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Will AI take your job? Let it in the new year. We don't mean it should replace you and run your meetings, but it should do the parts of your job that you hate for you. Create infographics for your website? One of AI's biggest issues, though, is there are so many (probably too many) tools out there.

Retrieval augmented generation (RAG) is a process where a large language model (LLM) retrieves useful information from a database and then generates the responses. It is becoming popular in enterprise settings for daily business operations. For example, Copilot for Microsoft 365 has accumulated millions of businesses. However, the security implications of adopting such RAG-based systems are unclear. In this paper, we introduce ConfusedPilot, a class of security vulnerabilities of RAG systems that confuse Copilot and cause integrity and confidentiality violations in its responses. First, we investigate a vulnerability that embeds malicious text in the modified prompt in RAG, corrupting the responses generated by the LLM. Second, we demonstrate a vulnerability that leaks secret data, which leverages the caching mechanism during retrieval. Third, we investigate how both vulnerabilities can be exploited to propagate misinformation within the enterprise and ultimately impact its operations, such as sales and manufacturing. We also discuss the root cause of these attacks by investigating the architecture of a RAG-based system. This study highlights the security vulnerabilities in today's RAG-based systems and proposes design guidelines to secure future RAG-based systems.

There has been a significant surge of Artificial Intelligence (AI) usage in the restaurant industry for providing improved services to elevate operations, trim cost and create a better environment for guests. How will AI use in the restaurant industry continue to evolve? To evaluate future sales, restaurant owners carry out a sales forecasting process. Most compare the sales report of the previous year with the current year, but factors such as holidays, international events, weather conditions and location, affecting the sales are variable so this traditional process of sales forecasting can sometimes go wrong. For more accurate sales reports, restaurant owners must take the help of technology and artificial intelligence can be a helpful tool for predictions.

For years, sales teams have been inundated with new apps and tools, each promising to help them navigate radical changes in how customers research and buy products. Many sales people are fatigued by tech overload – they're disillusioned by past claims of countless new tools being the next'quick fix', so it's fair that they see artificial intelligence (AI) as yet another tool in their overflowing toolboxes. And, if they listen to some analysts, it's even fair that they fear AI will take their jobs away entirely. But new data from a global study of sales professionals, the third annual State of Sales report, shows AI is being used by high-performers to address major challenges that have been building in the sales profession for years – high-performing sales teams (the top 24 per cent that have significantly increased year-over-year revenue) are nearly five times more likely than underperformers to be using AI. Ai is enabling and helping, rather than replacing, salespeople across the organisation, including inside and outside reps.

Discover how arming your reps with AI encourages more successful conversations and closes more sales. It's getting more difficult for sales leaders to make their numbers. According to Salesforce's State of Sales report, it's because prospects and customers are becoming inundated with messages that compete for their attention. Customer needs have grown more sophisticated, their motivations have shifted from price to value, and they expect consistent service across every interaction with a sales rep. Other challenges facing sales teams include inconsistent training and having to adhere to admin-heavy sales processes.