HHS\u2019 2024 AI use case inventory shows move toward internal chatbots FCW

Before that happens, legal scholar Andrew Ferguson would like to see more of a public discussion about the benefits and potential harms. For one thing, the large language models behind AI chatbots are prone to making up false information, a problem known as hallucination that could add convincing and hard-to-notice falsehoods into a police report. For one thing, the large language models behind AI chatbots are prone to making up false information, a problem known as hallucination that could add convincing and hard-to-notice falsehoods into a police report. In particular, he said district attorneys prosecuting a criminal case want to be sure that police officers — not solely an AI chatbot — are responsible for authoring their reports because they may have to testify in court about what they witnessed. The benefits include saving programmers and software developers from laborious tasks like code optimization, bug detection and code completion such that they can focus on tasks that require human intervention.

Benefits Of Generative AI In Marketing

Last, start with small and manageable marketing projects and iterate as you learn and gain experience in using AI in the marketing domain. About half of all states are using artificial intelligence for chatbots, according to a 2024 survey by the National Association of State Technology Directors. The National Association of State Chief Information Officers (NASCIO) also identifies using chatbots to support citizen services as a top generative AI use case for state governments. Automation and improved preventive maintenance eliminate labor-intensive tasks and enable more competitive pricing for outsourcing services. Additionally, AI assistants support code generation and bug fixing, reducing manual efforts and improving overall code quality.

Defining leadership through mentorship and a strong network

The results show that most enterprises expect to achieve most of their ROI by the end of 2025. Over 200 professionals—including C-level executives and leaders across sales, marketing, HR and financing—were surveyed from a cross-section on major industries across 10 regions. At the end of the report, the officer must click a box that indicates it was generated with the use of AI. That’s not the case in another city, Lafayette, Indiana, where Police Chief Scott Galloway told the AP that all of his officers can use Draft One on any kind of case and it’s been “incredibly popular” since the pilot began earlier this year. Generative AI has multiple use cases across different industry verticals and, in marketing especially, can enable brands to accelerate the delivery of personalized marketing content while adhering to the brand’s writing style and tone. It even documented a fact he didn’t remember hearing — another officer’s mention of the color of the car the suspects ran from.

Supporting compliance, forecasting, market research, supply chain planning and software development are all domains in which human expertise— rather than human time—can be the limiting factors,” said ISG researchers. Pulling from all the sounds and radio chatter picked up by the microphone attached to Gilmore’s body camera, the AI tool churned out a report in eight seconds. As the technology catches on, Bussert expects officers will become “more and more verbal” in describing what’s in front of them. Ferguson said a police report is important in determining whether an officer’s suspicion “justifies someone’s loss of liberty.” It’s sometimes the only testimony a judge sees, especially for misdemeanor crimes. Pulling from all the sounds and radio chatter picked up by the microphone attached to Gilbert’s body camera, the AI tool churned out a report in eight seconds.

• The District of Columbia Water and Sewer Authority is using predictive maintenance to identify potential water main breaks and to monitor performance of collection systems.
• As a marketer that is always looking to maximize ROI and experiment with the latest technology, I, like many of us, have tested and used generative AI.
• Delta Airlines has used AIOps to create a “full-scale digital simulation environment for its global operation,” which the company says is a “first in commercial passenger aviation,” to maintain reliability, especially during inclement weather.
• Johnson & Johnson has combined RPA with ML, AI, and task mining to identify and automate complex processes that span across departments.
• Meanwhile, companies such as Pentagon Credit Union (PenFed) are using chatbots and conversational AI to help customers get answers to common questions faster, reducing the load on customer service reps.

The District of Columbia Water and Sewer Authority is using predictive maintenance to identify potential water main breaks and to monitor performance of collection systems. DC Water even has an AI tool called Pipe Sleuth that can review CCTV footage of sewer pipes to assess their maintenance needs in real-time. Approximately 28 percent of enterprises expect to train large language models (LLMs) in private clouds or on-promise.

It’s not the only vendor, with startups like Policereports.ai and Truleo pitching similar products. But given Axon’s deep relationship with police departments that buy its Tasers and body cameras, experts and police officials expect AI-generated reports to become more ubiquitous in the coming months and years. For companies that rely on web services or e-commerce, maintaining uptime and website reliability is a top priority. AI helps organizations achieve this by constantly scanning systems, networks, and processes for inefficiencies, potential disruptions, and to identify any looming threats in a way humans could never accomplish. Nearly all major organizations are employing AI to support their unique uptime and reliability needs. Netflix, Uber, Facebook, Salesforce, AirBnB, and many more are implementing AI to monitor, maintain, and keep their services up and running and available for customers.

• The results show that most enterprises expect to achieve most of their ROI by the end of 2025.
• Some of its immediate benefits include saving time, personalizing content and helping to create content.
• Along with using AI to analyze and summarize the audio recording, Axon experimented with computer vision to summarize what’s “seen” in the video footage, before quickly realizing that the technology was not ready.

Customer service operations

Before trying out the tool in Oklahoma City, police officials showed it to local prosecutors who advised some caution before using it on high-stakes criminal cases. For now, it’s only used for minor incident reports that don’t lead to someone getting arrested. According to a report from OpsRamp, enterprises are using AIOps platforms for intelligent alerting (70%), root cause analysis (57%), anomaly and threat detection (52%), incident auto-remediation (50%), and capacity optimization (27%).

Following is our analysis of the 12 most popular ways AI is being used across all industries in the enterprise today, as companies seek to capitalize on artificial intelligence’s promise to improve customer service, cut business costs, and supercharge business processes. Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand. For example, AI and ML are being increasingly used in marketing to provide faster replies to customers than humans.

Approximately 70 percent of enterprises are using ChatGPT for software development activities, while 65 percent are hiring MSPs to drive many of their GenAI initiatives. Normally, the Oklahoma City police sergeant would grab his laptop and spend another 30 to 45 minutes writing up a report about the search. Those experiments led Axon to focus squarely on audio in the product unveiled in April during its annual company conference for police officials. Machine-generated content still lacks the emotional intelligence that comes with human creativity. As such, it can mute the personality of a brand, which, in turn, can negatively impact customer loyalty, engagement and brand perception. Furthermore, generative AI can analyze data and identify consumer behavior patterns to help marketers create appealing content that resonates with their audience.