Agentic AI systems, software agents with autonomy, decision-making ability, and adaptability, are increasingly used to execute complex tasks on behalf of organisations. Most such systems rely on Large Language Models (LLMs), whose broad semantic capabilities enable powerful language processing but lack explicit, institution-specific grounding. In enterprises, data rarely comes with an inspectable semantic layer, and constructing one typically requires labour-intensive "data archaeology": cleaning, modelling, and curating knowledge into ontologies, taxonomies, and other formal structures. At the same time, explainability methods such as saliency maps expose an "interpretability gap": they highlight what the model attends to but not why, leaving decision processes opaque. In this preprint, we present a case study, developed by Kaiasm and Avantra AI through their work with The Turing Way Practitioners Hub, a forum developed under the InnovateUK BridgeAI program. This study presents a collaborative human-AI approach to building an inspectable semantic layer for Agentic AI. AI agents first propose candidate knowledge structures from diverse data sources; domain experts then validate, correct, and extend these structures, with their feedback used to improve subsequent models. Authors show how this process captures tacit institutional knowledge, improves response quality and efficiency, and mitigates institutional amnesia. We argue for a shift from post-hoc explanation to justifiable Agentic AI, where decisions are grounded in explicit, inspectable evidence and reasoning accessible to both experts and non-specialists.

As this season's fashion weeks wrap up in London, Milan, New York, and Paris, brands are working to produce and sell the designs they've just showcased on runways--and they're starting next season's collections. In the future, it's entirely possible that those designs will blend the prowess of a creative director with the power of generative artificial intelligence (AI), helping to bring clothes and accessories to market faster, selling them more efficiently, and improving the customer experience. By now, you've likely heard of OpenAI's ChatGPT, the AI chatbot that became an overnight sensation and sparked a digital race to build and release competitors. ChatGPT is only one consumer-friendly example of generative AI, a technology comprising algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. Rather than simply identifying and classifying information, generative AI creates new information by leveraging foundation models, which are deep learning models that can handle multiple complex tasks at the same time.

It can also help small- and medium-sized businesses (SMBs) sell smarter and more efficiently, regardless of a company's resources. In the very near future, I imagine a world in which SMBs use generative AI through Sales Cloud to streamline the sales process and close more deals faster and with fewer resources. Capabilities like automated, AI-generated proposals and customer communications, along with predictive sales modeling, will give SMBs even more powerful tools to help them provide great customer experiences, manage operating expenses, and achieve sustainable growth. Generative AI is technology built on pre-trained, large-language models that help users create unique text, images, and other content from text-based prompts. Although it has the potential to transform sales, it will face several hurdles before it can become mainstream.

A chatbot is a marketing tool that imitates human communication to help brands optimize their marketing efforts and engage with customers throughout the day. They leverage messaging mediums like SMS, social media sites, and website pop-ups to receive and respond to messages. Brands can program their chatbots marketing tool to respond to certain messages the same way or use machine learning to give appropriate responses to specific questions. They allow brands to respond to pressing customer issues on time, whether users want to book a flight or return an item. Customers expect quick responses from the brands they are buying from, and chatbots for marketing allow them to reply instantly.

The 21st century has brought many incredible new technologies that were once dreamed about in old sci-fi epics, and even some technologies we never saw coming. However, artificial intelligence -- sometimes called machine intelligence or just AI -- is proving to be one of the most disruptive of all. It's already being applied by businesses across the globe in a variety of ways, from automating a portion of customer communications to determining product/market fit. A survey of CEOs from small and medium-sized businesses conducted by executive coaching company Vistage found that AI is quickly becoming an important part of business processes. In the survey, 29.5% of leaders said that of new technologies, AI will have the greatest impact on their business in the next year.

Existing and prospective customers now expect prompt, appropriate answers via the channel of their choice, or they may look to your competitors. For insurance carriers, customer retention relies on trusted communication between the company and its customers--often by way of representatives like brokers and agents. Developing and maintaining that trust depends heavily on the quality of policyholder communications: knowing and understanding your customers and presenting your brand in such a way that customers feel they know and understand you. While this seems a simple concept, in this era of digital communications it requires--and customers expect--the intimacy of personal interaction distributed through sophisticated and varied media channels and devices. The customer communication management (CCM) systems that many insurers employ today are able to create communications to be delivered via the various channels that customers prefer.

Long gone are the days when responding to a comment was enough. Many businesses are now taking the leap from customer service to being customer-centric, seeing it as the key to thriving even in today's ever-competitive environment. However, achieving this goal might not be as easy. Sorting voluminous client communication, extracting the most valuable data, and designing personalization strategies are only a few of the many actions to navigate. Artificial intelligence (AI) has emerged as a powerful ally.

Artificial intelligence is at the cutting edge of the digital revolution. Reduced operating costs, increased revenue, and optimized customer experience is three of the main benefits of artificial intelligence for business today. AI tools and solutions are becoming more advanced, changing the entire way companies work, market products, and communicate with consumers. It's an exciting stage of the digital revolution, with an opportunity for early adopters to leverage AI to achieve a competitive advantage. Today's consumer landscape is more crowded than ever before.

As mentioned above, these have gone awry in some instances, but today's chatbots are specifically designed for customer communications. There's no chance you'll unleash Tay on your prospects. These bots can answer common questions and help prospects find the resources and contacts they're seeking quickly. Email automation: There are many ways to use AI with email. For example, some solutions enable you to send out customized newsletters, optimized by the AI based on what previously engaged the reader enough to click through.

Chatbots have become an integral part of digital communication across web, social media, and mobile app interfaces. Marketers are increasingly growing fond of chatbots because of effortless, fast-paced, and customer-centric communication in different contexts. With the increasing popularity of chatbots, more and more brands are embracing them. In 2019 and beyond, we can expect chatbots to play a mission-critical role in marketing. Let's dive into the increasing influence of chatbot marketing through some credible statistics: Let's offer some more insights regarding the popularity of the Chatbots.