawyers, we only know about these instances because they're embarrassingly public, but it's an experience all users will have had at some point.
Every Fortune 500 CEO investing in AI right now faces the same brutal math. They're spending $590-$1,400 per employee annually on AI tools while 95% of their corporate AI initiatives fail to reach production. Meanwhile, employees using personal AI tools succeed at a 40% rate. The disconnect isn't technological-it's operational. Companies are struggling with a crisis in AI measurement.
Since the AI boom kicked off with ChatGPT's debut about three years ago, the technology's breathtaking capabilities have amazed the world. Tech companies have raced to develop better AI systems even as experts warn of its risks, including existential threats like engineered pandemics, large-scale misinformation or rogue AIs running out of control, and call for safeguards.The U.N.'s adoption of a new governance architecture is the latest and biggest effort to rein in AI.
As the number of foundation models proliferates and enterprises increasingly build applications or code on top of them, it becomes imperative for CIOs and IT leaders to establish and follow a robust multi-level due diligence framework, Shah said. That framework should ensure training data transparency, strong data privacy, security governance policies, and at the very least, rigorous checks for geopolitical biases, censorship influence, and potential IP violations.
EPAM is building its DIAL platform to become one of the most advanced enterprise AI orchestration systems in operation. With its recent DIAL 3.0 release, it addresses how to harness AI at scale without sacrificing governance, cost control, or transparency. We spoke with Arseny Gorokh, VP of AI Enablement & Growth at EPAM, about the platform. DIAL might not be the most known technology out there, but it has some history to build on.
" Microsoft and OpenAI have signed a non-binding memorandum of understanding for the next phase of our partnership," the companies said in a document described as a joint statement, continuing, "Together, we remain focused on delivering the best AI tools for everyone, grounded in our shared commitment to safety."
Its main nonprofit organization will control a new public benefit corporation that will house OpenAI's for-profit operations. The restructuring will make it easier for OpenAI to issue traditional equity to new investors, allowing the startup to raise the massive amount of money needed to pursue its ambitious plans. The OpenAI nonprofit doesn't just get control. It also gets an equity stake in the new business that is worth more than $100 billion, Taylor said.
It's been well established in the first year of Trump's second presidency that AI is a priority for the administration. Even prior to Trump taking office, government generative AI use cases had surged, growing ninefold between 2023 and 2024. In recent months, agencies have cut numerous deals with most leading AI companies under the General Services Administration's Trump-driven OneGov contracting strategy.
The General Assembly is the primary deliberative body of the United Nations and, in effect, of global diplomacy. This year's session will comprise delegations from all 193 UN member states, which all have equal representation on a "one state, one vote" basis. Unlike other UN bodies, such as the Security Council, this means all members have the same power when it comes to voting on resolutions. It is also the only forum where all member states are represented.
For the past five years, much of the enterprise conversation around artificial intelligence (AI) has revolved around access - with access to application programming interfaces (APIs) from hyperscalers, pre-trained models, and plug-and-play integrations promising productivity gains. This phase made sense. Leaders wanted to move quickly, experimenting with AI without the cost of building models from scratch. " AI-as-a-service " lowered barriers and accelerated adoption.
When you hear "governance," what pops to mind? We often picture limitations or roadblocks. Yet the opposite is true, particularly with artificial intelligence. AI governance is about discovering what your organization can do. Organizations implementing comprehensive AI governance experience measurable returns, including $840,000 in operational efficiency gains and 80% in productivity improvements. Building out your AI roadmap requires a mindset shift. These ideas will move you from limitation to acceleration.
In most cases, employees are driving adoption from the bottom up, often without oversight, while governance frameworks are still being defined from the top down. Even if they have enterprise-sanctioned tools, they are often eschewing these in favor of other newer tools that are better-placed to improve their productivity. Unless security leaders understand this reality, uncover and govern this activity, they are exposing the business to significant risks.
A new survey reveals a striking "AI readiness gap" in the modern workplace: those using AI tools the most-including top executives and Gen Z employees-are often the least likely to receive meaningful guidance, training, or even company approval for their use. The findings come from WalkMe, an SAP company, which surveyed over 1,000 U.S. workers for the 2025 edition of its " AI in the Workplace " survey.
Rather than pursuing massive, resource-intensive AI initiatives that take years to deliver, Huss argues for Minimum Viable AI - a pragmatic approach that focuses on getting functional, well-governed AI into production quickly. It's not about building the flashiest model or chasing state-of-the-art benchmarks; it's about delivering something useful, measurable, and adaptable from day one.
In the race to stay ahead, organizations have thrown open the doors to every AI tool under the sun. The result? AI overload. According to the Wharton School, AI spending has skyrocketed by 130% in just the past year, and 72% of companies are planning to invest even more in 2025. Yet, here's the kicker: 80% of organizations report no tangible enterprise-wide impact from their generative AI investments.
Erika Stael von Holstein, 41, has been advising European institutions on science, technology, society, and democracy for two decades. She's the founder and director of Re-Imagine Europe, a think tank focused on depolarization. The Stockholm-born advisor has also promoted Nodes.eu, a European observatory of narratives against disinformation. Von Holstein is a member of the expert council on artificial intelligence convened by the Spanish government. This work brought her to Madrid, where she met with EL PAIS.
