Articles about Generative AI

Generative AI models like ChatGPT are creating a lot of enthusiasm for what they can do for businesses, but they are generating just as much fear over what can go wrong with the data they handle. There is a lack of trust between large companies that have the data and the AI startups that want to use them.

What can we expect to see in the near future? We spoke with Katy Salamati, senior manager of the advanced analytics lifecycle at SAS, to find out.

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Generative artificial intelligence (GenAI) entered the public consciousness and debate about one year ago. As a science, it goes back several years but as an applicable piece of software, it is very much in its infancy. 

Text, images, and audio can be generated by GenAI models,but their integration into existing software tools worldwide is still in its early stages. Similarly, the majority of business leaders are only talking about GenAI, with some experimenting through proofs of concepts, while a small minority have deployed initial, and usually specific, use cases.

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The use of generative AI is becoming common across many industries, but while it undoubtedly offers benefits it can lead to problems too.

Legal firms in particular can fall foul of poor results, one firm was fined $5,000 after a court found that one of its lawyers had used ChatGPT to write a court brief which included false citations.

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Microsoft has announced a series of new artificial intelligence tools, options and capabilities which the company is using to empower retailers.

From copilot templates designed to help retailers provide personalized experiences for customers to generative AI tools for creating ads, Microsoft continues to push hard with AI. Of particular interest in the latest batch of tools is Retail Media Creative Studio, currently in preview.

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More than 10 percent of enterprise employees access at least one generative AI application every month, compared to just two percent a year ago, but there are security risks as a result.

New research from Netskope shows ChatGPT was the most popular generative AI application in 2023, accounting for seven percent of enterprise usage. The number of cloud apps the enterprise accessed also increased by an average of 19 percent per year, with users jumping from 14 to 20 different apps in just two years.

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Generative AI has the potential to reshape entire industries and how they operate, and financial services stand out as uniquely poised for AI-driven transformation. McKinsey & Company calls generative AI the next frontier for productivity, estimating that analyzing natural language text -- a core generative AI use case -- accounts for an average of 25 percent of the time people spend in any given enterprise.

The finance industry is a data-driven industry, so it’s no surprise that finance sector firms see big potential in using generative AI to tackle use cases that require assessing enormous amounts of unstructured data, such as company due diligence, know-your-customer (KYC) requirements, sustainability research, and controversy monitoring.

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The ChatGPT Revolution is the ultimate quick-start guide to unlocking the power of AI tool ChatGPT. We’re on the edge of an AI revolution… but what does that mean for you? It’s time to get curious about how the latest tech can help you handle your everyday load, at work and at home!

Whether you’re overwhelmed by repetitive, time-consuming tasks or you’re simply looking for a fresh injection of creativity, ChatGPT is the virtual assistant that’s got your back.

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AI’s path to maturity lacks footing without the stamp of regulation. While the recent developments of the White House executive order and the EU AI Act are a good start, there’s a lot of progress to be made in terms of AI research and rule-making. Because if we want to unlock the full range of AI use cases, we’re going to need precise regulation, tailored to the unique needs of each sector.

Generative AI sparks an opportunity to transform every industry; a prospect that has prompted a flurry of AI innovation across verticals that will undoubtedly send ripple effects throughout the economy. McKinsey estimates that across 63 different use cases, generative AI could contribute between $2.6 trillion to $4.4 trillion to the global economy annually. But sector and use-case-specific regulatory framework is imperative if we want to harness this potential and ensure responsible, safe applications of generative AI.

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Numerous businesses have embraced generative AI technology to enhance their operational efficiency, boost productivity and foster innovative ideas.

However, it is important to be aware of the potential legal and financial consequences associated with the use of ChatGPT and similar AI systems. We spoke to Sujay Rao, CPO at Sirion to find out more.

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Following a year full of excitement and uncertainty, and more opinions about the future of AI than anyone could count, AI providers, enterprises, and policymakers are now rallying around one thing: AI security. 

The White House recently followed in the European Union’s footsteps to introduce a new set of standards for the secure development and deployment of AI models. But while regulators triangulate their policies and AI companies work to comply, the real responsibility to proceed safely will remain with enterprises. 

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AI, particularly widely available tools like ChatGPT, has made big waves in 2023. Is this set to continue into next year or will we see a different approach to using the technology?

Here are the views of some industry experts.

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A new report from Abnormal Security highlights real-world examples of how AI is being used to carry out cyberattacks.

Generative AI allows scammers to craft unique email content, making detection that relies on matching known malicious text strings infinitely more difficult.

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A new report from Axiad shows that 88 percent of IT professionals feel their company is prepared to defend against a password-based cyberattack, yet 52 percent say their business has fallen victim to one within the last year.

Based on over 200 responses from US IT pros, the study shows 39 percent think phishing is the most feared cyberattack, while 49 percent say it's the attack most likely to happen.

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New research shows that businesses are increasing their investments in AI across many areas, but there are challenges and risks that they need to manage.

The study of 1,300 tech leaders from Dynatrace shows 98 percent are concerned that generative AI could be susceptible to unintentional bias, error, and misinformation. In addition 95 percent are concerned that using generative AI to create code could result in leakage and improper or illegal use of intellectual property.

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As the recent hype and excitement around Generative AI (GenAI) begins to settle somewhat, we are entering a critical phase where innovation must be more closely aligned with ethical considerations. The impact of AI is already evident in various aspects of life, pointing to a future where, ideally, its use is not only widespread but also guided by principled decision-making. In this context, the emphasis should be on using AI to address appropriate problems, not just any problem.

In particular, the early iterations of GenAI platforms have demonstrated their potential but also the need for careful application. In many organizations, GenAI has already improved both customer and employee experiences, with advanced chatbots capable of mimicking human interaction taking automated customer service to a whole new level by providing quick and relevant responses. In an ideal world, this use case highlights AI’s dual purpose: to enhance human capabilities while maintaining a focus on human-centred experiences.

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