Artificial intelligence (AI) is a two-sided coin. While it has revolutionized how we work, communicate, and interact with technology, it has also accelerated the speed and complexity of cyber exploits. As AI-driven attacks increase in scale and impact, experts emphasize the need for businesses to move beyond traditional, human-centric defense strategies.1 By harnessing AI to
Each year, industry leaders work to uncover trends and insights about cybercrime. The latest crop of reports shows that the human element remains a top issue in data breaches. What’s different in 2024 is that large language models (LLMs) have transformed how people work, enhancing our ability to brainstorm effectively and quickly, automate routine tasks,
On Tuesday, May 21, 2024, world leaders met virtually at the AI Seoul Summit—a follow-up to the AI Safety Summit in November—to adopt a new AI agreement. The gathering, co-hosted by South Korea and the UK, included leaders from the G7, Australia, Singapore, the UN, the EU, and representatives from global tech organizations. Sixteen leading
Artificial intelligence (AI) is driving innovation. With seemingly endless possibilities, organizations are universally adopting AI to enhance their offerings and keep pace in today’s ultra-competitive market. However, without clear and proper guidelines in place, AI can cause harm, driving unintended customer outcomes, or worse, introducing new security risks and exposures. It’s what’s led to the
AI’s transformative powers won’t be limited to just enterprises. Small and medium-sized businesses (SMBs) can use AI-powered products and solutions to increase efficiencies and achieve strategic objectives. Using AI can be a crucial component for success, with 80% of U.S. SMBs with very high technology usage report growth in revenue, employment, and profits.1 SMBs can
Artificial intelligence (AI) has become an essential part of business. The value is in its tangible benefits, including influencing decisions, improving customer interactions, and developing enhanced operational strategies. AI involves machine learning, natural language processing, and advanced algorithms. By understanding the technology and its practical applications, businesses can harness AI to innovate and solve complex
In our last post, we provided insights into how effectively managed data architectures and pipelines can power generative data models to create human-like outputs. In this post, we look at how the platform engineering team can partner with data engineers to help accelerate the time to value while alleviating some inherent issues with this burgeoning
Is artificial intelligence (AI) biased? This isn’t a new question—five years ago, a company abandoned its idea of using AI to narrow down job candidates because it discovered its system was biased against women in technical roles.1 More recently, an Asian student at the Massachusetts Institute of Technology (MIT) used an AI tool to create
*Editorial note: In some instances, ChatGPT provided a few elements that have been modified and used in this post. The Financial Times recently reported that investments in generative AI surpassed $2 billion in 20221, with more than half of companies surveyed claiming they are allocating over 5% of their digital budgets to AI. Looking at
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